cuBLASMp C API

Library Management

cublasMpCreate

cublasStatus_t cublasMpCreate(
        cublasMpHandle_t *handle,
        cudaStream_t stream);

The function initializes the cuBLASMp library handle (cublasMpHandle_t) which holds the cuBLASMp library context. It allocates light hardware resources on the host, and must be called prior to making any other cuBLASMp library calls.

Calling any cuBLASMp function which uses cublasMpHandle_t without a previous call of cublasMpCreate() will return an error.

The cuBLASMp library context is tied to the current CUDA device and the given CUDA stream.

Sharing a device with multiple processes may result in undefined behavior.

Parameter	Memory	In/Out	Description
handle	Host	Out	cuBLASMp library handle
stream	Host	In	Stream that will be assigned to the handle.

See cublasStatus_t for the description of the return status.

cublasMpDestroy

cublasStatus_t cublasMpDestroy(
        cublasMpHandle_t handle);

The function destroy the cuBLASMp library handle (cublasMpHandle_t) which holds the cuBLASMp library context.

The cuBLASMp library context is tied to the CUDA device that was set when calling cublasMpCreate(). Only one handle per process and per GPU supported.

Parameter	Memory	In/Out	Description
handle	Host	In/Out	cuBLASMp library handle to destroy

See cublasStatus_t for the description of the return status.

cublasMpGetVersion

cublasStatus_t cublasMpGetVersion(
        cublasMpHandle_t handle,
        int *version);

This function returns the version number of the cuBLASMp library.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
version	Host	Out	cuBLASMp library version. Value is CUBLASMP_VER_MAJOR * 1000 + CUBLASMP_VER_MINOR * 100 + CUBLASMP_VER_PATCH

See cublasStatus_t for the description of the return status.

cublasMpSetMathMode

cublasStatus_t cublasMpSetMathMode(
        cublasMpHandle_t handle,
        cublasMath_t mode);

The function enables you to choose the compute precision modes as defined by cublasMath_t. Users are allowed to set the compute precision mode as a logical combination of them (except the deprecated CUBLAS_TENSOR_OP_MATH). For example, cublasMpSetMathMode(handle, CUBLAS_DEFAULT_MATH | CUBLAS_MATH_DISALLOW_REDUCED_PRECISION_REDUCTION). Please note that the default math mode is CUBLAS_DEFAULT_MATH.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
mode	Host	In	cuBLAS math mode.

See cublasStatus_t for the description of the return status.

cublasMpGetMathMode

cublasStatus_t cublasMpGetMathMode(
        cublasMpHandle_t handle,
        cublasMath_t* mode);

This function returns the math mode used by the library routines.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
mode	Host	Out	cuBLAS math mode.

See cublasStatus_t for the description of the return status.

---

Grid Management

cublasMpGridCreate

cublasStatus_t cublasMpGridCreate(
        cublasMpHandle_t handle,
        int64_t nprow,
        int64_t npcol,
        int64_t myprow,
        int64_t mypcol,
        cal_comm_t comm,
        cublasMpGrid_t* grid);

The function initializes the grid opaque data structure. It maps the given resources (communicator, grid dimensions and grid layout) to a grid object.

All the processes defined to be in this grid must enter this function.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
nprow	Host	In	How many row process the grid contains.
npcol	Host	In	How many column process the grid contains.
myprow	Host	In	What is the current process’s row rank.
mypcol	Host	In	What is the current process’s column rank
comm	Host	In	Communicator associated with the grid.
grid	Host	In/Out	Pointer to a grid object.

See cublasStatus_t for the description of the return status.

---

cublasMpGridDestroy

cublasStatus_t cublasMpGridDestroy(
        cublasMpHandle_t handle,
        cublasMpGrid_t grid);

The function destroys the given grid object.

All the processes defined to be in this grid must enter this function.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
grid	Host	In/Out	Grid object to destroy.

See cublasStatus_t for the description of the return status.

---

Matrix Management

cublasMpMatrixDescriptorCreate

cublasStatus_t cublasMpMatrixDescriptorCreate(
        cublasMpHandle_t handle,
        int64_t m,
        int64_t n,
        int64_t mb,
        int64_t nb,
        int64_t rsrc,
        int64_t csrc,
        int64_t lld,
        cudaDataType_t type,
        cublasMpGrid_t grid,
        cublasMpMatrixDescriptor_t* desc);

The function initializes cublasMpMatrixDescriptor_t object.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
m	Host	In	Number of rows in the global array.
n	Host	In	Number of columns in the global matrix.
mb	Host	In	Blocking factor used to distribute the rows of the global matrix.
nb	Host	In	Blocking factor used to distribute the columns of the global matrix.
rsrc	Host	In	Row rank of the process who owns the first row block of the global matrix.
csrc	Host	In	Column rank of the process who owns the first column block of the global matrix.
lld	Host	In	Leading dimension of the local matrix.
type	Host	In	Data type of the matrix.
grid	Host	In	Grid object associated with the matrix descriptor
desc	Host	Out	Matrix descriptor object initialized by this function.

Supported values for dataType argument are listed.

Data Type of A	Description
CUDA_R_32F	Single precision real values.
CUDA_R_64F	Double precision real values.
CUDA_C_32F	Single precision complex values.
CUDA_C_64F	Double precision complex values.

See cublasStatus_t for the description of the return status.

---

cublasMpMatrixDescriptorDestroy

cublasStatus_t cublasMpMatrixDescriptorDestroy(
        cublasMpHandle_t handle,
        cublasMpMatrixDescriptor_t desc);

The function destroys cublasMpMatrixDescriptor_t object.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle
desc	Host	In/Out	Matrix descriptor object to destroy.

See cublasStatus_t for the description of the return status.

---

Utility

cublasMpNumroc

int64_t cublasMpNumroc(
        int64_t n,
        int64_t nb,
        uint32_t iproc,
        uint32_t isrcproc,
        uint32_t nprocs);

Computes the number of rows or columns of a distributed matrix owned by the process indicated by iproc argument.

Parameter	Memory	In/Out	Description
n	Host	In	Number of rows or columns in the global distributed matrix.
nb	Host	In	Row or column blocking size of the global matrix.
iproc	Host	In	The coordinate of the process whole local array row or column is to be determined.
isrcproc	Host	In	The coordinate of the process that owns the first row or column of the distributed matrix.
nprocs	Host	In	The total number of row or column processes over which the matrix is distributed.

---

cublasMpGemr2D

cublasStatus_t cublasMpGemr2D(
        cublasMpHandle_t handle,
        int64_t m,
        int64_t n,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost,
        cal_comm_t global_comm);

This function redistributes general rectangular matrix A according to the distribution properties of matrix B.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
m	Host	In	Number of rows of sub(A) and sub(B).
n	Host	In	Number of columns of sub(A) and sub(B).
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A).
ja	Host	In	Column index of the first column of the sub(A).
descA	Host	In	Matrix descriptor associated to the global matrix A. descA’s grid value must be set to null in processes that are not part of the grid of A.
b	Device	Out	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B).
jb	Host	In	Column index of the first column of the sub(B).
descB	Host	In	Matrix descriptor associated to the global matrix B. descB’s grid value must be set to null in processes that are not part of the grid of B.
d_work	Device	Out	Host workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpGemr2D_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpGemr2D_bufferSize()
global_comm	Host	In	A communicator containing at least the union of all processes in the communicators of A and B. All processes in the communicator must call this function, even if they do not own a piece of either matrix.

See cublasStatus_t for the description of the return status.

---

cublasMpGemr2D_bufferSize

cublasStatus_t cublasMpGemr2D_bufferSize(
        cublasMpHandle_t handle,
        int64_t m,
        int64_t n,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost,
        cal_comm_t global_comm);

This function returns the required buffer sizes to perform cublasMpGemr2D() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(B) and sub(C).
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A).
ja	Host	In	Column index of the first column of the sub(A).
descA	Host	In	Matrix descriptor associated to the global matrix A. descA’s grid value must be set to null in processes that are not part of the grid of A.
b	Device	In	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B).
jb	Host	In	Column index of the first column of the sub(B).
descB	Host	In	Matrix descriptor associated to the global matrix B. descB’s grid value must be set to null in processes that are not part of the grid of B.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpGemr2D().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpGemr2D().
global_comm	Host	In	A communicator containing at least the union of all processes in the communicators of A and B. All processes in the communicator must call this function, even if they do not own a piece of either matrix.

See cublasStatus_t for the description of the return status.

---

cublasMpTrmr2D

cublasStatus_t cublasMpTrmr2D(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasDiagType_t diag,
        int64_t m,
        int64_t n,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost,
        cal_comm_t global_comm);

This function redistributes trapezoidal matrix A according to the distribution properties of trapezoidal matrix B.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix A lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
diag	Host	In	Indicates if the elements on the main diagonal of matrix A are unity and should not be accessed.
m	Host	In	Number of rows of sub(A) and sub(B).
n	Host	In	Number of columns of sub(A) and sub(B).
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A).
ja	Host	In	Column index of the first column of the sub(A).
descA	Host	In	Matrix descriptor associated to the global matrix A. descA’s grid value must be set to null in processes that are not part of the grid of A.
b	Device	Out	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B).
jb	Host	In	Column index of the first column of the sub(B).
descB	Host	In	Matrix descriptor associated to the global matrix B. descB’s grid value must be set to null in processes that are not part of the grid of B.
d_work	Device	Out	Host workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpTrmr2D_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpTrmr2D_bufferSize()
global_comm	Host	In	A communicator containing at least the union of all processes in the communicators of A and B. All processes in the communicator must call this function, even if they do not own a piece of either matrix.

See cublasStatus_t for the description of the return status.

---

cublasMpTrmr2D_bufferSize

cublasStatus_t cublasMpTrmr2D_bufferSize(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasDiagType_t diag,
        int64_t m,
        int64_t n,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost,
        cal_comm_t global_comm);

This function returns the required buffer sizes to perform cublasMpTrmr2D() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix A lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
diag	Host	In	Indicates if the elements on the main diagonal of matrix A are unity and should not be accessed.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(B) and sub(C).
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A).
ja	Host	In	Column index of the first column of the sub(A).
descA	Host	In	Matrix descriptor associated to the global matrix A. descA’s grid value must be set to null in processes that are not part of the grid of A.
b	Device	In	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B).
jb	Host	In	Column index of the first column of the sub(B).
descB	Host	In	Matrix descriptor associated to the global matrix B. descB’s grid value must be set to null in processes that are not part of the grid of B.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpTrmr2D().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpTrmr2D().
global_comm	Host	In	A communicator containing at least the union of all processes in the communicators of A and B. All processes in the communicator must call this function, even if they do not own a piece of either matrix.

See cublasStatus_t for the description of the return status.

---

Logging

cublasMpLoggerSetCallback

cublasStatus_t cublasMpLoggerSetCallback(
        cublasMpLoggerCallback_t callback);

This function sets the logging callback function.

Parameter	Memory	In/Out	Description
callback	Host	In	Pointer to a callback function. See cublasMpLoggerCallback_t.

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetFile

cublasStatus_t cublasMpLoggerSetFile(
        FILE *file);

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.

Parameter	Memory	In/Out	Description
file	Host	In	Pointer to an open file. File should have write permission

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerOpenFile

cublasStatus_t cublasMpLoggerOpenFile(
        const char* logFile);

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

Parameter	Memory	In/Out	Description
logFile	Host	In	Path of the logging output file.

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetLevel

cublasStatus_t cublasMpLoggerSetLevel(
        int level);

Complete

Parameter	Memory	In/Out	Description
level	Host	In	Value of the logging level. See cuBLASMp Logging.

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetMask

cublasStatus_t cublasMpLoggerSetMask(
        int mask);

This function sets the value of the logging mask.

Parameter	Memory	In/Out	Description
mask	Host	In	Value of the logging mask. See cuBLASMp Logging.

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerForceDisable

cublasStatus_t cublasMpLoggerForceDisable(
        int level);

This function disables logging for the entier run.

See cublasStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

Dense Linear Algebra APIs

cublasMpTrsm

cublasStatus_t cublasMpTrsm(
        cublasMpHandle_t handle,
        cublasSideMode_t side,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        cublasDiagType_t diag,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        cublasComputeType_t computeType,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function solves the triangular linear system with multiple right-hand-sides

\(\left\{ \begin{matrix} {\text{op}(A)X = \alpha B} & {\text{if }\textsf{side == $\mathrm{CUBLAS\_SIDE\_LEFT}$}} \\ {X\text{op}(A) = \alpha B} & {\text{if }\textsf{side == $\mathrm{CUBLAS\_SIDE\_RIGHT}$}} \\ \end{matrix} \right.\)

where \(A\) is a triangular matrix stored in lower or upper mode with or without the main diagonal, \(X\) and \(B\) are \(m \times n\) matrices, and \(\alpha\) is a scalar. Also, for matrix \(A\)

\(\text{op}(A) = \left\{ \begin{matrix} A & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_N}$}} \\ A^{T} & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_T}$}} \\ A^{H} & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_C}$}} \\ \end{matrix} \right.\)

The solution \(X\) overwrites the right-hand-sides \(B\) on exit.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
side	Host	In	Indicates if matrix A is on the left or right of X.
uplo	Host	In	Indicates if matrix A lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
diag	Host	In	Indicates if the elements on the main diagonal of matrix A are unity and should not be accessed.
m	Host	In	Number of rows of matrix sub(B), with matrix sub(A) sized accordingly.
n	Host	In	Number of columns of matrix sub(B), with matrix sub(A) is sized accordingly.
alpha	Host	In	Scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A
b	Device	In/Out	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B). ib must be a multiple of the row blocking dimension mbB.
jb	Host	In	Column index of the first column of the sub(B). jb must be a multiple of the column blocking dimension nbB.
descB	Host	In	Matrix descriptor associated to the global matrix B
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
d_work	Device	Out	Device workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpTrsm_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpTrsm_bufferSize()

This function requires square block size.

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpTrsm_bufferSize

cublasStatus_t cublasMpTrsm_bufferSize(
        cublasMpHandle_t handle,
        cublasSideMode_t side,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        cublasDiagType_t diag,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        cublasComputeType_t computeType,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

This function returns the required buffer sizes to perform cublasMpTrsm() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
side	Host	In	Indicates if matrix A is on the left or right of X.
uplo	Host	In	Indicates if matrix A lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
diag	Host	In	Indicates if the elements on the main diagonal of matrix A are unity and should not be accessed.
m	Host	In	Number of rows of matrix sub(B), with matrix sub(A) sized accordingly.
n	Host	In	Number of columns of matrix sub(B), with matrix sub(A) is sized accordingly.
alpha	Host	In	Scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A
b	Device	In	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B). ib must be a multiple of the row blocking dimension mbB.
jb	Host	In	Column index of the first column of the sub(B). jb must be a multiple of the column blocking dimension nbB.
descB	Host	In	Matrix descriptor associated to the global matrix B
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpTrsm().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpTrsm().

This function requires square block size.

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpGemm

cublasStatus_t cublasMpGemm(
        cublasMpHandle_t handle,
        cublasOperation_t transA,
        cublasOperation_t transB,
        int64_t m,
        int64_t n,
        int64_t k,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        cublasComputeType_t computeType,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function performs the matrix-matrix multiplication

\(C = \alpha\text{op}(A)\text{op}(B) + \beta C\)

where \(\alpha\) and \(\beta\) are scalars, and \(A\) , \(B\) and \(C\) are matrices stored in column-major format with dimensions \(\text{op}(A)\) \(m \times k\) , \(\text{op}(B)\) \(k \times n\) and \(C\) \(m \times n\) , respectively. Also, for matrix \(A\)

\(\text{op}(A) = \left\{ \begin{matrix} A & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_N}$}} \\ A^{T} & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_T}$}} \\ A^{H} & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_C}$}} \\ \end{matrix} \right.\)

and \(\text{op}(B)\) is defined similarly for matrix \(B\) .

trans	Form of the linear system
CUBLAS_OP_N	\(sub(A) \cdot X = sub(B)\)
CUBLAS_OP_T	\(sub(A)^T \cdot X = sub(B)\)
CUBLAS_OP_C	\(sub(A)^H \cdot X = sub(B)\)

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
transA	Host	In	Operation op(A) that is non- or (conj.) transpose.
transB	Host	In	Operation op(B) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(B) and sub(C).
k	Host	In	Number of columns of sub(A) and rows of sub(B).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
b	Device	In	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B). ib must be a multiple of the row blocking dimension mbB.
jb	Host	In	Column index of the first column of the sub(B). jb must be a multiple of the column blocking dimension nbB.
descB	Host	In	Matrix descriptor associated to the global matrix B.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In/Out	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
d_work	Device	Out	Host workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpGemm_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpGemm_bufferSize()

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_16F or CUBLAS_COMPUTE_16F_PEDANTIC	CUDA_R_16F	CUDA_R_16F	CUDA_R_16F
CUBLAS_COMPUTE_32F or CUBLAS_COMPUTE_32F_PEDANTIC	CUDA_R_32F	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_16F	CUDA_R_16F
		CUDA_R_8I	CUDA_R_32F
		CUDA_R_16BF	CUDA_R_32F
		CUDA_R_16F	CUDA_R_32F
		CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_8I	CUDA_C_32F
		CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_32F_FAST_16F or CUBLAS_COMPUTE_32F_FAST_16BF or CUBLAS_COMPUTE_32F_FAST_TF32	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F or CUBLAS_COMPUTE_64F_PEDANTIC	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpGemm_bufferSize

cublasStatus_t cublasMpGemm_bufferSize(
        cublasMpHandle_t handle,
        cublasOperation_t transA,
        cublasOperation_t transB,
        int64_t m,
        int64_t n,
        int64_t k,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* b,
        int64_t ib,
        int64_t jb,
        cublasMpMatrixDescriptor_t descB,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        cublasComputeType_t computeType,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

This function returns the required buffer sizes to perform cublasMpGemm() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
transA	Host	In	Operation op(A) that is non- or (conj.) transpose.
transB	Host	In	Operation op(B) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(B) and sub(C).
k	Host	In	Number of columns of sub(A) and rows of sub(B).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
b	Device	In	Pointer to the first entry of the local portion of the global matrix B.
ib	Host	In	Row index of the first row of the sub(B). ib must be a multiple of the row blocking dimension mbB.
jb	Host	In	Column index of the first column of the sub(B). jb must be a multiple of the column blocking dimension nbB.
descB	Host	In	Matrix descriptor associated to the global matrix B.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpGemm().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpGemm().

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_16F or CUBLAS_COMPUTE_16F_PEDANTIC	CUDA_R_16F	CUDA_R_16F	CUDA_R_16F
CUBLAS_COMPUTE_32F or CUBLAS_COMPUTE_32F_PEDANTIC	CUDA_R_32F	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_16F	CUDA_R_16F
		CUDA_R_8I	CUDA_R_32F
		CUDA_R_16BF	CUDA_R_32F
		CUDA_R_16F	CUDA_R_32F
		CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_8I	CUDA_C_32F
		CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_32F_FAST_16F or CUBLAS_COMPUTE_32F_FAST_16BF or CUBLAS_COMPUTE_32F_FAST_TF32	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F or CUBLAS_COMPUTE_64F_PEDANTIC	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpSyrk

cublasStatus_t cublasMpSyrk(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        int64_t n,
        int64_t k,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        cublasComputeType_t computeType,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function performs the symmetric rank- \(k\) update

\(C = \alpha\text{op}(A)\text{op}(A)^{T} + \beta C\)

where \(\alpha\) and \(\beta\) are scalars, \(C\) is a symmetric matrix stored in lower or upper mode, and \(A\) is a matrix with dimensions \(\text{op}(A)\) \(n \times k\) . Also, for matrix \(A\)

\(\text{op}(A) = \left\{ \begin{matrix} A & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_N}$}} \\ A^{T} & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_T}$}} \\ \end{matrix} \right.\)

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix C lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or transpose.
n	Host	In	Number of rows of sub(A) and sub(C).
k	Host	In	Number of columns of sub(A).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In/Out	Pointer to the first entry of the local portion of the global matrix A.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
d_work	Device	Out	Device workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpSyrk_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpSyrk_bufferSize().

This function requires square block size.

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpSyrk_bufferSize

cublasStatus_t cublasMpSyrk_bufferSize(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        int64_t n,
        int64_t k,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        cublasComputeType_t computeType,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

This function returns the required buffer sizes to perform cublasMpSyrk() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix C lower or upper part is stored, the other symmetric part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or transpose.
n	Host	In	Number of rows of sub(A) and sub(C).
k	Host	In	Number of columns of sub(A).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpSyrk().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpSyrk().

This function requires square block size.

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype/Btype	Ctype
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_64F	CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

The computeType parameter provdied to this function is used only for internal matrix-matrix multiplications.

See cublasStatus_t for the description of the return status.

---

cublasMpGeadd

cublasStatus_t cublasMpGeadd(
        cublasMpHandle_t handle,
        cublasOperation_t trans,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function performs the matrix-matrix addition

\(C = \alpha\text{op}(A) + \beta C\)

where \(\alpha\) and \(\beta\) are scalars, and \(A\) and \(C\) are matrices stored in column-major format with dimensions \(\text{op}(A)\) \(m \times n\) and \(C\) \(m \times n\) , respectively. Also, for matrix \(A\)

\(\text{op}(A) = \left\{ \begin{matrix} A & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_N}$}} \\ A^{T} & {\text{if }\textsf{trans == $\mathrm{CUBLAS\_OP\_T}$}} \\ A^{H} & {\text{if }\textsf{trans == $\mathrm{CUBLAS\_OP\_C}$}} \\ \end{matrix} \right.\)

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(A) and sub(C).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In/Out	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
d_work	Device	Out	Host workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpGeadd_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpGeadd_bufferSize()

This function requires square block size.

This routine supports the following combinations of data types:

Data Type of A	computeType	Output Data Type
CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

See cublasStatus_t for the description of the return status.

---

cublasMpGeadd_bufferSize

cublasStatus_t cublasMpGeadd_bufferSize(
        cublasMpHandle_t handle,
        cublasOperation_t trans,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

This function returns the required buffer sizes to perform cublasMpGeadd() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(A) and sub(C).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpGeadd().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpGeadd().

This function requires square block size.

This routine supports the following combinations of data types:

Data Type of A	computeType	Output Data Type
CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

See cublasStatus_t for the description of the return status.

---

cublasMpTradd

cublasStatus_t cublasMpTradd(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function performs the trapezoidal matrix-matrix addition

\(C = \alpha\text{op}(A) + \beta C\)

where \(\alpha\) and \(\beta\) are scalars, and \(A\) and \(C\) are matrices stored in column-major format with dimensions \(\text{op}(A)\) \(m \times n\) and \(C\) \(m \times n\) , respectively. Also, for matrix \(A\)

\(\text{op}(A) = \left\{ \begin{matrix} A & {\text{if }\textsf{transa == $\mathrm{CUBLAS\_OP\_N}$}} \\ A^{T} & {\text{if }\textsf{trans == $\mathrm{CUBLAS\_OP\_T}$}} \\ A^{H} & {\text{if }\textsf{trans == $\mathrm{CUBLAS\_OP\_C}$}} \\ \end{matrix} \right.\)

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix C lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(A) and sub(C).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In/Out	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
d_work	Device	Out	Host workspace of size workspaceInBytesOnDevice.
workspaceInBytesOnDevice	Host	In	The size in bytes of the local device workspace needed by the routine as provided by cublasMpTradd_bufferSize().
h_work	Host	Out	Host workspace of size workspaceInBytesOnHost.
workspaceInBytesOnHost	Host	In	The size in bytes of the local host workspace needed by the routine as provided by cublasMpTradd_bufferSize()

This function requires square block size.

This routine supports the following combinations of data types:

Data Type of A	computeType	Output Data Type
CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

See cublasStatus_t for the description of the return status.

---

cublasMpTradd_bufferSize

cublasStatus_t cublasMpTradd_bufferSize(
        cublasMpHandle_t handle,
        cublasFillMode_t uplo,
        cublasOperation_t trans,
        int64_t m,
        int64_t n,
        const void* alpha,
        const void* a,
        int64_t ia,
        int64_t ja,
        cublasMpMatrixDescriptor_t descA,
        const void* beta,
        void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

This function returns the required buffer sizes to perform cublasMpTradd() on the given input.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
uplo	Host	In	Indicates if matrix C lower or upper part is stored, the other part is not referenced and is inferred from the stored elements.
trans	Host	In	Operation op(A) that is non- or (conj.) transpose.
m	Host	In	Number of rows of sub(A) and sub(C).
n	Host	In	Number of columns of sub(A) and sub(C).
alpha	Host	In	<type> scalar used for multiplication.
a	Device	In	Pointer to the first entry of the local portion of the global matrix A.
ia	Host	In	Row index of the first row of the sub(A). ia must be a multiple of the row blocking dimension mbA.
ja	Host	In	Column index of the first column of the sub(A). ja must be a multiple of the column blocking dimension nbA.
descA	Host	In	Matrix descriptor associated to the global matrix A.
beta	Host	In	<type> scalar used for multiplication.
c	Device	In	Pointer to the first entry of the local portion of the global matrix C.
ic	Host	In	Row index of the first row of the sub(C). ic must be a multiple of the row blocking dimension mbC.
jc	Host	In	Column index of the first column of the sub(C). jc must be a multiple of the column blocking dimension nbC.
descC	Host	In	Matrix descriptor associated to the global matrix C.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpTradd().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpTradd().

This function requires square block size.

This routine supports the following combinations of data types:

Data Type of A	computeType	Output Data Type
CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
CUDA_R_64F	CUDA_R_64F	CUDA_R_64F
CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

See cublasStatus_t for the description of the return status.