cuda_std 0.2.2

//! Raw libdevice math intrinsics.
//!
//! Note that this file was autogenerated using crude text analysis
//! from the libdevice PDF file, therefore many of the descriptions have broken
//! text, especially for math symbols. The link to the libdevice website is provided
//! for every intrinsic so you can view the non-broken description.
//!
//! Most of the intrinsics here have "proper" functions, corresponding f32/f64 functions
//! are already codegenned to libdevice intrinsics by the codegen automatically. This module
//! is mostly for exotic intrinsics that have not been added as proper functions yet.
//!
//! The underlying intrinsic functions have a prefix of `__nv_`, however this prefix
//! is stripped from the functions in this module just for convenience.

// Generated file, do not edit by hand, see scripts/gen_intrinsics.py

extern "C" {
    #[link_name = "__nv_abs"]
    #[doc = "Determine the absolute value of the 32-bit signed integer x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_abs.html#__nv_abs)

# Returns

Returns the absolute value of the 32-bit signed integer x."]
    pub fn abs(x: i32) -> i32;

    #[link_name = "__nv_acos"]
    #[doc = "Calculate the principal value of the arc cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_acos.html#__nv_acos)

# Returns

Result will be in radians, in the interval [0, ] for inside [-1, +1]x.
- __nv_acos(1) returns +0.
- __nv_acos(x) returns NaN for x outside [-1, +1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn acos(x: f64) -> f64;

    #[link_name = "__nv_acosf"]
    #[doc = "Calculate the principal value of the arc cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_acosf.html#__nv_acosf)

# Returns

Result will be in radians, in the interval [0, ] for inside [-1, +1]x.
- __nv_acosf(1) returns +0.
- __nv_acosf(x) returns NaN for x outside [-1, +1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn acosf(x: f32) -> f32;

    #[link_name = "__nv_acosh"]
    #[doc = "Calculate the nonnegative arc hyperbolic cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_acosh.html#__nv_acosh)

# Returns

Result will be in the interval [0, ].
- __nv_acosh(1) returns 0.
- __nv_acosh(x) returns NaN for x in the interval [ , 1).
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn acosh(x: f64) -> f64;

    #[link_name = "__nv_acoshf"]
    #[doc = "Calculate the nonnegative arc hyperbolic cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_acoshf.html#__nv_acoshf)

# Returns

Result will be in the interval [0, ].
- __nv_acoshf(1) returns 0.
- __nv_acoshf(x) returns NaN for x in the interval [ , 1).
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn acoshf(x: f32) -> f32;

    #[link_name = "__nv_asin"]
    #[doc = "Calculate the principal value of the arc sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_asin.html#__nv_asin)

# Returns

Result will be in radians, in the interval [- /2, + /2] for inside [-1, +1]x.
- __nv_asin(0) returns +0.
- __nv_asin(x) returns NaN for x outside [-1, +1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn asin(x: f64) -> f64;

    #[link_name = "__nv_asinf"]
    #[doc = "Calculate the principal value of the arc sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_asinf.html#__nv_asinf)

# Returns

Result will be in radians, in the interval [- /2, + /2] for inside [-1, +1]x.
- __nv_asinf(0) returns +0.
- __nv_asinf(x) returns NaN for x outside [-1, +1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn asinf(x: f32) -> f32;

    #[link_name = "__nv_asinh"]
    #[doc = "Calculate the arc hyperbolic sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_asinh.html#__nv_asinh)

# Returns

- __nv_asinh(0) returns 1.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn asinh(x: f64) -> f64;

    #[link_name = "__nv_asinhf"]
    #[doc = "Calculate the arc hyperbolic sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_asinhf.html#__nv_asinhf)

# Returns

- __nv_asinh(0) returns 1.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn asinhf(x: f32) -> f32;

    #[link_name = "__nv_atan"]
    #[doc = "Calculate the principal value of the arc tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atan.html#__nv_atan)

# Returns

Result will be in radians, in the interval [- /2, + /2].
- __nv_atan(0) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn atan(x: f64) -> f64;

    #[link_name = "__nv_atan2"]
    #[doc = "Calculate the principal value of the arc tangent of the ratio of first and second input
arguments / . The quadrant of the result is determined by the signs of inputs and x. y x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atan2.html#__nv_atan2)

# Returns

Result will be in radians, in the interval [- /, + ].
- __nv_atan2(0, 1) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn atan2(x: f64, y: f64) -> f64;

    #[link_name = "__nv_atan2f"]
    #[doc = "Calculate the principal value of the arc tangent of the ratio of first and second input
arguments / . The quadrant of the result is determined by the signs of inputs and x. y x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atan2f.html#__nv_atan2f)

# Returns

Result will be in radians, in the interval [- /, + ].
- __nv_atan2f(0, 1) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn atan2f(x: f32, y: f32) -> f32;

    #[link_name = "__nv_atanf"]
    #[doc = "Calculate the principal value of the arc tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atanf.html#__nv_atanf)

# Returns

Result will be in radians, in the interval [- /2, + /2].
- __nv_atan(0) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn atanf(x: f32) -> f32;

    #[link_name = "__nv_atanh"]
    #[doc = "Calculate the arc hyperbolic tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atanh.html#__nv_atanh)

# Returns

- __nv_atanh( ) returns .
- __nv_atanh( ) returns .
- __nv_atanh(x) returns NaN for x outside interval [-1, 1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn atanh(x: f64) -> f64;

    #[link_name = "__nv_atanhf"]
    #[doc = "Calculate the arc hyperbolic tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_atanhf.html#__nv_atanhf)

# Returns

- __nv_atanhf( ) returns .
- __nv_atanhf( ) returns .
- __nv_atanhf(x) returns NaN for x outside interval [-1, 1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn atanhf(x: f32) -> f32;

    #[link_name = "__nv_brev"]
    #[doc = "Reverses the bit order of the 32 bit unsigned integer x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_brev.html#__nv_brev)

# Returns

Returns the bit-reversed value of . i.e. bit N of the return value corresponds to bit 31-Nx
of x."]
    pub fn brev(x: i32) -> i32;

    #[link_name = "__nv_brevll"]
    #[doc = "Reverses the bit order of the 64 bit unsigned integer x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_brevll.html#__nv_brevll)

# Returns

Returns the bit-reversed value of . i.e. bit N of the return value corresponds to bit 63-Nx
of x."]
    pub fn brevll(x: i64) -> i64;

    #[link_name = "__nv_byte_perm"]
    #[doc = "__nv_byte_perm(x,y,s) returns a 32-bit integer consisting of four bytes from eight input
bytes provided in the two input integers and , as specified by a selector, x. y s
The input bytes are indexed as follows:
 input[0] = x<7:0> input[1] = x<15:8>
 input[2] = x<23:16> input[3] = x<31:24>
 input[4] = y<7:0> input[5] = y<15:8>
 input[6] = y<23:16> input[7] = y<31:24>
 
The selector indices are as follows (the upper 16-bits of the selector are not used):
 selector[0] = s<2:0> selector[1] = s<6:4>
 selector[2] = s<10:8> selector[3] = s<14:12>

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_byte_perm.html#__nv_byte_perm)

# Returns

The returned value r is computed to be: 
result[n] := input[selector[n]]
where is the nth byte of r.
result[n]"]
    pub fn byte_perm(x: i32, y: i32, z: i32) -> i32;

    #[link_name = "__nv_cbrt"]
    #[doc = "Calculate the cube root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cbrt.html#__nv_cbrt)

# Returns

Returns .
- __nv_cbrt( ) returns .
- __nv_cbrt( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn cbrt(x: f64) -> f64;

    #[link_name = "__nv_cbrtf"]
    #[doc = "Calculate the cube root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cbrtf.html#__nv_cbrtf)

# Returns

Returns .
- __nv_cbrtf( ) returns .
- __nv_cbrtf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn cbrtf(x: f32) -> f32;

    #[link_name = "__nv_ceil"]
    #[doc = "Compute the smallest integer value not less than x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ceil.html#__nv_ceil)

# Returns

Returns expressed as a floating-point number.
- __nv_ceil( ) returns .
- __nv_ceil( ) returns ."]
    pub fn ceil(x: f64) -> f64;

    #[link_name = "__nv_ceilf"]
    #[doc = "Compute the smallest integer value not less than x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ceilf.html#__nv_ceilf)

# Returns

Returns expressed as a floating-point number.
- __nv_ceilf( ) returns .
- __nv_ceilf( ) returns ."]
    pub fn ceilf(x: f32) -> f32;

    #[link_name = "__nv_clz"]
    #[doc = "Count the number of consecutive leading zero bits, starting at the most significant bit
(bit 31) of x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_clz.html#__nv_clz)

# Returns

Returns a value between 0 and 32 inclusive representing the number of zero bits."]
    pub fn clz(x: i32) -> i32;

    #[link_name = "__nv_clzll"]
    #[doc = "Count the number of consecutive leading zero bits, starting at the most significant bit
(bit 63) of x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_clzll.html#__nv_clzll)

# Returns

Returns a value between 0 and 64 inclusive representing the number of zero bits."]
    pub fn clzll(x: i64) -> i32;

    #[link_name = "__nv_copysign"]
    #[doc = "Create a floating-point value with the magnitude and the sign of x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_copysign.html#__nv_copysign)

# Returns

Returns a value with the magnitude of and the sign of x. y"]
    pub fn copysign(x: f64, y: f64) -> f64;

    #[link_name = "__nv_copysignf"]
    #[doc = "Create a floating-point value with the magnitude and the sign of x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_copysignf.html#__nv_copysignf)

# Returns

Returns a value with the magnitude of and the sign of x. y"]
    pub fn copysignf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_cos"]
    #[doc = "Calculate the cosine of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cos.html#__nv_cos)

# Returns

- __nv_cos( ) returns 1.
- __nv_cos( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn cos(x: f64) -> f64;

    #[link_name = "__nv_cosf"]
    #[doc = "Calculate the cosine of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cosf.html#__nv_cosf)

# Returns

- __nv_cosf( ) returns 1.
- __nv_cosf( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn cosf(x: f32) -> f32;

    #[link_name = "__nv_cosh"]
    #[doc = "Calculate the hyperbolic cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cosh.html#__nv_cosh)

# Returns

- __nv_cosh(0) returns 1.
- __nv_cosh( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn cosh(x: f64) -> f64;

    #[link_name = "__nv_coshf"]
    #[doc = "Calculate the hyperbolic cosine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_coshf.html#__nv_coshf)

# Returns

- __nv_coshf(0) returns 1.
- __nv_coshf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn coshf(x: f32) -> f32;

    #[link_name = "__nv_cospi"]
    #[doc = "Calculate the cosine of (measured in radians), where is the input argumentx. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cospi.html#__nv_cospi)

# Returns

- __nv_cospi( ) returns 1.
- __nv_cospi( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn cospi(x: f64) -> f64;

    #[link_name = "__nv_cospif"]
    #[doc = "Calculate the cosine of (measured in radians), where is the input argumentx. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_cospif.html#__nv_cospif)

# Returns

- __nv_cospif( ) returns 1.
- __nv_cospif( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn cospif(x: f32) -> f32;

    #[link_name = "__nv_dadd_rd"]
    #[doc = "Adds two floating point values and in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dadd_rd.html#__nv_dadd_rd)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dadd_rd(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dadd_rn"]
    #[doc = "Adds two floating point values and in round-to-nearest-even modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dadd_rn.html#__nv_dadd_rn)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dadd_rn(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dadd_ru"]
    #[doc = "Adds two floating point values and in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dadd_ru.html#__nv_dadd_ru)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dadd_ru(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dadd_rz"]
    #[doc = "Adds two floating point values and in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dadd_rz.html#__nv_dadd_rz)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dadd_rz(x: f64, y: f64) -> f64;

    #[link_name = "__nv_ddiv_rd"]
    #[doc = "Divides two floating point values by in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ddiv_rd.html#__nv_ddiv_rd)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn ddiv_rd(x: f64, y: f64) -> f64;

    #[link_name = "__nv_ddiv_rn"]
    #[doc = "Divides two floating point values by in round-to-nearest-even modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ddiv_rn.html#__nv_ddiv_rn)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn ddiv_rn(x: f64, y: f64) -> f64;

    #[link_name = "__nv_ddiv_ru"]
    #[doc = "Divides two floating point values by in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ddiv_ru.html#__nv_ddiv_ru)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn ddiv_ru(x: f64, y: f64) -> f64;

    #[link_name = "__nv_ddiv_rz"]
    #[doc = "Divides two floating point values by in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ddiv_rz.html#__nv_ddiv_rz)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn ddiv_rz(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dmul_rd"]
    #[doc = "Multiplies two floating point values and in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dmul_rd.html#__nv_dmul_rd)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dmul_rd(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dmul_rn"]
    #[doc = "Multiplies two floating point values and in round-to-nearest-even modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dmul_rn.html#__nv_dmul_rn)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dmul_rn(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dmul_ru"]
    #[doc = "Multiplies two floating point values and in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dmul_ru.html#__nv_dmul_ru)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dmul_ru(x: f64, y: f64) -> f64;

    #[link_name = "__nv_dmul_rz"]
    #[doc = "Multiplies two floating point values and in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dmul_rz.html#__nv_dmul_rz)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
This operation will never be merged into a single multiply-add instruction."]
    pub fn dmul_rz(x: f64, y: f64) -> f64;

    #[link_name = "__nv_double2float_rd"]
    #[doc = "Convert the double-precision floating point value to a single-precision floating pointx
value in round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2float_rd.html#__nv_double2float_rd)

# Returns

Returns converted value."]
    pub fn double2float_rd(d: f64) -> f32;

    #[link_name = "__nv_double2float_rn"]
    #[doc = "Convert the double-precision floating point value to a single-precision floating pointx
value in round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2float_rn.html#__nv_double2float_rn)

# Returns

Returns converted value."]
    pub fn double2float_rn(d: f64) -> f32;

    #[link_name = "__nv_double2float_ru"]
    #[doc = "Convert the double-precision floating point value to a single-precision floating pointx
value in round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2float_ru.html#__nv_double2float_ru)

# Returns

Returns converted value."]
    pub fn double2float_ru(d: f64) -> f32;

    #[link_name = "__nv_double2float_rz"]
    #[doc = "Convert the double-precision floating point value to a single-precision floating pointx
value in round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2float_rz.html#__nv_double2float_rz)

# Returns

Returns converted value."]
    pub fn double2float_rz(d: f64) -> f32;

    #[link_name = "__nv_double2hiint"]
    #[doc = "Reinterpret the high 32 bits in the double-precision floating point value as a signedx
integer.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2hiint.html#__nv_double2hiint)

# Returns

Returns reinterpreted value."]
    pub fn double2hiint(d: f64) -> i32;

    #[link_name = "__nv_double2int_rd"]
    #[doc = "Convert the double-precision floating point value to a signed integer value in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2int_rd.html#__nv_double2int_rd)

# Returns

Returns converted value."]
    pub fn double2int_rd(d: f64) -> i32;

    #[link_name = "__nv_double2int_rn"]
    #[doc = "Convert the double-precision floating point value to a signed integer value in round-x
to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2int_rn.html#__nv_double2int_rn)

# Returns

Returns converted value."]
    pub fn double2int_rn(d: f64) -> i32;

    #[link_name = "__nv_double2int_ru"]
    #[doc = "Convert the double-precision floating point value to a signed integer value in round-x
up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2int_ru.html#__nv_double2int_ru)

# Returns

Returns converted value."]
    pub fn double2int_ru(d: f64) -> i32;

    #[link_name = "__nv_double2int_rz"]
    #[doc = "Convert the double-precision floating point value to a signed integer value in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2int_rz.html#__nv_double2int_rz)

# Returns

Returns converted value."]
    pub fn double2int_rz(d: f64) -> i32;

    #[link_name = "__nv_double2ll_rd"]
    #[doc = "Convert the double-precision floating point value to a signed 64-bit integer value inx
round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ll_rd.html#__nv_double2ll_rd)

# Returns

Returns converted value."]
    pub fn double2ll_rd(f: f64) -> i64;

    #[link_name = "__nv_double2ll_rn"]
    #[doc = "Convert the double-precision floating point value to a signed 64-bit integer value inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ll_rn.html#__nv_double2ll_rn)

# Returns

Returns converted value."]
    pub fn double2ll_rn(f: f64) -> i64;

    #[link_name = "__nv_double2ll_ru"]
    #[doc = "Convert the double-precision floating point value to a signed 64-bit integer value inx
round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ll_ru.html#__nv_double2ll_ru)

# Returns

Returns converted value."]
    pub fn double2ll_ru(f: f64) -> i64;

    #[link_name = "__nv_double2ll_rz"]
    #[doc = "Convert the double-precision floating point value to a signed 64-bit integer value inx
round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ll_rz.html#__nv_double2ll_rz)

# Returns

Returns converted value."]
    pub fn double2ll_rz(f: f64) -> i64;

    #[link_name = "__nv_double2loint"]
    #[doc = "Reinterpret the low 32 bits in the double-precision floating point value as a signedx
integer.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2loint.html#__nv_double2loint)

# Returns

Returns reinterpreted value."]
    pub fn double2loint(d: f64) -> i32;

    #[link_name = "__nv_double2uint_rd"]
    #[doc = "Convert the double-precision floating point value to an unsigned integer value inx
round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2uint_rd.html#__nv_double2uint_rd)

# Returns

Returns converted value."]
    pub fn double2uint_rd(d: f64) -> i32;

    #[link_name = "__nv_double2uint_rn"]
    #[doc = "Convert the double-precision floating point value to an unsigned integer value inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2uint_rn.html#__nv_double2uint_rn)

# Returns

Returns converted value."]
    pub fn double2uint_rn(d: f64) -> i32;

    #[link_name = "__nv_double2uint_ru"]
    #[doc = "Convert the double-precision floating point value to an unsigned integer value inx
round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2uint_ru.html#__nv_double2uint_ru)

# Returns

Returns converted value."]
    pub fn double2uint_ru(d: f64) -> i32;

    #[link_name = "__nv_double2uint_rz"]
    #[doc = "Convert the double-precision floating point value to an unsigned integer value inx
round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2uint_rz.html#__nv_double2uint_rz)

# Returns

Returns converted value."]
    pub fn double2uint_rz(d: f64) -> i32;

    #[link_name = "__nv_double2ull_rd"]
    #[doc = "Convert the double-precision floating point value to an unsigned 64-bit integer valuex
in round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ull_rd.html#__nv_double2ull_rd)

# Returns

Returns converted value."]
    pub fn double2ull_rd(f: f64) -> i64;

    #[link_name = "__nv_double2ull_rn"]
    #[doc = "Convert the double-precision floating point value to an unsigned 64-bit integer valuex
in round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ull_rn.html#__nv_double2ull_rn)

# Returns

Returns converted value."]
    pub fn double2ull_rn(f: f64) -> i64;

    #[link_name = "__nv_double2ull_ru"]
    #[doc = "Convert the double-precision floating point value to an unsigned 64-bit integer valuex
in round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ull_ru.html#__nv_double2ull_ru)

# Returns

Returns converted value."]
    pub fn double2ull_ru(f: f64) -> i64;

    #[link_name = "__nv_double2ull_rz"]
    #[doc = "Convert the double-precision floating point value to an unsigned 64-bit integer valuex
in round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double2ull_rz.html#__nv_double2ull_rz)

# Returns

Returns converted value."]
    pub fn double2ull_rz(f: f64) -> i64;

    #[link_name = "__nv_double_as_longlong"]
    #[doc = "Reinterpret the bits in the double-precision floating point value as a signed 64-bitx
integer.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_double_as_longlong.html#__nv_double_as_longlong)

# Returns

Returns reinterpreted value."]
    pub fn double_as_longlong(x: f64) -> i64;

    #[link_name = "__nv_drcp_rd"]
    #[doc = "Compute the reciprocal of in round-down (to negative infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_drcp_rd.html#__nv_drcp_rd)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn drcp_rd(x: f64) -> f64;

    #[link_name = "__nv_drcp_rn"]
    #[doc = "Compute the reciprocal of in round-to-nearest-even modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_drcp_rn.html#__nv_drcp_rn)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn drcp_rn(x: f64) -> f64;

    #[link_name = "__nv_drcp_ru"]
    #[doc = "Compute the reciprocal of in round-up (to positive infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_drcp_ru.html#__nv_drcp_ru)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn drcp_ru(x: f64) -> f64;

    #[link_name = "__nv_drcp_rz"]
    #[doc = "Compute the reciprocal of in round-towards-zero modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_drcp_rz.html#__nv_drcp_rz)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn drcp_rz(x: f64) -> f64;

    #[link_name = "__nv_dsqrt_rd"]
    #[doc = "Compute the square root of in round-down (to negative infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dsqrt_rd.html#__nv_dsqrt_rd)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn dsqrt_rd(x: f64) -> f64;

    #[link_name = "__nv_dsqrt_rn"]
    #[doc = "Compute the square root of in round-to-nearest-even modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dsqrt_rn.html#__nv_dsqrt_rn)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn dsqrt_rn(x: f64) -> f64;

    #[link_name = "__nv_dsqrt_ru"]
    #[doc = "Compute the square root of in round-up (to positive infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dsqrt_ru.html#__nv_dsqrt_ru)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn dsqrt_ru(x: f64) -> f64;

    #[link_name = "__nv_dsqrt_rz"]
    #[doc = "Compute the square root of in round-towards-zero modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_dsqrt_rz.html#__nv_dsqrt_rz)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7.
Requires compute capability >= 2.0."]
    pub fn dsqrt_rz(x: f64) -> f64;

    #[link_name = "__nv_erf"]
    #[doc = "Calculate the value of the error function for the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erf.html#__nv_erf)

# Returns

- __nv_erf( ) returns .
- __nv_erf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn erf(x: f64) -> f64;

    #[link_name = "__nv_erfc"]
    #[doc = "Calculate the complementary error function of the input argument , 1 - erf( )x. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfc.html#__nv_erfc)

# Returns

- __nv_erfc( ) returns 2.
- __nv_erfc( ) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn erfc(x: f64) -> f64;

    #[link_name = "__nv_erfcf"]
    #[doc = "Calculate the complementary error function of the input argument , 1 - erf( )x. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfcf.html#__nv_erfcf)

# Returns

- __nv_erfcf( ) returns 2.
- __nv_erfcf( ) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn erfcf(x: f32) -> f32;

    #[link_name = "__nv_erfcinv"]
    #[doc = "Calculate the inverse complementary error function of the input argument , for in they y
interval [0, 2]. The inverse complementary error function find the value that satisfiesx
the equation = erfc( ), for , and .y x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfcinv.html#__nv_erfcinv)

# Returns

- __nv_erfcinv(0) returns .
- __nv_erfcinv(2) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn erfcinv(x: f64) -> f64;

    #[link_name = "__nv_erfcinvf"]
    #[doc = "Calculate the inverse complementary error function of the input argument , for in they y
interval [0, 2]. The inverse complementary error function find the value that satisfiesx
the equation = erfc( ), for , and .y x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfcinvf.html#__nv_erfcinvf)

# Returns

- __nv_erfcinvf(0) returns .
- __nv_erfcinvf(2) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn erfcinvf(x: f32) -> f32;

    #[link_name = "__nv_erfcx"]
    #[doc = "Calculate the scaled complementary error function of the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfcx.html#__nv_erfcx)

# Returns

- __nv_erfcx( ) returns 
- __nv_erfcx( ) returns +0
- __nv_erfcx(x) returns if the correctly calculated value is outside the double
floating point range.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn erfcx(x: f64) -> f64;

    #[link_name = "__nv_erfcxf"]
    #[doc = "Calculate the scaled complementary error function of the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfcxf.html#__nv_erfcxf)

# Returns

- __nv_erfcxf( ) returns 
- __nv_erfcxf( ) returns +0
- __nv_erfcxf(x) returns if the correctly calculated value is outside the double
floating point range.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn erfcxf(x: f32) -> f32;

    #[link_name = "__nv_erff"]
    #[doc = "Calculate the value of the error function for the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erff.html#__nv_erff)

# Returns

- __nv_erff( ) returns .
- __nv_erff( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn erff(x: f32) -> f32;

    #[link_name = "__nv_erfinv"]
    #[doc = "Calculate the inverse error function of the input argument , for in the interval [-1,y y
1]. The inverse error function finds the value that satisfies the equation = erf( ), forx y x
 , and .

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfinv.html#__nv_erfinv)

# Returns

- __nv_erfinv(1) returns .
- __nv_erfinv(-1) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn erfinv(x: f64) -> f64;

    #[link_name = "__nv_erfinvf"]
    #[doc = "Calculate the inverse error function of the input argument , for in the interval [-1,y y
1]. The inverse error function finds the value that satisfies the equation = erf( ), forx y x
 , and .

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_erfinvf.html#__nv_erfinvf)

# Returns

- __nv_erfinvf(1) returns .
- __nv_erfinvf(-1) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn erfinvf(x: f32) -> f32;

    #[link_name = "__nv_exp"]
    #[doc = "Calculate the base exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_exp.html#__nv_exp)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn exp(x: f64) -> f64;

    #[link_name = "__nv_exp10"]
    #[doc = "Calculate the base 10 exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_exp10.html#__nv_exp10)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn exp10(x: f64) -> f64;

    #[link_name = "__nv_exp10f"]
    #[doc = "Calculate the base 10 exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_exp10f.html#__nv_exp10f)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn exp10f(x: f32) -> f32;

    #[link_name = "__nv_exp2"]
    #[doc = "Calculate the base 2 exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_exp2.html#__nv_exp2)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn exp2(x: f64) -> f64;

    #[link_name = "__nv_exp2f"]
    #[doc = "Calculate the base 2 exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_exp2f.html#__nv_exp2f)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn exp2f(x: f32) -> f32;

    #[link_name = "__nv_expf"]
    #[doc = "Calculate the base exponential of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_expf.html#__nv_expf)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn expf(x: f32) -> f32;

    #[link_name = "__nv_expm1"]
    #[doc = "Calculate the base exponential of the input argument , minus 1x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_expm1.html#__nv_expm1)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn expm1(x: f64) -> f64;

    #[link_name = "__nv_expm1f"]
    #[doc = "Calculate the base exponential of the input argument , minus 1x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_expm1f.html#__nv_expm1f)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn expm1f(x: f32) -> f32;

    #[link_name = "__nv_fabs"]
    #[doc = "Calculate the absolute value of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fabs.html#__nv_fabs)

# Returns

Returns the absolute value of the input argument.
- __nv_fabs( ) returns .
- __nv_fabs( ) returns 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fabs(f: f64) -> f64;

    #[link_name = "__nv_fabsf"]
    #[doc = "Calculate the absolute value of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fabsf.html#__nv_fabsf)

# Returns

Returns the absolute value of the input argument.
- __nv_fabsf( ) returns .
- __nv_fabsf( ) returns 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fabsf(f: f32) -> f32;

    #[link_name = "__nv_fadd_rd"]
    #[doc = "Compute the sum of and in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fadd_rd.html#__nv_fadd_rd)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fadd_rd(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fadd_rn"]
    #[doc = "Compute the sum of and in round-to-nearest-even rounding modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fadd_rn.html#__nv_fadd_rn)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fadd_rn(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fadd_ru"]
    #[doc = "Compute the sum of and in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fadd_ru.html#__nv_fadd_ru)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fadd_ru(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fadd_rz"]
    #[doc = "Compute the sum of and in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fadd_rz.html#__nv_fadd_rz)

# Returns

Returns + x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fadd_rz(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fast_cosf"]
    #[doc = "Calculate the fast approximate cosine of the input argument , measured in radiansx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_cosf.html#__nv_fast_cosf)

# Returns

Returns the approximate cosine of x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Input and output in the denormal range is flushed to sign preserving 0.0."]
    pub fn fast_cosf(x: f32) -> f32;

    #[link_name = "__nv_fast_exp10f"]
    #[doc = "Calculate the fast approximate base 10 exponential of the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_exp10f.html#__nv_fast_exp10f)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Most input and output values around denormal range are flushed to sign preserving
0.0."]
    pub fn fast_exp10f(x: f32) -> f32;

    #[link_name = "__nv_fast_expf"]
    #[doc = "Calculate the fast approximate base exponential of the input argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_expf.html#__nv_fast_expf)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Most input and output values around denormal range are flushed to sign preserving
0.0."]
    pub fn fast_expf(x: f32) -> f32;

    #[link_name = "__nv_fast_fdividef"]
    #[doc = "Calculate the fast approximate division of by x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_fdividef.html#__nv_fast_fdividef)

# Returns

Returns / x. y
- __nv_fast_fdividef( , ) returns NaN for .y
- __nv_fast_fdividef( , ) returns 0 for and x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9."]
    pub fn fast_fdividef(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fast_log10f"]
    #[doc = "Calculate the fast approximate base 10 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_log10f.html#__nv_fast_log10f)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Most input and output values around denormal range are flushed to sign preserving
0.0."]
    pub fn fast_log10f(x: f32) -> f32;

    #[link_name = "__nv_fast_log2f"]
    #[doc = "Calculate the fast approximate base 2 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_log2f.html#__nv_fast_log2f)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Input and output in the denormal range is flushed to sign preserving 0.0."]
    pub fn fast_log2f(x: f32) -> f32;

    #[link_name = "__nv_fast_logf"]
    #[doc = "Calculate the fast approximate base logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_logf.html#__nv_fast_logf)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Most input and output values around denormal range are flushed to sign preserving
0.0."]
    pub fn fast_logf(x: f32) -> f32;

    #[link_name = "__nv_fast_powf"]
    #[doc = "Calculate the fast approximate of , the first input argument, raised to the power of ,x y
the second input argument, .

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_powf.html#__nv_fast_powf)

# Returns

Returns an approximation to .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Most input and output values around denormal range are flushed to sign preserving
0.0."]
    pub fn fast_powf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fast_sincosf"]
    #[doc = "Calculate the fast approximate of sine and cosine of the first input argument x
(measured in radians). The results for sine and cosine are written into the second
argument, , and, respectively, third argument, .
sptr zptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_sincosf.html#__nv_fast_sincosf)

# Returns

- none
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Denorm input/output is flushed to sign preserving 0.0."]
    pub fn fast_sincosf(x: f32, sptr: *mut f32, cptr: *mut f32) -> ();

    #[link_name = "__nv_fast_sinf"]
    #[doc = "Calculate the fast approximate sine of the input argument , measured in radiansx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_sinf.html#__nv_fast_sinf)

# Returns

Returns the approximate sine of x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
Input and output in the denormal range is flushed to sign preserving 0.0."]
    pub fn fast_sinf(x: f32) -> f32;

    #[link_name = "__nv_fast_tanf"]
    #[doc = "Calculate the fast approximate tangent of the input argument , measured in radiansx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fast_tanf.html#__nv_fast_tanf)

# Returns

Returns the approximate tangent of x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.2, Table 9.
The result is computed as the fast divide of __nv_sinf() by __nv_cosf(). Denormal
input and output are flushed to sign-preserving 0.0 at each step of the computation."]
    pub fn fast_tanf(x: f32) -> f32;

    #[link_name = "__nv_fdim"]
    #[doc = "Compute the positive difference between and . The positive difference is - when x y x y x
> and +0 otherwise.y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdim.html#__nv_fdim)

# Returns

Returns the positive difference between and x. y
- __nv_fdim(x, y) returns x - y if x > y.
- __nv_fdim(x, y) returns +0 if x y.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdim(x: f64, y: f64) -> f64;

    #[link_name = "__nv_fdimf"]
    #[doc = "Compute the positive difference between and . The positive difference is - when x y x y x
> and +0 otherwise.y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdimf.html#__nv_fdimf)

# Returns

Returns the positive difference between and x. y
- __nv_fdimf(x, y) returns x - y if x > y.
- __nv_fdimf(x, y) returns +0 if x y.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdimf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fdiv_rd"]
    #[doc = "Divide two floating point values by in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdiv_rd.html#__nv_fdiv_rd)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdiv_rd(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fdiv_rn"]
    #[doc = "Divide two floating point values by in round-to-nearest-even modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdiv_rn.html#__nv_fdiv_rn)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdiv_rn(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fdiv_ru"]
    #[doc = "Divide two floating point values by in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdiv_ru.html#__nv_fdiv_ru)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdiv_ru(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fdiv_rz"]
    #[doc = "Divide two floating point values by in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fdiv_rz.html#__nv_fdiv_rz)

# Returns

Returns / x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fdiv_rz(x: f32, y: f32) -> f32;

    #[link_name = "__nv_ffs"]
    #[doc = "Find the position of the first (least significant) bit set to 1 in , where the least significantx
bit position is 1.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ffs.html#__nv_ffs)

# Returns

Returns a value between 0 and 32 inclusive representing the position of the first bit set.
- __nv_ffs(0) returns 0."]
    pub fn ffs(x: i32) -> i32;

    #[link_name = "__nv_ffsll"]
    #[doc = "Find the position of the first (least significant) bit set to 1 in , where the least significantx
bit position is 1.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ffsll.html#__nv_ffsll)

# Returns

Returns a value between 0 and 64 inclusive representing the position of the first bit set.
- __nv_ffsll(0) returns 0."]
    pub fn ffsll(x: i64) -> i32;

    #[link_name = "__nv_finitef"]
    #[doc = "Determine whether the floating-point value is a finite valuex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_finitef.html#__nv_finitef)

# Returns

Returns a non-zero value if and only if is a finite valuex."]
    pub fn finitef(x: f32) -> i32;

    #[link_name = "__nv_float2half_rn"]
    #[doc = "Convert the single-precision float value to a half-precision floating point valuex
represented in format, in round-to-nearest-even mode.
unsigned short

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2half_rn.html#__nv_float2half_rn)

# Returns

Returns converted value."]
    pub fn float2half_rn(f: f32) -> i16;

    #[link_name = "__nv_float2int_rd"]
    #[doc = "Convert the single-precision floating point value to a signed integer in round-down (tox
negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2int_rd.html#__nv_float2int_rd)

# Returns

Returns converted value."]
    pub fn float2int_rd(in_: f32) -> i32;

    #[link_name = "__nv_float2int_rn"]
    #[doc = "Convert the single-precision floating point value to a signed integer in round-to-x
nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2int_rn.html#__nv_float2int_rn)

# Returns

Returns converted value."]
    pub fn float2int_rn(in_: f32) -> i32;

    #[link_name = "__nv_float2int_ru"]
    #[doc = "Convert the single-precision floating point value to a signed integer in round-up (tox
positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2int_ru.html#__nv_float2int_ru)

# Returns

Returns converted value."]
    pub fn float2int_ru(in_: f32) -> i32;

    #[link_name = "__nv_float2int_rz"]
    #[doc = "Convert the single-precision floating point value to a signed integer in round-towards-x
zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2int_rz.html#__nv_float2int_rz)

# Returns

Returns converted value."]
    pub fn float2int_rz(in_: f32) -> i32;

    #[link_name = "__nv_float2ll_rd"]
    #[doc = "Convert the single-precision floating point value to a signed 64-bit integer in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ll_rd.html#__nv_float2ll_rd)

# Returns

Returns converted value."]
    pub fn float2ll_rd(f: f32) -> i64;

    #[link_name = "__nv_float2ll_rn"]
    #[doc = "Convert the single-precision floating point value to a signed 64-bit integer in round-to-x
nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ll_rn.html#__nv_float2ll_rn)

# Returns

Returns converted value."]
    pub fn float2ll_rn(f: f32) -> i64;

    #[link_name = "__nv_float2ll_ru"]
    #[doc = "Convert the single-precision floating point value to a signed 64-bit integer in round-upx
(to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ll_ru.html#__nv_float2ll_ru)

# Returns

Returns converted value."]
    pub fn float2ll_ru(f: f32) -> i64;

    #[link_name = "__nv_float2ll_rz"]
    #[doc = "Convert the single-precision floating point value to a signed 64-bit integer in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ll_rz.html#__nv_float2ll_rz)

# Returns

Returns converted value."]
    pub fn float2ll_rz(f: f32) -> i64;

    #[link_name = "__nv_float2uint_rd"]
    #[doc = "Convert the single-precision floating point value to an unsigned integer in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2uint_rd.html#__nv_float2uint_rd)

# Returns

Returns converted value."]
    pub fn float2uint_rd(in_: f32) -> i32;

    #[link_name = "__nv_float2uint_rn"]
    #[doc = "Convert the single-precision floating point value to an unsigned integer in round-to-x
nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2uint_rn.html#__nv_float2uint_rn)

# Returns

Returns converted value."]
    pub fn float2uint_rn(in_: f32) -> i32;

    #[link_name = "__nv_float2uint_ru"]
    #[doc = "Convert the single-precision floating point value to an unsigned integer in round-upx
(to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2uint_ru.html#__nv_float2uint_ru)

# Returns

Returns converted value."]
    pub fn float2uint_ru(in_: f32) -> i32;

    #[link_name = "__nv_float2uint_rz"]
    #[doc = "Convert the single-precision floating point value to an unsigned integer in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2uint_rz.html#__nv_float2uint_rz)

# Returns

Returns converted value."]
    pub fn float2uint_rz(in_: f32) -> i32;

    #[link_name = "__nv_float2ull_rd"]
    #[doc = "Convert the single-precision floating point value to an unsigned 64-bit integer inx
round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ull_rd.html#__nv_float2ull_rd)

# Returns

Returns converted value."]
    pub fn float2ull_rd(f: f32) -> i64;

    #[link_name = "__nv_float2ull_rn"]
    #[doc = "Convert the single-precision floating point value to an unsigned 64-bit integer inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ull_rn.html#__nv_float2ull_rn)

# Returns

Returns converted value."]
    pub fn float2ull_rn(f: f32) -> i64;

    #[link_name = "__nv_float2ull_ru"]
    #[doc = "Convert the single-precision floating point value to an unsigned 64-bit integer inx
round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ull_ru.html#__nv_float2ull_ru)

# Returns

Returns converted value."]
    pub fn float2ull_ru(f: f32) -> i64;

    #[link_name = "__nv_float2ull_rz"]
    #[doc = "Convert the single-precision floating point value to an unsigned 64-bit integer inx
round-towards_zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float2ull_rz.html#__nv_float2ull_rz)

# Returns

Returns converted value."]
    pub fn float2ull_rz(f: f32) -> i64;

    #[link_name = "__nv_float_as_int"]
    #[doc = "Reinterpret the bits in the single-precision floating point value as a signed integerx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_float_as_int.html#__nv_float_as_int)

# Returns

Returns reinterpreted value."]
    pub fn float_as_int(x: f32) -> i32;

    #[link_name = "__nv_floor"]
    #[doc = "Calculates the largest integer value which is less than or equal to x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_floor.html#__nv_floor)

# Returns

Returns the largest integer value which is less than or equal to x expressed as a floating-
point number.
- __nv_floor( ) returns .
- __nv_floor( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn floor(f: f64) -> f64;

    #[link_name = "__nv_floorf"]
    #[doc = "Calculates the largest integer value which is less than or equal to x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_floorf.html#__nv_floorf)

# Returns

Returns the largest integer value which is less than or equal to x expressed as a floating-
point number.
- __nv_floorf( ) returns .
- __nv_floorf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn floorf(f: f32) -> f32;

    #[link_name = "__nv_fma"]
    #[doc = "Compute the value of as a single ternary operation. After computing the value
to infinite precision, the value is rounded once.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fma.html#__nv_fma)

# Returns

Returns the rounded value of as a single operation.
- __nv_fma( , , z) returns NaN.
- __nv_fma( , , z) returns NaN.
- __nv_fma(x, y, ) returns NaN if is an exact .
- __nv_fma(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fma(x: f64, y: f64, z: f64) -> f64;

    #[link_name = "__nv_fma_rd"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fma_rd.html#__nv_fma_rd)

# Returns

Returns the rounded value of as a single operation.
- __nv_fma_rd( , , z) returns NaN.
- __nv_fma_rd( , , z) returns NaN.
- __nv_fma_rd(x, y, ) returns NaN if is an exact 
- __nv_fma_rd(x, y, ) returns NaN if is an exact 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fma_rd(x: f64, y: f64, z: f64) -> f64;

    #[link_name = "__nv_fma_rn"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fma_rn.html#__nv_fma_rn)

# Returns

Returns the rounded value of as a single operation.
- __nv_fma_rn( , , z) returns NaN.
- __nv_fma_rn( , , z) returns NaN.
- __nv_fma_rn(x, y, ) returns NaN if is an exact 
- __nv_fma_rn(x, y, ) returns NaN if is an exact 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fma_rn(x: f64, y: f64, z: f64) -> f64;

    #[link_name = "__nv_fma_ru"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fma_ru.html#__nv_fma_ru)

# Returns

Returns the rounded value of as a single operation.
- __nv_fma_ru( , , z) returns NaN.
- __nv_fma_ru( , , z) returns NaN.
- __nv_fma_ru(x, y, ) returns NaN if is an exact 
- __nv_fma_ru(x, y, ) returns NaN if is an exact 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fma_ru(x: f64, y: f64, z: f64) -> f64;

    #[link_name = "__nv_fma_rz"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fma_rz.html#__nv_fma_rz)

# Returns

Returns the rounded value of as a single operation.
- __nv_fma_rz( , , z) returns NaN.
- __nv_fma_rz( , , z) returns NaN.
- __nv_fma_rz(x, y, ) returns NaN if is an exact 
- __nv_fma_rz(x, y, ) returns NaN if is an exact 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fma_rz(x: f64, y: f64, z: f64) -> f64;

    #[link_name = "__nv_fmaf"]
    #[doc = "Compute the value of as a single ternary operation. After computing the value
to infinite precision, the value is rounded once.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaf.html#__nv_fmaf)

# Returns

Returns the rounded value of as a single operation.
- __nv_fmaf( , , z) returns NaN.
- __nv_fmaf( , , z) returns NaN.
- __nv_fmaf(x, y, ) returns NaN if is an exact .
- __nv_fmaf(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmaf(x: f32, y: f32, z: f32) -> f32;

    #[link_name = "__nv_fmaf_rd"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaf_rd.html#__nv_fmaf_rd)

# Returns

Returns the rounded value of as a single operation.
- __nv_fmaf_rd( , , z) returns NaN.
- __nv_fmaf_rd( , , z) returns NaN.
- __nv_fmaf_rd(x, y, ) returns NaN if is an exact .
- __nv_fmaf_rd(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmaf_rd(x: f32, y: f32, z: f32) -> f32;

    #[link_name = "__nv_fmaf_rn"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaf_rn.html#__nv_fmaf_rn)

# Returns

Returns the rounded value of as a single operation.
- __nv_fmaf_rn( , , z) returns NaN.
- __nv_fmaf_rn( , , z) returns NaN.
- __nv_fmaf_rn(x, y, ) returns NaN if is an exact .
- __nv_fmaf_rn(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmaf_rn(x: f32, y: f32, z: f32) -> f32;

    #[link_name = "__nv_fmaf_ru"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaf_ru.html#__nv_fmaf_ru)

# Returns

Returns the rounded value of as a single operation.
- __nv_fmaf_ru( , , z) returns NaN.
- __nv_fmaf_ru( , , z) returns NaN.
- __nv_fmaf_ru(x, y, ) returns NaN if is an exact .
- __nv_fmaf_ru(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmaf_ru(x: f32, y: f32, z: f32) -> f32;

    #[link_name = "__nv_fmaf_rz"]
    #[doc = "Computes the value of as a single ternary operation, rounding the result once
in round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaf_rz.html#__nv_fmaf_rz)

# Returns

Returns the rounded value of as a single operation.
- __nv_fmaf_rz( , , z) returns NaN.
- __nv_fmaf_rz( , , z) returns NaN.
- __nv_fmaf_rz(x, y, ) returns NaN if is an exact .
- __nv_fmaf_rz(x, y, ) returns NaN if is an exact .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmaf_rz(x: f32, y: f32, z: f32) -> f32;

    #[link_name = "__nv_fmax"]
    #[doc = "Determines the maximum numeric value of the arguments and . Treats NaNx y
arguments as missing data. If one argument is a NaN and the other is legitimate numeric
value, the numeric value is chosen.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmax.html#__nv_fmax)

# Returns

Returns the maximum numeric values of the arguments and x. y
- If both arguments are NaN, returns NaN.
- If one argument is NaN, returns the numeric argument.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fmax(x: f64, y: f64) -> f64;

    #[link_name = "__nv_fmaxf"]
    #[doc = "Determines the maximum numeric value of the arguments and . Treats NaNx y
arguments as missing data. If one argument is a NaN and the other is legitimate numeric
value, the numeric value is chosen.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmaxf.html#__nv_fmaxf)

# Returns

Returns the maximum numeric values of the arguments and x. y
- If both arguments are NaN, returns NaN.
- If one argument is NaN, returns the numeric argument.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fmaxf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmin"]
    #[doc = "Determines the minimum numeric value of the arguments and . Treats NaNx y
arguments as missing data. If one argument is a NaN and the other is legitimate numeric
value, the numeric value is chosen.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmin.html#__nv_fmin)

# Returns

Returns the minimum numeric values of the arguments and x. y
- If both arguments are NaN, returns NaN.
- If one argument is NaN, returns the numeric argument.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fmin(x: f64, y: f64) -> f64;

    #[link_name = "__nv_fminf"]
    #[doc = "Determines the minimum numeric value of the arguments and . Treats NaNx y
arguments as missing data. If one argument is a NaN and the other is legitimate numeric
value, the numeric value is chosen.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fminf.html#__nv_fminf)

# Returns

Returns the minimum numeric values of the arguments and x. y
- If both arguments are NaN, returns NaN.
- If one argument is NaN, returns the numeric argument.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fminf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmod"]
    #[doc = "Calculate the floating-point remainder of / . The absolute value of the computedx y
value is always less than absolute value and will have the same sign as .y's x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmod.html#__nv_fmod)

# Returns

- Returns the floating point remainder of x / y.
- __nv_fmod( , y) returns if y is not zero.
- __nv_fmod(x, y) returns NaN and raised an invalid floating point exception if x is
 or is zero.y
- __nv_fmod(x, y) returns zero if y is zero or the result would overflow.
- __nv_fmod(x, ) returns x if x is finite.
- __nv_fmod(x, 0) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn fmod(x: f64, y: f64) -> f64;

    #[link_name = "__nv_fmodf"]
    #[doc = "Calculate the floating-point remainder of / . The absolute value of the computedx y
value is always less than absolute value and will have the same sign as .y's x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmodf.html#__nv_fmodf)

# Returns

- Returns the floating point remainder of x / y.
- __nv_fmodf( , y) returns if y is not zero.
- __nv_fmodf(x, y) returns NaN and raised an invalid floating point exception if x is
 or is zero.y
- __nv_fmodf(x, y) returns zero if y is zero or the result would overflow.
- __nv_fmodf(x, ) returns x if x is finite.
- __nv_fmodf(x, 0) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fmodf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmul_rd"]
    #[doc = "Compute the product of and in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmul_rd.html#__nv_fmul_rd)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fmul_rd(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmul_rn"]
    #[doc = "Compute the product of and in round-to-nearest-even modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmul_rn.html#__nv_fmul_rn)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fmul_rn(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmul_ru"]
    #[doc = "Compute the product of and in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmul_ru.html#__nv_fmul_ru)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fmul_ru(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fmul_rz"]
    #[doc = "Compute the product of and in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fmul_rz.html#__nv_fmul_rz)

# Returns

Returns * x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fmul_rz(x: f32, y: f32) -> f32;

    #[link_name = "__nv_frcp_rd"]
    #[doc = "Compute the reciprocal of in round-down (to negative infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frcp_rd.html#__nv_frcp_rd)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frcp_rd(x: f32) -> f32;

    #[link_name = "__nv_frcp_rn"]
    #[doc = "Compute the reciprocal of in round-to-nearest-even modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frcp_rn.html#__nv_frcp_rn)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frcp_rn(x: f32) -> f32;

    #[link_name = "__nv_frcp_ru"]
    #[doc = "Compute the reciprocal of in round-up (to positive infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frcp_ru.html#__nv_frcp_ru)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frcp_ru(x: f32) -> f32;

    #[link_name = "__nv_frcp_rz"]
    #[doc = "Compute the reciprocal of in round-towards-zero modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frcp_rz.html#__nv_frcp_rz)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frcp_rz(x: f32) -> f32;

    #[link_name = "__nv_frexp"]
    #[doc = "Decompose the floating-point value into a component for the normalized fractionx m
element and another term for the exponent. The absolute value of will be greater
n m
than or equal to 0.5 and less than 1.0 or it will be equal to 0; . The integer
exponent will be stored in the location to which points.
n nptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frexp.html#__nv_frexp)

# Returns

Returns the fractional component .
m
- __nv_frexp(0, nptr) returns 0 for the fractional component and zero for the integer
component.
- __nv_frexp( , nptr) returns and stores zero in the location pointed to by
.
nptr
- __nv_frexp( , nptr) returns and stores an unspecified value in the location
to which points.
nptr
- __nv_frexp(NaN, y) returns a NaN and stores an unspecified value in the location to
which points.
nptr
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn frexp(x: f64, b: *mut i32) -> f64;

    #[link_name = "__nv_frexpf"]
    #[doc = "Decompose the floating-point value into a component for the normalized fractionx m
element and another term for the exponent. The absolute value of will be greater
n m
than or equal to 0.5 and less than 1.0 or it will be equal to 0; . The integer
exponent will be stored in the location to which points.
n nptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frexpf.html#__nv_frexpf)

# Returns

Returns the fractional component .
m
- __nv_frexpf(0, nptr) returns 0 for the fractional component and zero for the integer
component.
- __nv_frexpf( , nptr) returns and stores zero in the location pointed to by
.
nptr
- __nv_frexpf( , nptr) returns and stores an unspecified value in the
location to which points.
nptr
- __nv_frexpf(NaN, y) returns a NaN and stores an unspecified value in the location
to which points.
nptr
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frexpf(x: f32, b: *mut i32) -> f32;

    #[link_name = "__nv_frsqrt_rn"]
    #[doc = "Compute the reciprocal square root of in round-to-nearest-even modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_frsqrt_rn.html#__nv_frsqrt_rn)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn frsqrt_rn(x: f32) -> f32;

    #[link_name = "__nv_fsqrt_rd"]
    #[doc = "Compute the square root of in round-down (to negative infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsqrt_rd.html#__nv_fsqrt_rd)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fsqrt_rd(x: f32) -> f32;

    #[link_name = "__nv_fsqrt_rn"]
    #[doc = "Compute the square root of in round-to-nearest-even modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsqrt_rn.html#__nv_fsqrt_rn)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fsqrt_rn(x: f32) -> f32;

    #[link_name = "__nv_fsqrt_ru"]
    #[doc = "Compute the square root of in round-up (to positive infinity) modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsqrt_ru.html#__nv_fsqrt_ru)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fsqrt_ru(x: f32) -> f32;

    #[link_name = "__nv_fsqrt_rz"]
    #[doc = "Compute the square root of in round-towards-zero modex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsqrt_rz.html#__nv_fsqrt_rz)

# Returns

Returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn fsqrt_rz(x: f32) -> f32;

    #[link_name = "__nv_fsub_rd"]
    #[doc = "Compute the difference of and in round-down (to negative infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsub_rd.html#__nv_fsub_rd)

# Returns

Returns - x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fsub_rd(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fsub_rn"]
    #[doc = "Compute the difference of and in round-to-nearest-even rounding modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsub_rn.html#__nv_fsub_rn)

# Returns

Returns - x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fsub_rn(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fsub_ru"]
    #[doc = "Compute the difference of and in round-up (to positive infinity) modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsub_ru.html#__nv_fsub_ru)

# Returns

Returns - x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fsub_ru(x: f32, y: f32) -> f32;

    #[link_name = "__nv_fsub_rz"]
    #[doc = "Compute the difference of and in round-towards-zero modex. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_fsub_rz.html#__nv_fsub_rz)

# Returns

Returns - x. y
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6.
This operation will never be merged into a single multiply-add instruction."]
    pub fn fsub_rz(x: f32, y: f32) -> f32;

    #[link_name = "__nv_hadd"]
    #[doc = "Compute average of signed input arguments and as ( + ) >> 1, avoiding overflowx y x y
in the intermediate sum.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_hadd.html#__nv_hadd)

# Returns

Returns a signed integer value representing the signed average value of the two inputs."]
    pub fn hadd(x: i32, y: i32) -> i32;

    #[link_name = "__nv_half2float"]
    #[doc = "Convert the half-precision floating point value represented in x unsigned short
format to a single-precision floating point value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_half2float.html#__nv_half2float)

# Returns

Returns converted value."]
    pub fn half2float(h: i16) -> f32;

    #[link_name = "__nv_hiloint2double"]
    #[doc = "Reinterpret the integer value of as the high 32 bits of a double-precision floating
hi
point value and the integer value of as the low 32 bits of the same double-precision
lo
floating point value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_hiloint2double.html#__nv_hiloint2double)

# Returns

Returns reinterpreted value."]
    pub fn hiloint2double(x: i32, y: i32) -> f64;

    #[link_name = "__nv_hypot"]
    #[doc = "Calculate the length of the hypotenuse of a right triangle whose two sides have lengths x
and without undue overflow or underflow.y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_hypot.html#__nv_hypot)

# Returns

Returns the length of the hypotenuse . If the correct value would overflow,
returns . If the correct value would underflow, returns 0. If one of the input
arguments is 0, returns the other argument
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn hypot(x: f64, y: f64) -> f64;

    #[link_name = "__nv_hypotf"]
    #[doc = "Calculate the length of the hypotenuse of a right triangle whose two sides have lengths x
and without undue overflow or underflow.y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_hypotf.html#__nv_hypotf)

# Returns

Returns the length of the hypotenuse . If the correct value would overflow,
returns . If the correct value would underflow, returns 0. If one of the input
arguments is 0, returns the other argument
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn hypotf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_ilogb"]
    #[doc = "Calculates the unbiased integer exponent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ilogb.html#__nv_ilogb)

# Returns

- If successful, returns the unbiased exponent of the argument.
- __nv_ilogb(0) returns INT_MIN.
- __nv_ilogb(NaN) returns NaN.
- __nv_ilogb(x) returns INT_MAX if x is or the correct value is greater than
.
INT_MAX
- __nv_ilogb(x) return INT_MIN if the correct value is less than INT_MIN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn ilogb(x: f64) -> i32;

    #[link_name = "__nv_ilogbf"]
    #[doc = "Calculates the unbiased integer exponent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ilogbf.html#__nv_ilogbf)

# Returns

- If successful, returns the unbiased exponent of the argument.
- __nv_ilogbf(0) returns INT_MIN.
- __nv_ilogbf(NaN) returns NaN.
- __nv_ilogbf(x) returns INT_MAX if x is or the correct value is greater than
.
INT_MAX
- __nv_ilogbf(x) return INT_MIN if the correct value is less than INT_MIN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn ilogbf(x: f32) -> i32;

    #[link_name = "__nv_int2double_rn"]
    #[doc = "Convert the signed integer value to a double-precision floating point valuex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int2double_rn.html#__nv_int2double_rn)

# Returns

Returns converted value."]
    pub fn int2double_rn(i: i32) -> f64;

    #[link_name = "__nv_int2float_rd"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int2float_rd.html#__nv_int2float_rd)

# Returns

Returns converted value."]
    pub fn int2float_rd(in_: i32) -> f32;

    #[link_name = "__nv_int2float_rn"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-to-x
nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int2float_rn.html#__nv_int2float_rn)

# Returns

Returns converted value."]
    pub fn int2float_rn(in_: i32) -> f32;

    #[link_name = "__nv_int2float_ru"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-upx
(to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int2float_ru.html#__nv_int2float_ru)

# Returns

Returns converted value."]
    pub fn int2float_ru(in_: i32) -> f32;

    #[link_name = "__nv_int2float_rz"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int2float_rz.html#__nv_int2float_rz)

# Returns

Returns converted value."]
    pub fn int2float_rz(in_: i32) -> f32;

    #[link_name = "__nv_int_as_float"]
    #[doc = "Reinterpret the bits in the signed integer value as a single-precision floating pointx
value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_int_as_float.html#__nv_int_as_float)

# Returns

Returns reinterpreted value."]
    pub fn int_as_float(x: i32) -> f32;

    #[link_name = "__nv_isfinited"]
    #[doc = "Determine whether the floating-point value is a finite value (zero, subnormal, orx
normal and not infinity or NaN).

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_isfinited.html#__nv_isfinited)

# Returns

Returns a nonzero value if and only if is a finite valuex."]
    pub fn isfinited(x: f64) -> i32;

    #[link_name = "__nv_isinfd"]
    #[doc = "Determine whether the floating-point value is an infinite value (positive or negative)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_isinfd.html#__nv_isinfd)

# Returns

Returns a nonzero value if and only if is a infinite valuex."]
    pub fn isinfd(x: f64) -> i32;

    #[link_name = "__nv_isinff"]
    #[doc = "Determine whether the floating-point value is an infinite value (positive or negative)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_isinff.html#__nv_isinff)

# Returns

Returns a nonzero value if and only if is a infinite valuex."]
    pub fn isinff(x: f32) -> i32;

    #[link_name = "__nv_isnand"]
    #[doc = "Determine whether the floating-point value is a NaNx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_isnand.html#__nv_isnand)

# Returns

Returns a nonzero value if and only if is a NaN valuex."]
    pub fn isnand(x: f64) -> i32;

    #[link_name = "__nv_isnanf"]
    #[doc = "Determine whether the floating-point value is a NaNx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_isnanf.html#__nv_isnanf)

# Returns

Returns a nonzero value if and only if is a NaN valuex."]
    pub fn isnanf(x: f32) -> i32;

    #[link_name = "__nv_j0"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order 0 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_j0.html#__nv_j0)

# Returns

Returns the value of the Bessel function of the first kind of order 0.
- __nv_j0( ) returns +0.
- __nv_j0(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn j0(x: f64) -> f64;

    #[link_name = "__nv_j0f"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order 0 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_j0f.html#__nv_j0f)

# Returns

Returns the value of the Bessel function of the first kind of order 0.
- __nv_j0f( ) returns +0.
- __nv_j0f(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn j0f(x: f32) -> f32;

    #[link_name = "__nv_j1"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order 1 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_j1.html#__nv_j1)

# Returns

Returns the value of the Bessel function of the first kind of order 1.
- __nv_j1( ) returns .
- __nv_j1( ) returns +0.
- __nv_j1(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn j1(x: f64) -> f64;

    #[link_name = "__nv_j1f"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order 1 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_j1f.html#__nv_j1f)

# Returns

Returns the value of the Bessel function of the first kind of order 1.
- __nv_j1f( ) returns .
- __nv_j1f( ) returns +0.
- __nv_j1f(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn j1f(x: f32) -> f32;

    #[link_name = "__nv_jn"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order for the input
n
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_jn.html#__nv_jn)

# Returns

Returns the value of the Bessel function of the first kind of order .
n
- __nv_jn(n, NaN) returns NaN.
- __nv_jn(n, x) returns NaN for n < 0.
- __nv_jn(n, ) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn jn(n: i32, x: f64) -> f64;

    #[link_name = "__nv_jnf"]
    #[doc = "Calculate the value of the Bessel function of the first kind of order for the input
n
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_jnf.html#__nv_jnf)

# Returns

Returns the value of the Bessel function of the first kind of order .
n
- __nv_jnf(n, NaN) returns NaN.
- __nv_jnf(n, x) returns NaN for n < 0.
- __nv_jnf(n, ) returns +0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn jnf(n: i32, x: f32) -> f32;

    #[link_name = "__nv_ldexp"]
    #[doc = "Calculate the value of of the input arguments and x. exp

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ldexp.html#__nv_ldexp)

# Returns

- __nv_ldexp(x) returns if the correctly calculated value is outside the double
floating point range.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn ldexp(x: f64, y: i32) -> f64;

    #[link_name = "__nv_ldexpf"]
    #[doc = "Calculate the value of of the input arguments and x. exp

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ldexpf.html#__nv_ldexpf)

# Returns

- __nv_ldexpf(x) returns if the correctly calculated value is outside the double
floating point range.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn ldexpf(x: f32, y: i32) -> f32;

    #[link_name = "__nv_lgamma"]
    #[doc = "Calculate the natural logarithm of the absolute value of the gamma function of the input
argument , namely the value of x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_lgamma.html#__nv_lgamma)

# Returns

- __nv_lgamma(1) returns +0.
- __nv_lgamma(2) returns +0.
- __nv_lgamma(x) returns if the correctly calculated value is outside the double
floating point range.
- __nv_lgamma(x) returns if x 0.
- __nv_lgamma( ) returns .
- __nv_lgamma( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn lgamma(x: f64) -> f64;

    #[link_name = "__nv_lgammaf"]
    #[doc = "Calculate the natural logarithm of the absolute value of the gamma function of the input
argument , namely the value of x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_lgammaf.html#__nv_lgammaf)

# Returns

- __nv_lgammaf(1) returns +0.
- __nv_lgammaf(2) returns +0.
- __nv_lgammaf(x) returns if the correctly calculated value is outside the double
floating point range.
- __nv_lgammaf(x) returns if x 0.
- __nv_lgammaf( ) returns .
- __nv_lgammaf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn lgammaf(x: f32) -> f32;

    #[link_name = "__nv_ll2double_rd"]
    #[doc = "Convert the signed 64-bit integer value to a double-precision floating point value inx
round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2double_rd.html#__nv_ll2double_rd)

# Returns

Returns converted value."]
    pub fn ll2double_rd(l: i64) -> f64;

    #[link_name = "__nv_ll2double_rn"]
    #[doc = "Convert the signed 64-bit integer value to a double-precision floating point value inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2double_rn.html#__nv_ll2double_rn)

# Returns

Returns converted value."]
    pub fn ll2double_rn(l: i64) -> f64;

    #[link_name = "__nv_ll2double_ru"]
    #[doc = "Convert the signed 64-bit integer value to a double-precision floating point value inx
round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2double_ru.html#__nv_ll2double_ru)

# Returns

Returns converted value."]
    pub fn ll2double_ru(l: i64) -> f64;

    #[link_name = "__nv_ll2double_rz"]
    #[doc = "Convert the signed 64-bit integer value to a double-precision floating point value inx
round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2double_rz.html#__nv_ll2double_rz)

# Returns

Returns converted value."]
    pub fn ll2double_rz(l: i64) -> f64;

    #[link_name = "__nv_ll2float_rd"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2float_rd.html#__nv_ll2float_rd)

# Returns

Returns converted value."]
    pub fn ll2float_rd(l: i64) -> f32;

    #[link_name = "__nv_ll2float_rn"]
    #[doc = "Convert the signed 64-bit integer value to a single-precision floating point value inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2float_rn.html#__nv_ll2float_rn)

# Returns

Returns converted value."]
    pub fn ll2float_rn(l: i64) -> f32;

    #[link_name = "__nv_ll2float_ru"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-upx
(to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2float_ru.html#__nv_ll2float_ru)

# Returns

Returns converted value."]
    pub fn ll2float_ru(l: i64) -> f32;

    #[link_name = "__nv_ll2float_rz"]
    #[doc = "Convert the signed integer value to a single-precision floating point value in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ll2float_rz.html#__nv_ll2float_rz)

# Returns

Returns converted value."]
    pub fn ll2float_rz(l: i64) -> f32;

    #[link_name = "__nv_llabs"]
    #[doc = "Determine the absolute value of the 64-bit signed integer x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llabs.html#__nv_llabs)

# Returns

Returns the absolute value of the 64-bit signed integer x."]
    pub fn llabs(x: i64) -> i64;

    #[link_name = "__nv_llmax"]
    #[doc = "Determine the maximum value of the two 64-bit signed integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llmax.html#__nv_llmax)

# Returns

Returns the maximum value of the two 64-bit signed integers and x. y"]
    pub fn llmax(x: i64, y: i64) -> i64;

    #[link_name = "__nv_llmin"]
    #[doc = "Determine the minimum value of the two 64-bit signed integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llmin.html#__nv_llmin)

# Returns

Returns the minimum value of the two 64-bit signed integers and x. y"]
    pub fn llmin(x: i64, y: i64) -> i64;

    #[link_name = "__nv_llrint"]
    #[doc = "Round to the nearest integer value, with halfway cases rounded towards zero. If thex
result is outside the range of the return type, the result is undefined.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llrint.html#__nv_llrint)

# Returns

Returns rounded integer value."]
    pub fn llrint(x: f64) -> i64;

    #[link_name = "__nv_llrintf"]
    #[doc = "Round to the nearest integer value, with halfway cases rounded towards zero. If thex
result is outside the range of the return type, the result is undefined.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llrintf.html#__nv_llrintf)

# Returns

Returns rounded integer value."]
    pub fn llrintf(x: f32) -> i64;

    #[link_name = "__nv_llround"]
    #[doc = "Round to the nearest integer value, with halfway cases rounded away from zero. If thex
result is outside the range of the return type, the result is undefined.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llround.html#__nv_llround)

# Returns

Returns rounded integer value.
This function may be slower than alternate rounding methods. See llrint()."]
    pub fn llround(x: f64) -> i64;

    #[link_name = "__nv_llroundf"]
    #[doc = "Round to the nearest integer value, with halfway cases rounded away from zero. If thex
result is outside the range of the return type, the result is undefined.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_llroundf.html#__nv_llroundf)

# Returns

Returns rounded integer value.
This function may be slower than alternate rounding methods. See llrint()."]
    pub fn llroundf(x: f32) -> i64;

    #[link_name = "__nv_log"]
    #[doc = "Calculate the base logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log.html#__nv_log)

# Returns

- __nv_log( ) returns .
- __nv_log(1) returns +0.
- __nv_log(x) returns NaN for x < 0.
- __nv_log( ) returns 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn log(x: f64) -> f64;

    #[link_name = "__nv_log10"]
    #[doc = "Calculate the base 10 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log10.html#__nv_log10)

# Returns

- __nv_log10( ) returns .
- __nv_log10(1) returns +0.
- __nv_log10(x) returns NaN for x < 0.
- __nv_log10( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn log10(x: f64) -> f64;

    #[link_name = "__nv_log10f"]
    #[doc = "Calculate the base 10 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log10f.html#__nv_log10f)

# Returns

- __nv_log10f( ) returns .
- __nv_log10f(1) returns +0.
- __nv_log10f(x) returns NaN for x < 0.
- __nv_log10f( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn log10f(x: f32) -> f32;

    #[link_name = "__nv_log1p"]
    #[doc = "Calculate the value of of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log1p.html#__nv_log1p)

# Returns

- __nv_log1p( ) returns .
- __nv_log1p(-1) returns +0.
- __nv_log1p(x) returns NaN for x < -1.
- __nv_log1p( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn log1p(x: f64) -> f64;

    #[link_name = "__nv_log1pf"]
    #[doc = "Calculate the value of of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log1pf.html#__nv_log1pf)

# Returns

- __nv_log1pf( ) returns .
- __nv_log1pf(-1) returns +0.
- __nv_log1pf(x) returns NaN for x < -1.
- __nv_log1pf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn log1pf(x: f32) -> f32;

    #[link_name = "__nv_log2"]
    #[doc = "Calculate the base 2 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log2.html#__nv_log2)

# Returns

- __nv_log2( ) returns .
- __nv_log2(1) returns +0.
- __nv_log2(x) returns NaN for x < 0.
- __nv_log2( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn log2(x: f64) -> f64;

    #[link_name = "__nv_log2f"]
    #[doc = "Calculate the base 2 logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_log2f.html#__nv_log2f)

# Returns

- __nv_log2f( ) returns .
- __nv_log2f(1) returns +0.
- __nv_log2f(x) returns NaN for x < 0.
- __nv_log2f( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn log2f(x: f32) -> f32;

    #[link_name = "__nv_logb"]
    #[doc = "Calculate the floating point representation of the exponent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_logb.html#__nv_logb)

# Returns

- __nv_logb returns 
- __nv_logb returns 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn logb(x: f64) -> f64;

    #[link_name = "__nv_logbf"]
    #[doc = "Calculate the floating point representation of the exponent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_logbf.html#__nv_logbf)

# Returns

- __nv_logbf returns 
- __nv_logbf returns 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn logbf(x: f32) -> f32;

    #[link_name = "__nv_logf"]
    #[doc = "Calculate the base logarithm of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_logf.html#__nv_logf)

# Returns

- __nv_logf( ) returns .
- __nv_logf(1) returns +0.
- __nv_logf(x) returns NaN for x < 0.
- __nv_logf( ) returns 
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn logf(x: f32) -> f32;

    #[link_name = "__nv_longlong_as_double"]
    #[doc = "Reinterpret the bits in the 64-bit signed integer value as a double-precision floatingx
point value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_longlong_as_double.html#__nv_longlong_as_double)

# Returns

Returns reinterpreted value."]
    pub fn longlong_as_double(x: i64) -> f64;

    #[link_name = "__nv_max"]
    #[doc = "Determine the maximum value of the two 32-bit signed integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_max.html#__nv_max)

# Returns

Returns the maximum value of the two 32-bit signed integers and x. y"]
    pub fn max(x: i32, y: i32) -> i32;

    #[link_name = "__nv_min"]
    #[doc = "Determine the minimum value of the two 32-bit signed integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_min.html#__nv_min)

# Returns

Returns the minimum value of the two 32-bit signed integers and x. y"]
    pub fn min(x: i32, y: i32) -> i32;

    #[link_name = "__nv_modf"]
    #[doc = "Break down the argument into fractional and integral parts. The integral part is storedx
in the argument . Fractional and integral parts are given the same sign as the
iptr
argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_modf.html#__nv_modf)

# Returns

- __nv_modf( , iptr) returns a result with the same sign as x.
- __nv_modf( , iptr) returns and stores in the object pointed to by
.
iptr
- __nv_modf(NaN, iptr) stores a NaN in the object pointed to by iptr and returns a
NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn modf(x: f64, b: *mut f64) -> f64;

    #[link_name = "__nv_modff"]
    #[doc = "Break down the argument into fractional and integral parts. The integral part is storedx
in the argument . Fractional and integral parts are given the same sign as the
iptr
argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_modff.html#__nv_modff)

# Returns

- __nv_modff( , iptr) returns a result with the same sign as x.
- __nv_modff( , iptr) returns and stores in the object pointed to by
.
iptr
- __nv_modff(NaN, iptr) stores a NaN in the object pointed to by iptr and returns
a NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn modff(x: f32, b: *mut f32) -> f32;

    #[link_name = "__nv_mul24"]
    #[doc = "Calculate the least significant 32 bits of the product of the least significant 24 bits of x
and . The high order 8 bits of and are ignored.y x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_mul24.html#__nv_mul24)

# Returns

Returns the least significant 32 bits of the product * x. y"]
    pub fn mul24(x: i32, y: i32) -> i32;

    #[link_name = "__nv_mul64hi"]
    #[doc = "Calculate the most significant 64 bits of the 128-bit product * , where and are 64-x y x y
bit integers.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_mul64hi.html#__nv_mul64hi)

# Returns

Returns the most significant 64 bits of the product * x. y"]
    pub fn mul64hi(x: i64, y: i64) -> i64;

    #[link_name = "__nv_mulhi"]
    #[doc = "Calculate the most significant 32 bits of the 64-bit product * , where and are 32-bitx y x y
integers.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_mulhi.html#__nv_mulhi)

# Returns

Returns the most significant 32 bits of the product * x. y"]
    pub fn mulhi(x: i32, y: i32) -> i32;

    #[link_name = "__nv_nan"]
    #[doc = "Return a representation of a quiet NaN. Argument selects one of the possible
tagp
representations.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nan.html#__nv_nan)

# Returns

- __nv_nan(tagp) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn nan(tagp: *mut i8) -> f64;

    #[link_name = "__nv_nanf"]
    #[doc = "Return a representation of a quiet NaN. Argument selects one of the possible
tagp
representations.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nanf.html#__nv_nanf)

# Returns

- __nv_nanf(tagp) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn nanf(tagp: *mut i8) -> f32;

    #[link_name = "__nv_nearbyint"]
    #[doc = "Round argument to an integer value in double precision floating-point formatx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nearbyint.html#__nv_nearbyint)

# Returns

- __nv_nearbyint( ) returns .
- __nv_nearbyint( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn nearbyint(x: f64) -> f64;

    #[link_name = "__nv_nearbyintf"]
    #[doc = "Round argument to an integer value in double precision floating-point formatx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nearbyintf.html#__nv_nearbyintf)

# Returns

- __nv_nearbyintf( ) returns .
- __nv_nearbyintf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn nearbyintf(x: f32) -> f32;

    #[link_name = "__nv_nextafter"]
    #[doc = "Calculate the next representable double-precision floating-point value following inx
the direction of . For example, if is greater than , nextafter() returns the smallesty y x
representable number greater than x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nextafter.html#__nv_nextafter)

# Returns

- __nv_nextafter( , y) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn nextafter(x: f64, y: f64) -> f64;

    #[link_name = "__nv_nextafterf"]
    #[doc = "Calculate the next representable double-precision floating-point value following inx
the direction of . For example, if is greater than , nextafter() returns the smallesty y x
representable number greater than x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_nextafterf.html#__nv_nextafterf)

# Returns

- __nv_nextafterf( , y) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn nextafterf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_normcdf"]
    #[doc = "Calculate the cumulative distribution function of the standard normal distribution for
input argument , .y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_normcdf.html#__nv_normcdf)

# Returns

- __nv_normcdf( ) returns 1
- __nv_normcdf( ) returns +0
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn normcdf(x: f64) -> f64;

    #[link_name = "__nv_normcdff"]
    #[doc = "Calculate the cumulative distribution function of the standard normal distribution for
input argument , .y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_normcdff.html#__nv_normcdff)

# Returns

- __nv_normcdff( ) returns 1
- __nv_normcdff( ) returns +0
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn normcdff(x: f32) -> f32;

    #[link_name = "__nv_normcdfinv"]
    #[doc = "Calculate the inverse of the standard normal cumulative distribution function for input
argument , . The function is defined for input values in the interval .y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_normcdfinv.html#__nv_normcdfinv)

# Returns

- __nv_normcdfinv(0) returns .
- __nv_normcdfinv(1) returns .
- __nv_normcdfinv(x) returns NaN if x is not in the interval [0,1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn normcdfinv(x: f64) -> f64;

    #[link_name = "__nv_normcdfinvf"]
    #[doc = "Calculate the inverse of the standard normal cumulative distribution function for input
argument , . The function is defined for input values in the interval .y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_normcdfinvf.html#__nv_normcdfinvf)

# Returns

- __nv_normcdfinvf(0) returns .
- __nv_normcdfinvf(1) returns .
- __nv_normcdfinvf(x) returns NaN if x is not in the interval [0,1].
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn normcdfinvf(x: f32) -> f32;

    #[link_name = "__nv_popc"]
    #[doc = "Count the number of bits that are set to 1 in x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_popc.html#__nv_popc)

# Returns

Returns a value between 0 and 32 inclusive representing the number of set bits."]
    pub fn popc(x: i32) -> i32;

    #[link_name = "__nv_popcll"]
    #[doc = "Count the number of bits that are set to 1 in x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_popcll.html#__nv_popcll)

# Returns

Returns a value between 0 and 64 inclusive representing the number of set bits."]
    pub fn popcll(x: i64) -> i32;

    #[link_name = "__nv_pow"]
    #[doc = "Calculate the value of to the power of x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_pow.html#__nv_pow)

# Returns

- __nv_pow( , y) returns for y an integer less than 0.
- __nv_pow( , y) returns for y an odd integer greater than 0.
- __nv_pow( , y) returns +0 for y > 0 and not and odd integer.
- __nv_pow(-1, ) returns 1.
- __nv_pow(+1, y) returns 1 for any y, even a NaN.
- __nv_pow(x, ) returns 1 for any x, even a NaN.
- __nv_pow(x, y) returns a NaN for finite x < 0 and finite non-integer y.
- __nv_pow( , ) returns for x.
- __nv_pow( , ) returns +0 for x.
- __nv_pow( , ) returns +0 for x.
- __nv_pow( , ) returns for x.
- __nv_pow( , y) returns -0 for y an odd integer less than 0.
- __nv_pow( , y) returns +0 for y < 0 and not an odd integer.
- __nv_pow( , y) returns for y an odd integer greater than 0.
- __nv_pow( , y) returns for y > 0 and not an odd integer.
- __nv_pow( , y) returns +0 for y < 0.
- __nv_pow( , y) returns for y > 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn pow(x: f64, y: f64) -> f64;

    #[link_name = "__nv_powf"]
    #[doc = "Calculate the value of to the power of x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_powf.html#__nv_powf)

# Returns

- __nv_powf( , y) returns for y an integer less than 0.
- __nv_powf( , y) returns for y an odd integer greater than 0.
- __nv_powf( , y) returns +0 for y > 0 and not and odd integer.
- __nv_powf(-1, ) returns 1.
- __nv_powf(+1, y) returns 1 for any y, even a NaN.
- __nv_powf(x, ) returns 1 for any x, even a NaN.
- __nv_powf(x, y) returns a NaN for finite x < 0 and finite non-integer y.
- __nv_powf( , ) returns for x.
- __nv_powf( , ) returns +0 for x.
- __nv_powf( , ) returns +0 for x.
- __nv_powf( , ) returns for x.
- __nv_powf( , y) returns -0 for y an odd integer less than 0.
- __nv_powf( , y) returns +0 for y < 0 and not an odd integer.
- __nv_powf( , y) returns for y an odd integer greater than 0.
- __nv_powf( , y) returns for y > 0 and not an odd integer.
- __nv_powf( , y) returns +0 for y < 0.
- __nv_powf( , y) returns for y > 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn powf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_powi"]
    #[doc = "Calculate the value of to the power of x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_powi.html#__nv_powi)

# Returns

- __nv_powi( , y) returns for y an integer less than 0.
- __nv_powi( , y) returns for y an odd integer greater than 0.
- __nv_powi( , y) returns +0 for y > 0 and not and odd integer.
- __nv_powi(-1, ) returns 1.
- __nv_powi(+1, y) returns 1 for any y, even a NaN.
- __nv_powi(x, ) returns 1 for any x, even a NaN.
- __nv_powi(x, y) returns a NaN for finite x < 0 and finite non-integer y.
- __nv_powi( , ) returns for x.
- __nv_powi( , ) returns +0 for x.
- __nv_powi( , ) returns +0 for x.
- __nv_powi( , ) returns for x.
- __nv_powi( , y) returns -0 for y an odd integer less than 0.
- __nv_powi( , y) returns +0 for y < 0 and not an odd integer.
- __nv_powi( , y) returns for y an odd integer greater than 0.
- __nv_powi( , y) returns for y > 0 and not an odd integer.
- __nv_powi( , y) returns +0 for y < 0.
- __nv_powi( , y) returns for y > 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn powi(x: f64, y: i32) -> f64;

    #[link_name = "__nv_powif"]
    #[doc = "Calculate the value of to the power of x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_powif.html#__nv_powif)

# Returns

- __nv_powif( , y) returns for y an integer less than 0.
- __nv_powif( , y) returns for y an odd integer greater than 0.
- __nv_powif( , y) returns +0 for y > 0 and not and odd integer.
- __nv_powif(-1, ) returns 1.
- __nv_powif(+1, y) returns 1 for any y, even a NaN.
- __nv_powif(x, ) returns 1 for any x, even a NaN.
- __nv_powif(x, y) returns a NaN for finite x < 0 and finite non-integer y.
- __nv_powif( , ) returns for x.
- __nv_powif( , ) returns +0 for x.
- __nv_powif( , ) returns +0 for x.
- __nv_powif( , ) returns for x.
- __nv_powif( , y) returns -0 for y an odd integer less than 0.
- __nv_powif( , y) returns +0 for y < 0 and not an odd integer.
- __nv_powif( , y) returns for y an odd integer greater than 0.
- __nv_powif( , y) returns for y > 0 and not an odd integer.
- __nv_powif( , y) returns +0 for y < 0.
- __nv_powif( , y) returns for y > 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn powif(x: f32, y: i32) -> f32;

    #[link_name = "__nv_rcbrt"]
    #[doc = "Calculate reciprocal cube root function of x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rcbrt.html#__nv_rcbrt)

# Returns

- __nv_rcbrt( ) returns .
- __nv_rcbrt( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn rcbrt(x: f64) -> f64;

    #[link_name = "__nv_rcbrtf"]
    #[doc = "Calculate reciprocal cube root function of x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rcbrtf.html#__nv_rcbrtf)

# Returns

- __nv_rcbrtf( ) returns .
- __nv_rcbrtf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn rcbrtf(x: f32) -> f32;

    #[link_name = "__nv_remainder"]
    #[doc = "Compute double-precision floating-point remainder of dividing by for nonzero .
r x y y
Thus . The value is the integer value nearest . In the case when ,
n
the even value is chosen.
n

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_remainder.html#__nv_remainder)

# Returns

- __nv_remainder(x, 0) returns NaN.
- __nv_remainder( , y) returns NaN.
- __nv_remainder(x, ) returns x for finite x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn remainder(x: f64, y: f64) -> f64;

    #[link_name = "__nv_remainderf"]
    #[doc = "Compute double-precision floating-point remainder of dividing by for nonzero .
r x y y
Thus . The value is the integer value nearest . In the case when ,
n
the even value is chosen.
n

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_remainderf.html#__nv_remainderf)

# Returns

- __nv_remainderf(x, 0) returns NaN.
- __nv_remainderf( , y) returns NaN.
- __nv_remainderf(x, ) returns x for finite x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn remainderf(x: f32, y: f32) -> f32;

    #[link_name = "__nv_remquo"]
    #[doc = "Compute a double-precision floating-point remainder in the same way as the
remainder() function. Argument returns part of quotient upon division of by .
quo x y
Value has the same sign as and may not be the exact quotient but agrees with the
quo
exact quotient in the low order 3 bits.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_remquo.html#__nv_remquo)

# Returns

Returns the remainder.
- __nv_remquo(x, 0, quo) returns NaN.
- __nv_remquo( , y, quo) returns NaN.
- __nv_remquo(x, , quo) returns x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn remquo(x: f64, y: f64, c: *mut i32) -> f64;

    #[link_name = "__nv_remquof"]
    #[doc = "Compute a double-precision floating-point remainder in the same way as the
remainder() function. Argument returns part of quotient upon division of by .
quo x y
Value has the same sign as and may not be the exact quotient but agrees with the
quo
exact quotient in the low order 3 bits.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_remquof.html#__nv_remquof)

# Returns

Returns the remainder.
- __nv_remquof(x, 0, quo) returns NaN.
- __nv_remquof( , y, quo) returns NaN.
- __nv_remquof(x, , quo) returns x.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn remquof(x: f32, y: f32, quo: *mut i32) -> f32;

    #[link_name = "__nv_rhadd"]
    #[doc = "Compute average of signed input arguments and as ( + + 1 ) >> 1, avoidingx y x y
overflow in the intermediate sum.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rhadd.html#__nv_rhadd)

# Returns

Returns a signed integer value representing the signed rounded average value of the two
inputs."]
    pub fn rhadd(x: i32, y: i32) -> i32;

    #[link_name = "__nv_rint"]
    #[doc = "Round to the nearest integer value in floating-point format, with halfway casesx
rounded to the nearest even integer value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rint.html#__nv_rint)

# Returns

Returns rounded integer value."]
    pub fn rint(x: f64) -> f64;

    #[link_name = "__nv_rintf"]
    #[doc = "Round to the nearest integer value in floating-point format, with halfway casesx
rounded to the nearest even integer value.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rintf.html#__nv_rintf)

# Returns

Returns rounded integer value."]
    pub fn rintf(x: f32) -> f32;

    #[link_name = "__nv_round"]
    #[doc = "Round to the nearest integer value in floating-point format, with halfway casesx
rounded away from zero.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_round.html#__nv_round)

# Returns

Returns rounded integer value.
This function may be slower than alternate rounding methods. See rint()."]
    pub fn round(x: f64) -> f64;

    #[link_name = "__nv_roundf"]
    #[doc = "Round to the nearest integer value in floating-point format, with halfway casesx
rounded away from zero.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_roundf.html#__nv_roundf)

# Returns

Returns rounded integer value.
This function may be slower than alternate rounding methods. See rint()."]
    pub fn roundf(x: f32) -> f32;

    #[link_name = "__nv_rsqrt"]
    #[doc = "Calculate the reciprocal of the nonnegative square root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rsqrt.html#__nv_rsqrt)

# Returns

Returns .
- __nv_rsqrt( ) returns +0.
- __nv_rsqrt( ) returns .
- __nv_rsqrt(x) returns NaN if x is less than 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn rsqrt(x: f64) -> f64;

    #[link_name = "__nv_rsqrtf"]
    #[doc = "Calculate the reciprocal of the nonnegative square root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_rsqrtf.html#__nv_rsqrtf)

# Returns

Returns .
- __nv_rsqrtf( ) returns +0.
- __nv_rsqrtf( ) returns .
- __nv_rsqrtf(x) returns NaN if x is less than 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn rsqrtf(x: f32) -> f32;

    #[link_name = "__nv_sad"]
    #[doc = "Calculate , the 32-bit sum of the third argument plus and the absolute value
z
of the difference between the first argument, , and second argument, x. y
Inputs and are signed 32-bit integers, input is a 32-bit unsigned integerx. y z

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sad.html#__nv_sad)

# Returns

Returns ."]
    pub fn sad(x: i32, y: i32, z: i32) -> i32;

    #[link_name = "__nv_saturatef"]
    #[doc = "Clamp the input argument to be within the interval [+0.0, 1.0]x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_saturatef.html#__nv_saturatef)

# Returns

- __nv_saturatef(x) returns 0 if x < 0.
- __nv_saturatef(x) returns 1 if x > 1.
- __nv_saturatef(x) returns x if .
- __nv_saturatef(NaN) returns 0."]
    pub fn saturatef(x: f32) -> f32;

    #[link_name = "__nv_scalbn"]
    #[doc = "Scale by by efficient manipulation of the floating-point exponentx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_scalbn.html#__nv_scalbn)

# Returns

Returns * x.
- __nv_scalbn( , n) returns .
- __nv_scalbn(x, 0) returns x.
- __nv_scalbn( , n) returns ."]
    pub fn scalbn(x: f64, y: i32) -> f64;

    #[link_name = "__nv_scalbnf"]
    #[doc = "Scale by by efficient manipulation of the floating-point exponentx.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_scalbnf.html#__nv_scalbnf)

# Returns

Returns * x.
- __nv_scalbnf( , n) returns .
- __nv_scalbnf(x, 0) returns x.
- __nv_scalbnf( , n) returns ."]
    pub fn scalbnf(x: f32, y: i32) -> f32;

    #[link_name = "__nv_signbitd"]
    #[doc = "Determine whether the floating-point value is negativex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_signbitd.html#__nv_signbitd)

# Returns

Returns a nonzero value if and only if is negative. Reports the sign bit of all valuesx
including infinities, zeros, and NaNs."]
    pub fn signbitd(x: f64) -> i32;

    #[link_name = "__nv_signbitf"]
    #[doc = "Determine whether the floating-point value is negativex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_signbitf.html#__nv_signbitf)

# Returns

Returns a nonzero value if and only if is negative. Reports the sign bit of all valuesx
including infinities, zeros, and NaNs."]
    pub fn signbitf(x: f32) -> i32;

    #[link_name = "__nv_sin"]
    #[doc = "Calculate the sine of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sin.html#__nv_sin)

# Returns

- __nv_sin( ) returns .
- __nv_sin( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sin(x: f64) -> f64;

    #[link_name = "__nv_sincos"]
    #[doc = "Calculate the sine and cosine of the first input argument (measured in radians). Thex
results for sine and cosine are written into the second argument, , and, respectively,
sptr
third argument, .
zptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sincos.html#__nv_sincos)

# Returns

- none
See __nv_sin() and __nv_cos().
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sincos(x: f64, sptr: *mut f64, cptr: *mut f64) -> ();

    #[link_name = "__nv_sincosf"]
    #[doc = "Calculate the sine and cosine of the first input argument (measured in radians). Thex
results for sine and cosine are written into the second argument, , and, respectively,
sptr
third argument, .
zptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sincosf.html#__nv_sincosf)

# Returns

- none
See __nv_sinf() and __nv_cosf().
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn sincosf(x: f32, sptr: *mut f32, cptr: *mut f32) -> ();

    #[link_name = "__nv_sincospi"]
    #[doc = "Calculate the sine and cosine of the first input argument, (measured in radians),x
. The results for sine and cosine are written into the second argument, , and,
sptr
respectively, third argument, .
zptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sincospi.html#__nv_sincospi)

# Returns

- none
See __nv_sinpi() and __nv_cospi().
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sincospi(x: f64, sptr: *mut f64, cptr: *mut f64) -> ();

    #[link_name = "__nv_sincospif"]
    #[doc = "Calculate the sine and cosine of the first input argument, (measured in radians),x
. The results for sine and cosine are written into the second argument, , and,
sptr
respectively, third argument, .
zptr

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sincospif.html#__nv_sincospif)

# Returns

- none
See __nv_sinpif() and __nv_cospif().
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn sincospif(x: f32, sptr: *mut f32, cptr: *mut f32) -> ();

    #[link_name = "__nv_sinf"]
    #[doc = "Calculate the sine of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sinf.html#__nv_sinf)

# Returns

- __nv_sinf( ) returns .
- __nv_sinf( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn sinf(x: f32) -> f32;

    #[link_name = "__nv_sinh"]
    #[doc = "Calculate the hyperbolic sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sinh.html#__nv_sinh)

# Returns

- __nv_sinh( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sinh(x: f64) -> f64;

    #[link_name = "__nv_sinhf"]
    #[doc = "Calculate the hyperbolic sine of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sinhf.html#__nv_sinhf)

# Returns

- __nv_sinhf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn sinhf(x: f32) -> f32;

    #[link_name = "__nv_sinpi"]
    #[doc = "Calculate the sine of (measured in radians), where is the input argumentx. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sinpi.html#__nv_sinpi)

# Returns

- __nv_sinpi( ) returns .
- __nv_sinpi( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sinpi(x: f64) -> f64;

    #[link_name = "__nv_sinpif"]
    #[doc = "Calculate the sine of (measured in radians), where is the input argumentx. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sinpif.html#__nv_sinpif)

# Returns

- __nv_sinpif( ) returns .
- __nv_sinpif( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn sinpif(x: f32) -> f32;

    #[link_name = "__nv_sqrt"]
    #[doc = "Calculate the nonnegative square root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sqrt.html#__nv_sqrt)

# Returns

Returns .
- __nv_sqrt( ) returns .
- __nv_sqrt( ) returns .
- __nv_sqrt(x) returns NaN if x is less than 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sqrt(x: f64) -> f64;

    #[link_name = "__nv_sqrtf"]
    #[doc = "Calculate the nonnegative square root of , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_sqrtf.html#__nv_sqrtf)

# Returns

Returns .
- __nv_sqrtf( ) returns .
- __nv_sqrtf( ) returns .
- __nv_sqrtf(x) returns NaN if x is less than 0.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn sqrtf(x: f32) -> f32;

    #[link_name = "__nv_tan"]
    #[doc = "Calculate the tangent of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tan.html#__nv_tan)

# Returns

- __nv_tan( ) returns .
- __nv_tan( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn tan(x: f64) -> f64;

    #[link_name = "__nv_tanf"]
    #[doc = "Calculate the tangent of the input argument (measured in radians)x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tanf.html#__nv_tanf)

# Returns

- __nv_tanf( ) returns .
- __nv_tanf( ) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn tanf(x: f32) -> f32;

    #[link_name = "__nv_tanh"]
    #[doc = "Calculate the hyperbolic tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tanh.html#__nv_tanh)

# Returns

- __nv_tanh( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn tanh(x: f64) -> f64;

    #[link_name = "__nv_tanhf"]
    #[doc = "Calculate the hyperbolic tangent of the input argument x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tanhf.html#__nv_tanhf)

# Returns

- __nv_tanhf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn tanhf(x: f32) -> f32;

    #[link_name = "__nv_tgamma"]
    #[doc = "Calculate the gamma function of the input argument , namely the value of x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tgamma.html#__nv_tgamma)

# Returns

- __nv_tgamma( ) returns .
- __nv_tgamma(2) returns +0.
- __nv_tgamma(x) returns if the correctly calculated value is outside the double
floating point range.
- __nv_tgamma(x) returns NaN if x < 0.
- __nv_tgamma( ) returns NaN.
- __nv_tgamma( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn tgamma(x: f64) -> f64;

    #[link_name = "__nv_tgammaf"]
    #[doc = "Calculate the gamma function of the input argument , namely the value of x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_tgammaf.html#__nv_tgammaf)

# Returns

- __nv_tgammaf( ) returns .
- __nv_tgammaf(2) returns +0.
- __nv_tgammaf(x) returns if the correctly calculated value is outside the double
floating point range.
- __nv_tgammaf(x) returns NaN if x < 0.
- __nv_tgammaf( ) returns NaN.
- __nv_tgammaf( ) returns .
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn tgammaf(x: f32) -> f32;

    #[link_name = "__nv_trunc"]
    #[doc = "Round to the nearest integer value that does not exceed in magnitudex. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_trunc.html#__nv_trunc)

# Returns

Returns truncated integer value."]
    pub fn trunc(x: f64) -> f64;

    #[link_name = "__nv_truncf"]
    #[doc = "Round to the nearest integer value that does not exceed in magnitudex. x

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_truncf.html#__nv_truncf)

# Returns

Returns truncated integer value."]
    pub fn truncf(x: f32) -> f32;

    #[link_name = "__nv_uhadd"]
    #[doc = "Compute average of unsigned input arguments and as ( + ) >> 1, avoidingx y x y
overflow in the intermediate sum.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uhadd.html#__nv_uhadd)

# Returns

Returns an unsigned integer value representing the unsigned average value of the two
inputs."]
    pub fn uhadd(x: i32, y: i32) -> i32;

    #[link_name = "__nv_uint2double_rn"]
    #[doc = "Convert the unsigned integer value to a double-precision floating point valuex.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uint2double_rn.html#__nv_uint2double_rn)

# Returns

Returns converted value."]
    pub fn uint2double_rn(i: i32) -> f64;

    #[link_name = "__nv_uint2float_rd"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uint2float_rd.html#__nv_uint2float_rd)

# Returns

Returns converted value."]
    pub fn uint2float_rd(in_: i32) -> f32;

    #[link_name = "__nv_uint2float_rn"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uint2float_rn.html#__nv_uint2float_rn)

# Returns

Returns converted value."]
    pub fn uint2float_rn(in_: i32) -> f32;

    #[link_name = "__nv_uint2float_ru"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uint2float_ru.html#__nv_uint2float_ru)

# Returns

Returns converted value."]
    pub fn uint2float_ru(in_: i32) -> f32;

    #[link_name = "__nv_uint2float_rz"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_uint2float_rz.html#__nv_uint2float_rz)

# Returns

Returns converted value."]
    pub fn uint2float_rz(in_: i32) -> f32;

    #[link_name = "__nv_ull2double_rd"]
    #[doc = "Convert the unsigned 64-bit integer value to a double-precision floating point value inx
round-down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2double_rd.html#__nv_ull2double_rd)

# Returns

Returns converted value."]
    pub fn ull2double_rd(l: i64) -> f64;

    #[link_name = "__nv_ull2double_rn"]
    #[doc = "Convert the unsigned 64-bit integer value to a double-precision floating point value inx
round-to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2double_rn.html#__nv_ull2double_rn)

# Returns

Returns converted value."]
    pub fn ull2double_rn(l: i64) -> f64;

    #[link_name = "__nv_ull2double_ru"]
    #[doc = "Convert the unsigned 64-bit integer value to a double-precision floating point value inx
round-up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2double_ru.html#__nv_ull2double_ru)

# Returns

Returns converted value."]
    pub fn ull2double_ru(l: i64) -> f64;

    #[link_name = "__nv_ull2double_rz"]
    #[doc = "Convert the unsigned 64-bit integer value to a double-precision floating point value inx
round-towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2double_rz.html#__nv_ull2double_rz)

# Returns

Returns converted value."]
    pub fn ull2double_rz(l: i64) -> f64;

    #[link_name = "__nv_ull2float_rd"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
down (to negative infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2float_rd.html#__nv_ull2float_rd)

# Returns

Returns converted value."]
    pub fn ull2float_rd(l: i64) -> f32;

    #[link_name = "__nv_ull2float_rn"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
to-nearest-even mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2float_rn.html#__nv_ull2float_rn)

# Returns

Returns converted value."]
    pub fn ull2float_rn(l: i64) -> f32;

    #[link_name = "__nv_ull2float_ru"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
up (to positive infinity) mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2float_ru.html#__nv_ull2float_ru)

# Returns

Returns converted value."]
    pub fn ull2float_ru(l: i64) -> f32;

    #[link_name = "__nv_ull2float_rz"]
    #[doc = "Convert the unsigned integer value to a single-precision floating point value in round-x
towards-zero mode.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ull2float_rz.html#__nv_ull2float_rz)

# Returns

Returns converted value."]
    pub fn ull2float_rz(l: i64) -> f32;

    #[link_name = "__nv_ullmax"]
    #[doc = "Determine the maximum value of the two 64-bit unsigned integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ullmax.html#__nv_ullmax)

# Returns

Returns the maximum value of the two 64-bit unsigned integers and x. y"]
    pub fn ullmax(x: i64, y: i64) -> i64;

    #[link_name = "__nv_ullmin"]
    #[doc = "Determine the minimum value of the two 64-bit unsigned integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ullmin.html#__nv_ullmin)

# Returns

Returns the minimum value of the two 64-bit unsigned integers and x. y"]
    pub fn ullmin(x: i64, y: i64) -> i64;

    #[link_name = "__nv_umax"]
    #[doc = "Determine the maximum value of the two 32-bit unsigned integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_umax.html#__nv_umax)

# Returns

Returns the maximum value of the two 32-bit unsigned integers and x. y"]
    pub fn umax(x: i32, y: i32) -> i32;

    #[link_name = "__nv_umin"]
    #[doc = "Determine the minimum value of the two 32-bit unsigned integers and x. y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_umin.html#__nv_umin)

# Returns

Returns the minimum value of the two 32-bit unsigned integers and x. y"]
    pub fn umin(x: i32, y: i32) -> i32;

    #[link_name = "__nv_umul24"]
    #[doc = "Calculate the least significant 32 bits of the product of the least significant 24 bits of x
and . The high order 8 bits of and are ignored.y x y

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_umul24.html#__nv_umul24)

# Returns

Returns the least significant 32 bits of the product * x. y"]
    pub fn umul24(x: i32, y: i32) -> i32;

    #[link_name = "__nv_umul64hi"]
    #[doc = "Calculate the most significant 64 bits of the 128-bit product * , where and are 64-x y x y
bit unsigned integers.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_umul64hi.html#__nv_umul64hi)

# Returns

Returns the most significant 64 bits of the product * x. y"]
    pub fn umul64hi(x: i64, y: i64) -> i64;

    #[link_name = "__nv_umulhi"]
    #[doc = "Calculate the most significant 32 bits of the 64-bit product * , where and are 32-bitx y x y
unsigned integers.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_umulhi.html#__nv_umulhi)

# Returns

Returns the most significant 32 bits of the product * x. y"]
    pub fn umulhi(x: i32, y: i32) -> i32;

    #[link_name = "__nv_urhadd"]
    #[doc = "Compute average of unsigned input arguments and as ( + + 1 ) >> 1, avoidingx y x y
overflow in the intermediate sum.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_urhadd.html#__nv_urhadd)

# Returns

Returns an unsigned integer value representing the unsigned rounded average value of
the two inputs."]
    pub fn urhadd(x: i32, y: i32) -> i32;

    #[link_name = "__nv_usad"]
    #[doc = "Calculate , the 32-bit sum of the third argument plus and the absolute value
z
of the difference between the first argument, , and second argument, x. y
Inputs , , and are unsigned 32-bit integersx. y z

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_usad.html#__nv_usad)

# Returns

Returns ."]
    pub fn usad(x: i32, y: i32, z: i32) -> i32;

    #[link_name = "__nv_y0"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order 0 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_y0.html#__nv_y0)

# Returns

Returns the value of the Bessel function of the second kind of order 0.
- __nv_y0(0) returns .
- __nv_y0(x) returns NaN for x < 0.
- __nv_y0( ) returns +0.
- __nv_y0(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn y0(x: f64) -> f64;

    #[link_name = "__nv_y0f"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order 0 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_y0f.html#__nv_y0f)

# Returns

Returns the value of the Bessel function of the second kind of order 0.
- __nv_y0f(0) returns .
- __nv_y0f(x) returns NaN for x < 0.
- __nv_y0f( ) returns +0.
- __nv_y0f(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn y0f(x: f32) -> f32;

    #[link_name = "__nv_y1"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order 1 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_y1.html#__nv_y1)

# Returns

Returns the value of the Bessel function of the second kind of order 1.
- __nv_y1(0) returns .
- __nv_y1(x) returns NaN for x < 0.
- __nv_y1( ) returns +0.
- __nv_y1(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn y1(x: f64) -> f64;

    #[link_name = "__nv_y1f"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order 1 for the input
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_y1f.html#__nv_y1f)

# Returns

Returns the value of the Bessel function of the second kind of order 1.
- __nv_y1f(0) returns .
- __nv_y1f(x) returns NaN for x < 0.
- __nv_y1f( ) returns +0.
- __nv_y1f(NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn y1f(x: f32) -> f32;

    #[link_name = "__nv_yn"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order for the input
n
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_yn.html#__nv_yn)

# Returns

Returns the value of the Bessel function of the second kind of order .
n
- __nv_yn(n, x) returns NaN for n < 0.
- __nv_yn(n, 0) returns .
- __nv_yn(n, x) returns NaN for x < 0.
- __nv_yn(n, ) returns +0.
- __nv_yn(n, NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 7."]
    pub fn yn(n: i32, x: f64) -> f64;

    #[link_name = "__nv_ynf"]
    #[doc = "Calculate the value of the Bessel function of the second kind of order for the input
n
argument , x.

[Nvidia docs](https://docs.nvidia.com/cuda/libdevice-users-guide/__nv_ynf.html#__nv_ynf)

# Returns

Returns the value of the Bessel function of the second kind of order .
n
- __nv_ynf(n, x) returns NaN for n < 0.
- __nv_ynf(n, 0) returns .
- __nv_ynf(n, x) returns NaN for x < 0.
- __nv_ynf(n, ) returns +0.
- __nv_ynf(n, NaN) returns NaN.
For accuracy information for this function see the CUDA C Programming Guide,
Appendix D.1, Table 6."]
    pub fn ynf(n: i32, x: f32) -> f32;

}