Crate singe_cusolver_sys 

Raw FFI bindings for cuSOLVER.

Prefer the safe singe-cusolver crate unless direct NVIDIA ABI access is required.

Structs

CUstream_st

_IO_FILE

_IO_codecvt

_IO_marker

_IO_wide_data

__BindgenBitfieldUnit

cusolverDnContext

cusolverDnIRSInfos

cusolverDnIRSParams

cusolverDnParams

double2

float2

gesvdjInfo

syevjInfo

Enums

cublasDiagType_t

cublasFillMode_t

The type indicates which part (lower or upper) of the dense matrix was filled and consequently should be used by the function.

cublasOperation_t

The cublasOperation_t type indicates which operation needs to be performed with the dense matrix.

cublasSideMode_t

cusolverAlgMode_t

The cusolverAlgMode_t type indicates which algorithm is selected by cusolverDnSetAdvOptions. The set of algorithms supported for each routine is described in detail along with the routine’s documentation.

cusolverDeterministicMode_t

The cusolverDeterministicMode_t type indicates whether multiple cuSolver function executions with the same input have the same bitwise equal result (deterministic) or might have bitwise different results (non-deterministic). In comparison to cublasAtomicsMode_t, which only includes the usage of atomic functions, cusolverDeterministicMode_t includes all non-deterministic programming patterns. The deterministic mode can be set and queried using cusolverDnSetDeterministicMode and cusolverDnGetDeterministicMode routines, respectively.

cusolverDirectMode_t

Specifies the order in which the elementary reflectors are multiplied to form the block reflector.

cusolverDnFunction_t

The cusolverDnFunction_t type indicates which routine needs to be configured by cusolverDnSetAdvOptions. The value cusolverDnFunction_t::CUSOLVERDN_GETRF corresponds to the routine Getrf.

cusolverEigMode_t

The cusolverEigMode_t type indicates whether or not eigenvectors are computed.

cusolverEigRange_t

cusolverEigType_t

The cusolverEigType_t type indicates which type of eigenvalue the solver is.

cusolverIRSRefinement_t

The cusolverIRSRefinement_t type indicates which solver type would be used for the specific cusolver function. Most of our experimentation shows that cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES is the best option.

cusolverMathMode_t

The cusolverMathMode_t type is used in cusolverDnSetMathMode to choose compute precision modes as defined in the following table:

cusolverNorm_t

cusolverPrecType_t

cusolverStatus_t

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

cusolverStorevMode_t

Specifies how the vectors which define the elementary reflectors are stored.

Constants

CUSOLVER_VERSION

CUSOLVER_VER_BUILD

CUSOLVER_VER_MAJOR

CUSOLVER_VER_MINOR

CUSOLVER_VER_PATCH

Functions

cusolverDnCCgels^⚠

cusolverDnCCgels_bufferSize^⚠

cusolverDnCCgesv^⚠

cusolverDnCCgesv_bufferSize^⚠

cusolverDnCEgels^⚠

cusolverDnCEgels_bufferSize^⚠

cusolverDnCEgesv^⚠

cusolverDnCEgesv_bufferSize^⚠

cusolverDnCKgels^⚠

cusolverDnCKgels_bufferSize^⚠

cusolverDnCKgesv^⚠

cusolverDnCKgesv_bufferSize^⚠

cusolverDnCYgels^⚠

cusolverDnCYgels_bufferSize^⚠

cusolverDnCYgesv^⚠

cusolverDnCYgesv_bufferSize^⚠

cusolverDnCgebrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnCgebrd_bufferSize^⚠

cusolverDnCgeqrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnCgeqrf_bufferSize^⚠

cusolverDnCgesvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnCgesvd_bufferSize^⚠

cusolverDnCgesvdaStridedBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnCgesvdaStridedBatched_bufferSize^⚠

cusolverDnCgesvdj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnCgesvdjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnCgesvdjBatched_bufferSize^⚠

cusolverDnCgesvdj_bufferSize^⚠

cusolverDnCgetrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnCgetrf_bufferSize^⚠

cusolverDnCgetrs^⚠

Please visit cuSOLVER Library Samples - getrf for a code example.

cusolverDnCheevd^⚠

cusolverDnCheevd_bufferSize^⚠

cusolverDnCheevdx^⚠

cusolverDnCheevdx_bufferSize^⚠

cusolverDnCheevj^⚠

cusolverDnCheevjBatched^⚠

cusolverDnCheevjBatched_bufferSize^⚠

cusolverDnCheevj_bufferSize^⚠

cusolverDnChegvd^⚠

cusolverDnChegvd_bufferSize^⚠

cusolverDnChegvdx^⚠

cusolverDnChegvdx_bufferSize^⚠

cusolverDnChegvj^⚠

cusolverDnChegvj_bufferSize^⚠

cusolverDnChetrd^⚠

cusolverDnChetrd_bufferSize^⚠

cusolverDnClaswp^⚠

cusolverDnClauum^⚠

cusolverDnClauum_bufferSize^⚠

cusolverDnCpotrf^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnCpotrfBatched^⚠

The S and D data types are real valued single and double precision, respectively. Please visit cuSOLVER Library Samples - potrfBatched for a code example.

cusolverDnCpotrf_bufferSize^⚠

cusolverDnCpotri^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnCpotri_bufferSize^⚠

cusolverDnCpotrs^⚠

This function solves a system of linear equations: $$ A\*X = B $$

cusolverDnCpotrsBatched^⚠

This function solves a sequence of linear systems: $$ {A\lbrack i\rbrack}\*{X\lbrack i\rbrack} = {B\lbrack i\rbrack} $$

cusolverDnCreate^⚠

This function initializes the cuSolverDN library and creates a handle on the cuSolverDN context. It must be called before any other cuSolverDN API function is invoked. It allocates hardware resources necessary for accessing the GPU. This function allocates 4 MiB or 32 MiB of memory (for GPUs with Compute Capability of 9.0 and higher), which will be used as the cuBLAS workspace for the first user-defined stream on which cusolverDnSetStream is called. For the default stream and in all the other cases, cuBLAS will manage its own workspace.

cusolverDnCreateGesvdjInfo^⚠

This function creates and initializes the structure of gesvdj and gesvdjBatched to default values.

cusolverDnCreateParams^⚠

This function creates and initializes the structure of 64-bit API to default values.

cusolverDnCreateSyevjInfo^⚠

This function creates and initializes the structure of syevj, syevjBatched and sygvj to default values.

cusolverDnCsytrf^⚠

These helper functions calculate the size of the needed buffers.

cusolverDnCsytrf_bufferSize^⚠

cusolverDnCsytri^⚠

cusolverDnCsytri_bufferSize^⚠

cusolverDnCungbr^⚠

cusolverDnCungbr_bufferSize^⚠

cusolverDnCungqr^⚠

cusolverDnCungqr_bufferSize^⚠

cusolverDnCungtr^⚠

cusolverDnCungtr_bufferSize^⚠

cusolverDnCunmqr^⚠

cusolverDnCunmqr_bufferSize^⚠

cusolverDnCunmtr^⚠

cusolverDnCunmtr_bufferSize^⚠

cusolverDnDBgels^⚠

cusolverDnDBgels_bufferSize^⚠

cusolverDnDBgesv^⚠

cusolverDnDBgesv_bufferSize^⚠

cusolverDnDDgels^⚠

cusolverDnDDgels_bufferSize^⚠

cusolverDnDDgesv^⚠

cusolverDnDDgesv_bufferSize^⚠

cusolverDnDHgels^⚠

cusolverDnDHgels_bufferSize^⚠

cusolverDnDHgesv^⚠

cusolverDnDHgesv_bufferSize^⚠

cusolverDnDSgels^⚠

cusolverDnDSgels_bufferSize^⚠

cusolverDnDSgesv^⚠

cusolverDnDSgesv_bufferSize^⚠

cusolverDnDXgels^⚠

cusolverDnDXgels_bufferSize^⚠

cusolverDnDXgesv^⚠

cusolverDnDXgesv_bufferSize^⚠

cusolverDnDestroy^⚠

This function releases CPU-side resources used by the cuSolverDN library.

cusolverDnDestroyGesvdjInfo^⚠

This function destroys and releases any memory required by the structure.

cusolverDnDestroyParams^⚠

This function destroys and releases any memory required by the structure.

cusolverDnDestroySyevjInfo^⚠

This function destroys and releases any memory required by the structure.

cusolverDnDgebrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDgebrd_bufferSize^⚠

cusolverDnDgeqrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDgeqrf_bufferSize^⚠

cusolverDnDgesvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDgesvd_bufferSize^⚠

cusolverDnDgesvdaStridedBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDgesvdaStridedBatched_bufferSize^⚠

cusolverDnDgesvdj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDgesvdjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDgesvdjBatched_bufferSize^⚠

cusolverDnDgesvdj_bufferSize^⚠

cusolverDnDgetrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDgetrf_bufferSize^⚠

cusolverDnDgetrs^⚠

Please visit cuSOLVER Library Samples - getrf for a code example.

cusolverDnDlaswp^⚠

cusolverDnDlauum^⚠

cusolverDnDlauum_bufferSize^⚠

cusolverDnDorgbr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDorgbr_bufferSize^⚠

cusolverDnDorgqr^⚠

These helper functions calculate the size of work buffers needed. Please visit cuSOLVER Library Samples - orgqr for a code example.

cusolverDnDorgqr_bufferSize^⚠

cusolverDnDorgtr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDorgtr_bufferSize^⚠

cusolverDnDormqr^⚠

These helper functions calculate the size of work buffers needed. Please visit cuSOLVER Library Samples - ormqr for a code example.

cusolverDnDormqr_bufferSize^⚠

cusolverDnDormtr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDormtr_bufferSize^⚠

cusolverDnDpotrf^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnDpotrfBatched^⚠

The S and D data types are real valued single and double precision, respectively. Please visit cuSOLVER Library Samples - potrfBatched for a code example.

cusolverDnDpotrf_bufferSize^⚠

cusolverDnDpotri^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnDpotri_bufferSize^⚠

cusolverDnDpotrs^⚠

This function solves a system of linear equations: $$ A\*X = B $$

cusolverDnDpotrsBatched^⚠

This function solves a sequence of linear systems: $$ {A\lbrack i\rbrack}\*{X\lbrack i\rbrack} = {B\lbrack i\rbrack} $$

cusolverDnDsyevd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsyevd_bufferSize^⚠

cusolverDnDsyevdx^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsyevdx_bufferSize^⚠

cusolverDnDsyevj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsyevjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsyevjBatched_bufferSize^⚠

cusolverDnDsyevj_bufferSize^⚠

cusolverDnDsygvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsygvd_bufferSize^⚠

cusolverDnDsygvdx^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsygvdx_bufferSize^⚠

cusolverDnDsygvj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnDsygvj_bufferSize^⚠

cusolverDnDsytrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnDsytrd_bufferSize^⚠

cusolverDnDsytrf^⚠

These helper functions calculate the size of the needed buffers.

cusolverDnDsytrf_bufferSize^⚠

cusolverDnDsytri^⚠

cusolverDnDsytri_bufferSize^⚠

cusolverDnGetDeterministicMode^⚠

This function queries the deterministic mode which is set for handle.

cusolverDnGetEmulationSpecialValuesSupport^⚠

This function queries the special floating point value support which is set for handle if floating point emulation is allowed.

cusolverDnGetEmulationStrategy^⚠

This function queries the emulation strategy which is set for handle.

cusolverDnGetFixedPointEmulationMantissaBitOffset^⚠

This function queries the mantissa bit offset for fixed point FP64 emulation in case of dynamic mantissa control mode.

cusolverDnGetFixedPointEmulationMantissaControl^⚠

This function queries how the number of mantissa bits is determined for fixed point FP64 emulation.

cusolverDnGetFixedPointEmulationMaxMantissaBitCount^⚠

This function queries the maximum number of mantissa bits used for fixed point FP64 emulation.

cusolverDnGetMathMode^⚠

This function queries the math modes which are set for handle. Note that math modes can be combined, e.g., cusolverDnSetMathMode(handle, CUSOLVER_FP32_EMULATED_BF16X9_MATH | CUSOLVER_FP64_EMULATED_FIXEDPOINT_MATH). Please see cusolverMathMode_t for allowed combinations.

cusolverDnGetStream^⚠

This function queries the stream to be used by the cuSolverDN library to execute its routines.

cusolverDnIRSInfosCreate^⚠

This function creates and initializes the Infos structure that will hold the refinement information of an Iterative Refinement Solver (IRS) call. Such information includes the total number of iterations that was needed to converge (Niters), the outer number of iterations (meaningful when two-levels preconditioner such as cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL_GMRES is used ), the maximal number of iterations that was allowed for that call, and a pointer to the matrix of the convergence history residual norms. The Infos structure needs to be created before a call to an IRS solver. The Infos structure is valid for only one call to an IRS solver, since it holds info about that solve and thus each solve will requires its own Infos structure.

cusolverDnIRSInfosDestroy^⚠

This function destroys and releases any memory required by the Infos structure. This function destroys all the information (for example, Niters performed, OuterNiters performed, residual history etc.) about a solver call; thus, this function should only be called after the user is finished with the information.

cusolverDnIRSInfosGetMaxIters^⚠

This function returns the maximal allowed number of iterations that was set for the corresponding call to the IRS solver. Note that this function returns the setting that was set when that call happened and is not to be confused with the cusolverDnIRSParamsGetMaxIters which returns the current setting in the params configuration structure. To be clearer, the params structure can be used for many calls to an IRS solver. A user can change the allowed MaxIters between calls while the Infos structure in cusolverDnIRSInfosGetMaxIters contains information about a particular call and cannot be reused for different calls, thus cusolverDnIRSInfosGetMaxIters returns the allowed MaxIters for that call.

cusolverDnIRSInfosGetNiters^⚠

This function returns the total number of iterations performed by the IRS solver. If it was negative, it means that the IRS solver did not converge and if the user did not disable the fallback to full precision, then the fallback to a full precision solution happened and solution is good. Please refer to the description of negative niters values in the corresponding IRS linear solver functions such as cusolverDnXgesv() or cusolverDnXgels().

cusolverDnIRSInfosGetOuterNiters^⚠

This function returns the number of iterations performed by the outer refinement loop of the IRS solver. When the refinement solver consists of a one-level solver such as cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL or cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES, it is the same as Niters. When the refinement solver consists of a two-levels solver such as cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL_GMRES or cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES_GMRES, it is the number of iterations of the outer loop. Refer to the description of the cusolverIRSRefinement_t for more details.

cusolverDnIRSInfosGetResidualHistory^⚠

If the user called cusolverDnIRSInfosRequestResidual before the call to the IRS function, then the IRS solver will store the convergence history (residual norms) of the refinement phase in a matrix that can be accessed via a pointer returned by this function. The datatype of the residual norms depends on the input and output data type. If the Inputs/Outputs datatype is double precision real or complex (CUSOLVER_R_FP64 or CUSOLVER_C_FP64), this residual will be of type real double precision (FP64) double, otherwise if the Inputs/Outputs datatype is single precision real or complex (CUSOLVER_R_FP32 or CUSOLVER_C_FP32), this residual will be real single precision FP32 float.

cusolverDnIRSInfosRequestResidual^⚠

This function tells the IRS solver to store the convergence history (residual norms) of the refinement phase in a matrix that can be accessed via a pointer returned by the cusolverDnIRSInfosGetResidualHistory function.

cusolverDnIRSParamsCreate^⚠

This function creates and initializes the structure of parameters for an IRS solver such as the cusolverDnIRSXgesv or the cusolverDnIRSXgels functions to default values. The params structure created by this function can be used by one or more call to the same or to a different IRS solver. Note that in CUDA 10.2, the behavior was different and a new params structure was needed to be created per each call to an IRS solver. Also note that the user can also change configurations of the params and then call a new IRS instance, but be careful that the previous call was done because any change to the configuration before the previous call was done could affect it.

cusolverDnIRSParamsDestroy^⚠

This function destroys and releases any memory required by the Params structure.

cusolverDnIRSParamsDisableFallback^⚠

This function disables the fallback to the main precision in case the Iterative Refinement Solver (IRS) failed to converge. In other term, if the IRS solver failed to converge, the solver will return a no convergence code (e.g., niter < 0), but can either return the non-convergent solution as it is (e.g., disable fallback) or can fallback (e.g., enable fallback) to the main precision (which is the precision of the Inputs/Outputs data) and solve the problem from scratch returning the good solution. This function disables the fallback and the returned solution is whatever the refinement solver was able to reach before it returns. Disabling fallback does not guarantee that the solution is the good one. However, if users want to keep getting the solution of the lower precision in case the IRS did not converge after certain number of iterations, they need to disable the fallback. The user can re-enable it by calling cusolverDnIRSParamsEnableFallback.

cusolverDnIRSParamsEnableFallback^⚠

This function enable the fallback to the main precision in case the Iterative Refinement Solver (IRS) failed to converge. In other term, if the IRS solver failed to converge, the solver will return a no convergence code (e.g., niter < 0), but can either return the non-convergent solution as it is (e.g., disable fallback) or can fallback (e.g., enable fallback) to the main precision (which is the precision of the Inputs/Outputs data) and solve the problem from scratch returning the good solution. This is the behavior by default, and it will guarantee that the IRS solver always provide the good solution. This function is provided because we provided cusolverDnIRSParamsDisableFallback which allows the user to disable the fallback and thus this function allow the user to re-enable it.

cusolverDnIRSParamsGetMaxIters^⚠

This function returns the current setting in the params structure for the maximal allowed number of iterations (for example, either the default MaxIters, or the one set by the user in case he set it using cusolverDnIRSParamsSetMaxIters). Note that this function returns the current setting in the params configuration and not to be confused with the cusolverDnIRSInfosGetMaxIters which return the maximal allowed number of iterations for a particular call to an IRS solver. To be clearer, the params structure can be used for many calls to an IRS solver. A user can change the allowed MaxIters between calls while the Infos structure in cusolverDnIRSInfosGetMaxIters contains information about a particular call and cannot be reused for different calls, and thus, cusolverDnIRSInfosGetMaxIters returns the allowed MaxIters for that call.

cusolverDnIRSParamsSetMaxIters^⚠

This function sets the total number of allowed refinement iterations after which the solver will stop. Total means any iteration which means the sum of the outer and the inner iterations (inner is meaningful when two-levels refinement solver is set). Default value is set to 50. Our goal is to give the user more control such a way he can investigate and control every detail of the IRS solver.

cusolverDnIRSParamsSetMaxItersInner^⚠

This function sets the maximal number of iterations allowed for the inner refinement solver. It is not referenced in case of one level refinement solver such as cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL or cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES. The inner refinement solver will stop after reaching either the inner tolerance or the MaxItersInner value. By default, it is set to 50. Note that this value could not be larger than the MaxIters since MaxIters is the total number of allowed iterations. Note that if the user calls cusolverDnIRSParamsSetMaxIters after calling this function, SetMaxIters has priority and will overwrite MaxItersInner to the minimum value of (MaxIters, MaxItersInner).

cusolverDnIRSParamsSetRefinementSolver^⚠

This function sets the refinement solver to be used in the Iterative Refinement Solver functions such as the cusolverDnIRSXgesv or the cusolverDnIRSXgels functions. Note that the user has to set the refinement algorithm before a first call to the IRS solver because it is NOT set by default with the creating of params. Details about values that can be set to and theirs meaning are described in the table below.

cusolverDnIRSParamsSetSolverLowestPrecision^⚠

This function sets the lowest precision that will be used by Iterative Refinement Solver. By lowest precision, we mean the solver is allowed to use as lowest computational precision during the LU factorization process. Note that the user has to set both the main and lowest precision before a first call to the IRS solver because they are NOT set by default with the params structure creation, as it depends on the Input Output data type and user request. Usually the lowest precision defines the speedup that can be achieved. The ratio of the performance of the lowest precision over the main precision (e.g., Inputs/Outputs datatype) define somehow the upper bound of the speedup that could be obtained. More precisely, it depends on many factors, but for large matrices sizes, it is the ratio of the matrix-matrix rank-k product (e.g., GEMM where K is 256 and M=N=size of the matrix) that define the possible speedup. For instance, if the inout precision is real double precision CUSOLVER_R_64F and the lowest precision is CUSOLVER_R_32F, then we can expect a speedup of at most 2X for large problem sizes. If the lowest precision was CUSOLVER_R_16F, then we can expect 3X-4X. A reasonable strategy should take the number of right-hand sides, the size of the matrix as well as the convergence rate into account.

cusolverDnIRSParamsSetSolverMainPrecision^⚠

This function sets the main precision for the Iterative Refinement Solver (IRS). By main precision, we mean, the type of the Input and Output data. Note that the user has to set both the main and lowest precision before a first call to the IRS solver because they are NOT set by default with the params structure creation, as it depends on the Input Output data type and user request. user can set it by either calling this function or by calling cusolverDnIRSParamsSetSolverPrecisions which set both the main and the lowest precision together. All possible combinations of main/lowest precision are described in the table in the cusolverDnIRSParamsSetSolverPrecisions section above.

cusolverDnIRSParamsSetSolverPrecisions^⚠

This function sets both the main and the lowest precision for the Iterative Refinement Solver (IRS). By main precision, we mean the precision of the Input and Output datatype. By lowest precision, we mean the solver is allowed to use as lowest computational precision during the LU factorization process. Note that the user has to set both the main and lowest precision before the first call to the IRS solver because they are NOT set by default with the params structure creation, as it depends on the Input Output data type and user request. It is a wrapper to both cusolverDnIRSParamsSetSolverMainPrecision and cusolverDnIRSParamsSetSolverLowestPrecision. All possible combinations of main/lowest precision are described in the table below. Usually the lowest precision defines the speedup that can be achieved. The ratio of the performance of the lowest precision over the main precision (e.g., Inputs/Outputs datatype) define the upper bound of the speedup that could be obtained. More precisely, it depends on many factors, but for large matrices sizes, it is the ratio of the matrix-matrix rank-k product (e.g., GEMM where K is 256 and M=N=size of the matrix) that define the possible speedup. For instance, if the inout precision is real double precision CUSOLVER_R_64F and the lowest precision is CUSOLVER_R_32F, then we can expect a speedup of at most 2X for large problem sizes. If the lowest precision was CUSOLVER_R_16F, then we can expect 3X-4X. A reasonable strategy should take the number of right-hand sides, the size of the matrix as well as the convergence rate into account.

cusolverDnIRSParamsSetTol^⚠

This function sets the tolerance for the refinement solver. By default it is such that all the RHS satisfy:

cusolverDnIRSParamsSetTolInner^⚠

This function sets the tolerance for the inner refinement solver when the refinement solver consists of two-levels solver (for example, cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL_GMRES or cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES_GMRES cases). It is not referenced in case of one level refinement solver such as cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL or cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_GMRES. It is set to 1e-4 by default. This function sets the tolerance for the inner solver (e.g. the inner GMRES). For example, if the Refinement Solver was set to cusolverIRSRefinement_t::CUSOLVER_IRS_REFINE_CLASSICAL_GMRES, setting this tolerance mean that the inner GMRES solver will converge to that tolerance at each outer iteration of the classical refinement solver. Our goal is to give the user more control such a way he can investigate and control every detail of the IRS solver. Note the, the tolerance value is always in real double precision whatever the Inputs/Outputs datatype is.

cusolverDnIRSXgels^⚠

This function is designed to perform same functionality as cusolverDn<T1><T2>gels() functions, but wrapped in a more generic and expert interface that gives user more control to parametrize the function as well as it provides more information on output. cusolverDnIRSXgels allows additional control of the solver parameters such as setting:

cusolverDnIRSXgels_bufferSize^⚠

cusolverDnIRSXgesv^⚠

This function is designed to perform same functionality as cusolverDn<T1><T2>gesv() functions, but wrapped in a more generic and expert interface that gives user more control to parametrize the function as well as it provides more information on output. cusolverDnIRSXgesv allows additional control of the solver parameters such as setting:

cusolverDnIRSXgesv_bufferSize^⚠

cusolverDnLoggerForceDisable^⚠

This function disables logging for the entire run.

cusolverDnLoggerOpenFile^⚠

This function opens a logging output file in the given path.

cusolverDnLoggerSetCallback^⚠

This function sets the logging callback function.

cusolverDnLoggerSetFile^⚠

This function sets the logging output file. Note: once registered using this function call, the provided file handle must not be closed unless the function is called again to switch to a different file handle.

cusolverDnLoggerSetLevel^⚠

This function sets the value of the logging level.

cusolverDnLoggerSetMask^⚠

This function sets the value of the logging mask.

cusolverDnSBgels^⚠

cusolverDnSBgels_bufferSize^⚠

cusolverDnSBgesv^⚠

cusolverDnSBgesv_bufferSize^⚠

cusolverDnSHgels^⚠

cusolverDnSHgels_bufferSize^⚠

cusolverDnSHgesv^⚠

cusolverDnSHgesv_bufferSize^⚠

cusolverDnSSgels^⚠

cusolverDnSSgels_bufferSize^⚠

cusolverDnSSgesv^⚠

cusolverDnSSgesv_bufferSize^⚠

cusolverDnSXgels^⚠

cusolverDnSXgels_bufferSize^⚠

cusolverDnSXgesv^⚠

cusolverDnSXgesv_bufferSize^⚠

cusolverDnSetAdvOptions^⚠

This function configures algorithm algo of function, a 64-bit API routine.

cusolverDnSetDeterministicMode^⚠

This function sets the deterministic mode of all cuSolverDN functions for handle. For improved performance, non-deterministic results can be allowed. Affected functions are cusolverDn<t>geqrf(), cusolverDn<t>syevd(), cusolverDn<t>syevdx(), cusolverDn<t>gesvd() (if m > n), cusolverDn<t>gesvdj(), cusolverDnXgeqrf, cusolverDnXsyevd, cusolverDnXsyevdx, cusolverDnXgesvd (if m > n), cusolverDnXgesvdr and cusolverDnXgesvdp.

cusolverDnSetEmulationSpecialValuesSupport^⚠

This function sets the handling of special floating point values for handle, which is used once floating point emulation is allowed.

cusolverDnSetEmulationStrategy^⚠

This function sets the emulation strategy of all cuSolverDN functions for handle. For more information about the effects of the corresponding strategies, please refer to the analogous definition of cublasEmulationStrategy_t.

cusolverDnSetFixedPointEmulationMantissaBitOffset^⚠

This function sets the mantissa bit offset for fixed point FP64 emulation in case of dynamic mantissa control mode.

cusolverDnSetFixedPointEmulationMantissaControl^⚠

This function sets how the number of mantissa bits is determined for fixed point FP64 emulation. For more information about the effects of the corresponding control modes, please refer to cudaEmulationMantissaControl_t.

cusolverDnSetFixedPointEmulationMaxMantissaBitCount^⚠

This function sets the maximum number of mantissa bits for fixed point FP64 emulation.

cusolverDnSetMathMode^⚠

This function sets the math modes of all cuSolverDN functions for handle. For more information about the effects of the corresponding math modes, please refer to cusolverMathMode_t. Note that math modes can be combined, e.g., cusolverDnSetMathMode(handle, CUSOLVER_FP32_EMULATED_BF16X9_MATH | CUSOLVER_FP64_EMULATED_FIXEDPOINT_MATH). Please see cusolverMathMode_t for allowed combinations.

cusolverDnSetStream^⚠

This function sets the stream to be used by the cuSolverDN library to execute its routines.

cusolverDnSgebrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSgebrd_bufferSize^⚠

cusolverDnSgeqrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSgeqrf_bufferSize^⚠

cusolverDnSgesvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSgesvd_bufferSize^⚠

cusolverDnSgesvdaStridedBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSgesvdaStridedBatched_bufferSize^⚠

cusolverDnSgesvdj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSgesvdjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSgesvdjBatched_bufferSize^⚠

cusolverDnSgesvdj_bufferSize^⚠

cusolverDnSgetrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSgetrf_bufferSize^⚠

cusolverDnSgetrs^⚠

Please visit cuSOLVER Library Samples - getrf for a code example.

cusolverDnSlaswp^⚠

cusolverDnSlauum^⚠

cusolverDnSlauum_bufferSize^⚠

cusolverDnSorgbr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSorgbr_bufferSize^⚠

cusolverDnSorgqr^⚠

These helper functions calculate the size of work buffers needed. Please visit cuSOLVER Library Samples - orgqr for a code example.

cusolverDnSorgqr_bufferSize^⚠

cusolverDnSorgtr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSorgtr_bufferSize^⚠

cusolverDnSormqr^⚠

These helper functions calculate the size of work buffers needed. Please visit cuSOLVER Library Samples - ormqr for a code example.

cusolverDnSormqr_bufferSize^⚠

cusolverDnSormtr^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSormtr_bufferSize^⚠

cusolverDnSpotrf^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnSpotrfBatched^⚠

The S and D data types are real valued single and double precision, respectively. Please visit cuSOLVER Library Samples - potrfBatched for a code example.

cusolverDnSpotrf_bufferSize^⚠

cusolverDnSpotri^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnSpotri_bufferSize^⚠

cusolverDnSpotrs^⚠

This function solves a system of linear equations: $$ A\*X = B $$

cusolverDnSpotrsBatched^⚠

This function solves a sequence of linear systems: $$ {A\lbrack i\rbrack}\*{X\lbrack i\rbrack} = {B\lbrack i\rbrack} $$

cusolverDnSsyevd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsyevd_bufferSize^⚠

cusolverDnSsyevdx^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsyevdx_bufferSize^⚠

cusolverDnSsyevj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsyevjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsyevjBatched_bufferSize^⚠

cusolverDnSsyevj_bufferSize^⚠

cusolverDnSsygvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsygvd_bufferSize^⚠

cusolverDnSsygvdx^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsygvdx_bufferSize^⚠

cusolverDnSsygvj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnSsygvj_bufferSize^⚠

cusolverDnSsytrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnSsytrd_bufferSize^⚠

cusolverDnSsytrf^⚠

These helper functions calculate the size of the needed buffers.

cusolverDnSsytrf_bufferSize^⚠

cusolverDnSsytri^⚠

cusolverDnSsytri_bufferSize^⚠

cusolverDnXgeev^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgeev_bufferSize^⚠

cusolverDnXgeqrf^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgeqrf_bufferSize^⚠

cusolverDnXgesvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgesvd_bufferSize^⚠

cusolverDnXgesvdjGetResidual^⚠

This function reports the Frobenius norm of the internal residual returned by gesvdj. Note that this is not the Frobenious norm of the exact residual calculated as: $$ {\|{S} - {U}^{H}\{A}\{V}\|}_{F} $$

cusolverDnXgesvdjGetSweeps^⚠

This function reports number of executed sweeps of gesvdj. It does not support gesvdjBatched. If the user calls this function after gesvdjBatched, the error cusolverStatus_t::CUSOLVER_STATUS_NOT_SUPPORTED is returned.

cusolverDnXgesvdjSetMaxSweeps^⚠

This function configures the maximum number of sweeps in gesvdj. The default value is 100.

cusolverDnXgesvdjSetSortEig^⚠

If sort_svd is zero, the singular values are not sorted. This function only works for gesvdjBatched. gesvdj always sorts singular values in descending order. By default, singular values are always sorted in descending order.

cusolverDnXgesvdjSetTolerance^⚠

This function configures tolerance of gesvdj.

cusolverDnXgesvdp^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgesvdp_bufferSize^⚠

cusolverDnXgesvdr^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgesvdr_bufferSize^⚠

cusolverDnXgetrf^⚠

The helper function below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXgetrf_bufferSize^⚠

cusolverDnXgetrs^⚠

This function solves a linear system of multiple right-hand sides: $$ op(A)\*X = B $$

cusolverDnXlarft^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXlarft_bufferSize^⚠

cusolverDnXpotrf^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXpotrf_bufferSize^⚠

cusolverDnXpotrs^⚠

This function solves a system of linear equations: $$ A\*X = B $$

cusolverDnXsyevBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXsyevBatched_bufferSize^⚠

cusolverDnXsyevd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXsyevd_bufferSize^⚠

cusolverDnXsyevdx^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXsyevdx_bufferSize^⚠

cusolverDnXsyevjGetResidual^⚠

This function reports residual of syevj or sygvj. It does not support syevjBatched. If the user calls this function after syevjBatched, the error cusolverStatus_t::CUSOLVER_STATUS_NOT_SUPPORTED is returned.

cusolverDnXsyevjGetSweeps^⚠

This function reports number of executed sweeps of syevj or sygvj. It does not support syevjBatched. If the user calls this function after syevjBatched, the error cusolverStatus_t::CUSOLVER_STATUS_NOT_SUPPORTED is returned.

cusolverDnXsyevjSetMaxSweeps^⚠

This function configures maximum number of sweeps in syevj. The default value is 100.

cusolverDnXsyevjSetSortEig^⚠

If sort_eig is zero, the eigenvalues are not sorted. This function only works for syevjBatched. syevj and sygvj always sort eigenvalues in ascending order. By default, eigenvalues are always sorted in ascending order.

cusolverDnXsyevjSetTolerance^⚠

This function configures tolerance of syevj.

cusolverDnXsygvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXsygvd_bufferSize^⚠

cusolverDnXsygvdx^⚠

The helper function below can calculate the sizes needed for pre-allocated buffer.

cusolverDnXsygvdx_bufferSize^⚠

cusolverDnXsytrs^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffers.

cusolverDnXsytrs_bufferSize^⚠

cusolverDnXtrtri^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffers.

cusolverDnXtrtri_bufferSize^⚠

cusolverDnZCgels^⚠

cusolverDnZCgels_bufferSize^⚠

cusolverDnZCgesv^⚠

cusolverDnZCgesv_bufferSize^⚠

cusolverDnZEgels^⚠

cusolverDnZEgels_bufferSize^⚠

cusolverDnZEgesv^⚠

cusolverDnZEgesv_bufferSize^⚠

cusolverDnZKgels^⚠

cusolverDnZKgels_bufferSize^⚠

cusolverDnZKgesv^⚠

cusolverDnZKgesv_bufferSize^⚠

cusolverDnZYgels^⚠

cusolverDnZYgels_bufferSize^⚠

cusolverDnZYgesv^⚠

cusolverDnZYgesv_bufferSize^⚠

cusolverDnZZgels^⚠

cusolverDnZZgels_bufferSize^⚠

cusolverDnZZgesv^⚠

cusolverDnZZgesv_bufferSize^⚠

cusolverDnZgebrd^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnZgebrd_bufferSize^⚠

cusolverDnZgeqrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnZgeqrf_bufferSize^⚠

cusolverDnZgesvd^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnZgesvd_bufferSize^⚠

cusolverDnZgesvdaStridedBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnZgesvdaStridedBatched_bufferSize^⚠

cusolverDnZgesvdj^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnZgesvdjBatched^⚠

The helper functions below can calculate the sizes needed for pre-allocated buffer.

cusolverDnZgesvdjBatched_bufferSize^⚠

cusolverDnZgesvdj_bufferSize^⚠

cusolverDnZgetrf^⚠

These helper functions calculate the size of work buffers needed.

cusolverDnZgetrf_bufferSize^⚠

cusolverDnZgetrs^⚠

Please visit cuSOLVER Library Samples - getrf for a code example.

cusolverDnZheevd^⚠

cusolverDnZheevd_bufferSize^⚠

cusolverDnZheevdx^⚠

cusolverDnZheevdx_bufferSize^⚠

cusolverDnZheevj^⚠

cusolverDnZheevjBatched^⚠

cusolverDnZheevjBatched_bufferSize^⚠

cusolverDnZheevj_bufferSize^⚠

cusolverDnZhegvd^⚠

cusolverDnZhegvd_bufferSize^⚠

cusolverDnZhegvdx^⚠

cusolverDnZhegvdx_bufferSize^⚠

cusolverDnZhegvj^⚠

cusolverDnZhegvj_bufferSize^⚠

cusolverDnZhetrd^⚠

cusolverDnZhetrd_bufferSize^⚠

cusolverDnZlaswp^⚠

cusolverDnZlauum^⚠

cusolverDnZlauum_bufferSize^⚠

cusolverDnZpotrf^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnZpotrfBatched^⚠

The S and D data types are real valued single and double precision, respectively. Please visit cuSOLVER Library Samples - potrfBatched for a code example.

cusolverDnZpotrf_bufferSize^⚠

cusolverDnZpotri^⚠

These helper functions calculate the necessary size of work buffers.

cusolverDnZpotri_bufferSize^⚠

cusolverDnZpotrs^⚠

This function solves a system of linear equations: $$ A\*X = B $$

cusolverDnZpotrsBatched^⚠

This function solves a sequence of linear systems: $$ {A\lbrack i\rbrack}\*{X\lbrack i\rbrack} = {B\lbrack i\rbrack} $$

cusolverDnZsytrf^⚠

These helper functions calculate the size of the needed buffers.

cusolverDnZsytrf_bufferSize^⚠

cusolverDnZsytri^⚠

cusolverDnZsytri_bufferSize^⚠

cusolverDnZungbr^⚠

cusolverDnZungbr_bufferSize^⚠

cusolverDnZungqr^⚠

cusolverDnZungqr_bufferSize^⚠

cusolverDnZungtr^⚠

cusolverDnZungtr_bufferSize^⚠

cusolverDnZunmqr^⚠

cusolverDnZunmqr_bufferSize^⚠

cusolverDnZunmtr^⚠

cusolverDnZunmtr_bufferSize^⚠

cusolverGetProperty^⚠

cusolverGetVersion^⚠

Type Aliases

FILE

_IO_lock_t

__off64_t

__off_t

__uint64_t

cuComplex

cuDoubleComplex

cuFloatComplex

cusolverDnHandle_t

This is a pointer type to an opaque cuSolverDN context, which the user must initialize by calling cusolverDnCreate prior to calling any other library function. An uninitialized Handle object will lead to unexpected behavior, including crashes of cuSolverDN. The handle created and returned by cusolverDnCreate must be passed to every cuSolverDN function.

cusolverDnIRSInfos_t

This is a pointer type to an opaque cusolverDnIRSInfos_t structure, which holds information about the performed call to an iterative refinement linear solver (such as cusolverDnXgesv()). Use corresponding helper functions described below to either Create/Destroy this structure or retrieve solve information.

cusolverDnIRSParams_t

This is a pointer type to an opaque cusolverDnIRSParams_t structure, which holds parameters for the iterative refinement linear solvers such as cusolverDnXgesv(). Use corresponding helper functions described below to either Create/Destroy this structure or Set/Get solver parameters.

cusolverDnLoggerCallback_t

cusolverDnLoggerCallback_t is a callback function pointer type.

cusolverDnParams_t

cusolver_int_t

gesvdjInfo_t

size_t

syevjInfo_t