Enum cusolverStatus_t 

#[repr(u32)]
pub enum cusolverStatus_t {
    CUSOLVER_STATUS_SUCCESS = 0,
    CUSOLVER_STATUS_NOT_INITIALIZED = 1,
    CUSOLVER_STATUS_ALLOC_FAILED = 2,
    CUSOLVER_STATUS_INVALID_VALUE = 3,
    CUSOLVER_STATUS_ARCH_MISMATCH = 4,
    CUSOLVER_STATUS_MAPPING_ERROR = 5,
    CUSOLVER_STATUS_EXECUTION_FAILED = 6,
    CUSOLVER_STATUS_INTERNAL_ERROR = 7,
    CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED = 8,
    CUSOLVER_STATUS_NOT_SUPPORTED = 9,
    CUSOLVER_STATUS_ZERO_PIVOT = 10,
    CUSOLVER_STATUS_INVALID_LICENSE = 11,
    CUSOLVER_STATUS_IRS_PARAMS_NOT_INITIALIZED = 12,
    CUSOLVER_STATUS_IRS_PARAMS_INVALID = 13,
    CUSOLVER_STATUS_IRS_PARAMS_INVALID_PREC = 14,
    CUSOLVER_STATUS_IRS_PARAMS_INVALID_REFINE = 15,
    CUSOLVER_STATUS_IRS_PARAMS_INVALID_MAXITER = 16,
    CUSOLVER_STATUS_IRS_INTERNAL_ERROR = 20,
    CUSOLVER_STATUS_IRS_NOT_SUPPORTED = 21,
    CUSOLVER_STATUS_IRS_OUT_OF_RANGE = 22,
    CUSOLVER_STATUS_IRS_NRHS_NOT_SUPPORTED_FOR_REFINE_GMRES = 23,
    CUSOLVER_STATUS_IRS_INFOS_NOT_INITIALIZED = 25,
    CUSOLVER_STATUS_IRS_INFOS_NOT_DESTROYED = 26,
    CUSOLVER_STATUS_IRS_MATRIX_SINGULAR = 30,
    CUSOLVER_STATUS_INVALID_WORKSPACE = 31,
}

This is a status type returned by the library functions and it can have the following values.

cusolverStatus_t::CUSOLVER_STATUS_SUCCESS: The operation completed successfully.

cusolverStatus_t::CUSOLVER_STATUS_NOT_INITIALIZED: The cuSolver library was not initialized. This is usually caused by the lack of a prior call, an error in the CUDA Runtime API called by the cuSolver routine, or an error in the hardware setup.

To correct: call cusolverDnCreate prior to the function call; and check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed.

cusolverStatus_t::CUSOLVER_STATUS_ALLOC_FAILED: Resource allocation failed inside the cuSolver library. This is usually caused by a cudaMalloc() failure.

To correct: prior to the function call, deallocate previously allocated memory as much as possible.

cusolverStatus_t::CUSOLVER_STATUS_INVALID_VALUE: An unsupported value or parameter was passed to the function (a negative vector size, for example).

To correct: ensure that all the parameters being passed have valid values.

cusolverStatus_t::CUSOLVER_STATUS_ARCH_MISMATCH: The function requires a feature absent from the device architecture; usually caused by the lack of support for atomic operations or double precision.

To correct: compile and run the application on a device with compute capability 5.0 or above.

cusolverStatus_t::CUSOLVER_STATUS_EXECUTION_FAILED: The GPU program failed to execute. This is often caused by a launch failure of the kernel on the GPU, which can be caused by multiple reasons.

To correct: check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed.

cusolverStatus_t::CUSOLVER_STATUS_INTERNAL_ERROR: An internal cuSolver operation failed. This error is usually caused by a cudaMemcpyAsync() failure.

To correct: check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed. Also, check that the memory passed as a parameter to the routine is not being deallocated prior to the routine’s completion.

cusolverStatus_t::CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED: The matrix type is not supported by this function. This is usually caused by passing an invalid matrix descriptor to the function.

To correct: check that the fields in descrA were set correctly.

cusolverStatus_t::CUSOLVER_STATUS_NOT_SUPPORTED: The parameter combination is not supported, for example batched version is not supported or M < N is not supported.

To correct: consult the documentation, and use a supported configuration.

Variants

CUSOLVER_STATUS_SUCCESS = 0

The operation completed successfully.

CUSOLVER_STATUS_NOT_INITIALIZED = 1

The cuSolver library was not initialized. This is usually caused by the lack of a prior call, an error in the CUDA Runtime API called by the cuSolver routine, or an error in the hardware setup.

To correct: call cusolverDnCreate prior to the function call; and check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed.

CUSOLVER_STATUS_ALLOC_FAILED = 2

Resource allocation failed inside the cuSolver library. This is usually caused by a cudaMalloc() failure.

To correct: prior to the function call, deallocate previously allocated memory as much as possible.

CUSOLVER_STATUS_INVALID_VALUE = 3

An unsupported value or parameter was passed to the function (a negative vector size, for example).

To correct: ensure that all the parameters being passed have valid values.

CUSOLVER_STATUS_ARCH_MISMATCH = 4

The function requires a feature absent from the device architecture; usually caused by the lack of support for atomic operations or double precision.

To correct: compile and run the application on a device with compute capability 5.0 or above.

CUSOLVER_STATUS_MAPPING_ERROR = 5

CUSOLVER_STATUS_EXECUTION_FAILED = 6

The GPU program failed to execute. This is often caused by a launch failure of the kernel on the GPU, which can be caused by multiple reasons.

To correct: check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed.

CUSOLVER_STATUS_INTERNAL_ERROR = 7

An internal cuSolver operation failed. This error is usually caused by a cudaMemcpyAsync() failure.

To correct: check that the hardware, an appropriate version of the driver, and the cuSolver library are correctly installed. Also, check that the memory passed as a parameter to the routine is not being deallocated prior to the routine’s completion.

CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED = 8

The matrix type is not supported by this function. This is usually caused by passing an invalid matrix descriptor to the function.

To correct: check that the fields in descrA were set correctly.

CUSOLVER_STATUS_NOT_SUPPORTED = 9

The parameter combination is not supported, for example batched version is not supported or M < N is not supported.

To correct: consult the documentation, and use a supported configuration.

CUSOLVER_STATUS_ZERO_PIVOT = 10

CUSOLVER_STATUS_INVALID_LICENSE = 11

CUSOLVER_STATUS_IRS_PARAMS_NOT_INITIALIZED = 12

CUSOLVER_STATUS_IRS_PARAMS_INVALID = 13

CUSOLVER_STATUS_IRS_PARAMS_INVALID_PREC = 14

CUSOLVER_STATUS_IRS_PARAMS_INVALID_REFINE = 15

CUSOLVER_STATUS_IRS_PARAMS_INVALID_MAXITER = 16

CUSOLVER_STATUS_IRS_INTERNAL_ERROR = 20

CUSOLVER_STATUS_IRS_NOT_SUPPORTED = 21

CUSOLVER_STATUS_IRS_OUT_OF_RANGE = 22

CUSOLVER_STATUS_IRS_NRHS_NOT_SUPPORTED_FOR_REFINE_GMRES = 23

CUSOLVER_STATUS_IRS_INFOS_NOT_INITIALIZED = 25

CUSOLVER_STATUS_IRS_INFOS_NOT_DESTROYED = 26

CUSOLVER_STATUS_IRS_MATRIX_SINGULAR = 30

CUSOLVER_STATUS_INVALID_WORKSPACE = 31

Trait Implementations

impl Clone for cusolverStatus_t

fn clone(&self) -> cusolverStatus_t

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for cusolverStatus_t

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl From<cusolverStatus_t> for u32

fn from(enum_value: cusolverStatus_t) -> Self

Converts to this type from the input type.

impl Hash for cusolverStatus_t

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl Ord for cusolverStatus_t

fn cmp(&self, other: &cusolverStatus_t) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl PartialEq for cusolverStatus_t

fn eq(&self, other: &cusolverStatus_t) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl PartialOrd for cusolverStatus_t

fn partial_cmp(&self, other: &cusolverStatus_t) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Rhs) -> bool

Tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Rhs) -> bool

Tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Rhs) -> bool

Tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Rhs) -> bool

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl TryFrom<u32> for cusolverStatus_t

type Error = TryFromPrimitiveError<cusolverStatus_t>

The type returned in the event of a conversion error.

fn try_from(number: u32) -> Result<Self, TryFromPrimitiveError<Self>>

Performs the conversion.

impl TryFromPrimitive for cusolverStatus_t

const NAME: &'static str = "cusolverStatus_t"

type Primitive = u32

type Error = TryFromPrimitiveError<cusolverStatus_t>

fn try_from_primitive( number: Self::Primitive, ) -> Result<Self, TryFromPrimitiveError<Self>>

impl Copy for cusolverStatus_t

impl Eq for cusolverStatus_t

impl StructuralPartialEq for cusolverStatus_t