cuBLASMp C API

Library Management

cublasMpCreate

cublasMpStatus_t cublasMpCreate(
        cublasMpHandle_t *handle,
        cudaStream_t stream);

This 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 cublasMpStatus_t for the description of the return status.

cublasMpDestroy

cublasMpStatus_t cublasMpDestroy(
        cublasMpHandle_t handle);

This function destroys 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 cublasMpStatus_t for the description of the return status.

cublasMpStreamSet

cublasMpStatus_t cublasMpStreamSet(
        cublasMpHandle_t handle,
        cudaStream_t stream);

This function sets the CUDA stream to be used in the computations.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
stream	Host	In	CUDA stream pointer to set.

See cublasMpStatus_t for the description of the return status.

cublasMpStreamGet

cublasMpStatus_t cublasMpStreamGet(
        cublasMpHandle_t handle,
        cudaStream_t* stream);

This function returns the current CUDA stream that is being used in the computations.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
stream	Host	Out	CUDA stream pointer to set.

See cublasMpStatus_t for the description of the return status.

cublasMpGetVersion

cublasMpStatus_t cublasMpGetVersion(
        int *version);

This function returns the version number of the cuBLASMp library.

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

See cublasMpStatus_t for the description of the return status.

---

Grid Management

cublasMpGridCreate

cublasMpStatus_t cublasMpGridCreate(
        int64_t nprow,
        int64_t npcol,
        cublasMpGridLayout_t layout,
        cal_comm_t comm,
        cublasMpGrid_t* grid);

This 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.

Note

cuBLASMp will initialize NVSHMEM as the first grid is created, hence the user should ensure that it uses a communicator that contains all the required ranks. If NVSHMEM was previously initialized by the user in their application, the first cuBLASMp grid should be created using the same set of ranks. cuBLASMp will call nvshmem_finalize as part of the cublasMpGridDestroy() call of the last remaining grid.

Parameter	Memory	In/Out	Description
nprow	Host	In	How many row processes the grid contains.
npcol	Host	In	How many column processes the grid contains.
layout	Host	In	Grid’s layout (cublasMpGridLayout_t).
comm	Host	In	Communicator associated with the grid.
grid	Host	In/Out	Pointer to a grid object.

See cublasMpStatus_t for the description of the return status.

---

cublasMpGridDestroy

cublasMpStatus_t cublasMpGridDestroy(
        cublasMpGrid_t grid);

This function destroys the given grid object.

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

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

See cublasMpStatus_t for the description of the return status.

---

Matrix Management

cublasMpMatrixDescriptorCreate

cublasMpStatus_t cublasMpMatrixDescriptorCreate(
        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);

This function initializes cublasMpMatrixDescriptor_t object.

Parameter	Memory	In/Out	Description
m	Host	In	Number of rows in the global matrix.
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 type argument are listed.

Data Type	Description
CUDA_R_8I	8-bit real signed integer.
CUDA_R_32I	32-bit real signed integer.
CUDA_R_8F_E4M3	8-bit real floating point in E4M3 format.
CUDA_R_8F_E5M2	8-bit real floating point in E5M2 format.
CUDA_R_16F	16-bit real half precision floating-point.
CUDA_R_16BF	16-bit real bfloat16 floating-point.
CUDA_R_32F	32-bit real single precision floating-point.
CUDA_R_64F	64-bit real double precision floating-point.
CUDA_C_32F	64-bit structure comprised of two single precision floating-points representing a complex number.
CUDA_C_64F	128-bit structure comprised of two double precision floating-points representing a complex number.

See cublasMpStatus_t for the description of the return status.

---

cublasMpMatrixDescriptorDestroy

cublasMpStatus_t cublasMpMatrixDescriptorDestroy(
        cublasMpMatrixDescriptor_t desc);

This function destroys cublasMpMatrixDescriptor_t object.

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

See cublasMpStatus_t for the description of the return status.

cublasMpMatrixDescriptorInit

cublasMpStatus_t cublasMpMatrixDescriptorInit(
        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);

This function initializes the values of a cublasMpMatrixDescriptor_t object. This function does not allocate additional memory.

Parameter	Memory	In/Out	Description
m	Host	In	Number of rows in the global matrix.
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 type argument are listed below:

Data Type	Description
CUDA_R_8I	8-bit real signed integer.
CUDA_R_32I	32-bit real signed integer.
CUDA_R_8F_E4M3	8-bit real floating point in E4M3 format.
CUDA_R_8F_E5M2	8-bit real floating point in E5M2 format.
CUDA_R_16F	16-bit real half precision floating-point.
CUDA_R_16BF	16-bit real bfloat16 floating-point.
CUDA_R_32F	32-bit real single precision floating-point.
CUDA_R_64F	64-bit real double precision floating-point.
CUDA_C_32F	64-bit structure comprised of two single precision floating-points representing a complex number.
CUDA_C_64F	128-bit structure comprised of two double precision floating-points representing a complex number.

See cublasMpStatus_t for the description of the return status.

---

Matmul Properties

cublasMpMatmulDescriptorCreate

cublasMpStatus_t cublasMpMatmulDescriptorCreate(
        cublasMpMatmulDescriptor_t* matmulDesc,
        cublasComputeType_t computeType);

This function initializes the values of a cublasMpMatmulDescriptor_t object used in cublasMpMatmul().

Parameter	Memory	In/Out	Description
matmulDesc	Host	In/Out	Pointer to a cublasMpMatmulDescriptor object to initialize.
computeType	Host	In	cuBLAS compute type used for computations. See table below for supported combinations.

Supported values for computeType argument are listed.

Compute Types
CUBLAS_COMPUTE_32I
CUBLAS_COMPUTE_32I_PEDANTIC
CUBLAS_COMPUTE_16F
CUBLAS_COMPUTE_16F_PEDANTIC
CUBLAS_COMPUTE_32F
CUBLAS_COMPUTE_32F_PEDANTIC
CUBLAS_COMPUTE_32F_FAST_16F
CUBLAS_COMPUTE_32F_FAST_16BF
CUBLAS_COMPUTE_32F_FAST_TF32
CUBLAS_COMPUTE_64F
CUBLAS_COMPUTE_64F_PEDANTIC

See cublasMpStatus_t for the description of the return status.

cublasMpMatmulDescriptorDestroy

cublasMpStatus_t cublasMpMatmulDescriptorDestroy(
        cublasMpMatmulDescriptor_t matmulDesc);

This function destroys cublasMpMatmulDescriptor_t object used in cublasMpMatmul().

Parameter	Memory	In/Out	Description
matmulDesc	Host	In/Out	Matmul descriptor object to destroy.

See cublasMpStatus_t for the description of the return status.

cublasMpMatmulDescriptorAttributeSet

cublasMpStatus_t cublasMpMatmulDescriptorAttributeSet(
        cublasMpMatmulDescriptor_t matmulDesc,
        cublasMpMatmulDescriptorAttribute_t attr,
        const void* buf,
        size_t sizeInBytes);

This function sets attributes of cublasMpMatmulDescriptor_t object used in cublasMpMatmul(). The attributes are of type cublasMpMatmulDescriptorAttribute_t.

Parameter	Memory	In/Out	Description
matmulDesc	Host	In	Matmul descriptor object to set its attribute.
attr	Host	In	Matmul descriptor attribute to set.
buf	Host	In	Attribute value to set.
sizeInBytes	Host	In	Attribute buffer size in bytes.

See cublasMpStatus_t for the description of the return status.

cublasMpMatmulDescriptorAttributeGet

cublasMpStatus_t cublasMpMatmulDescriptorAttributeGet(
        cublasMpMatmulDescriptor_t matmulDesc,
        cublasMpMatmulDescriptorAttribute_t attr,
        const void* buf,
        size_t sizeInBytes,
        size_t* sizeWritten);

This function returns the attributes of cublasMpMatmulDescriptor_t object used in cublasMpMatmul().

Parameter	Memory	In/Out	Description
matmulDesc	Host	In	Matmul descriptor object to set its attribute.
attr	Host	In	Matmul descriptor attribute to set.
buf	Host	Out	Attribute value to set.
sizeInBytes	Host	In	Attribute buffer size in bytes.
sizeWritten	Host	Out	Size of the attribute written into buf in bytes.

See cublasMpStatus_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 whose 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

cublasMpStatus_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	Device 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 cublasMpStatus_t for the description of the return status.

---

cublasMpGemr2D_bufferSize

cublasMpStatus_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(B).
n	Host	In	Number of columns of sub(B) 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	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 cublasMpStatus_t for the description of the return status.

---

cublasMpTrmr2D

cublasMpStatus_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	Device 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 cublasMpStatus_t for the description of the return status.

---

cublasMpTrmr2D_bufferSize

cublasMpStatus_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(B).
n	Host	In	Number of columns of sub(B) 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	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 cublasMpStatus_t for the description of the return status.

---

Logging

cublasMpLoggerSetCallback

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetFile

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerOpenFile

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetLevel

cublasMpStatus_t cublasMpLoggerSetLevel(
        int level);

This function sets the logging level.

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

See cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerSetMask

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

cublasMpLoggerForceDisable

cublasMpStatus_t cublasMpLoggerForceDisable();

This function disables logging for the entire run.

See cublasMpStatus_t for the description of the return status.

Warning

This is an experimental feature.

---

Dense Linear Algebra APIs

cublasMpTrsm

cublasMpStatus_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 \(A\)

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

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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpTrsm_bufferSize

cublasMpStatus_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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpGemm

cublasMpStatus_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 \(B\) .

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	Device 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().

Note

This routine will internally call cublasMpMatmul() with d == c.

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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpGemm_bufferSize

cublasMpStatus_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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpMatmul

cublasMpStatus_t cublasMpMatmul(
        cublasMpHandle_t handle,
        cublasMpMatmulDescriptor_t matmulDesc,
        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,
        const void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        void* d,
        int64_t id,
        int64_t jd,
        cublasMpMatrixDescriptor_t descD,
        void* d_work,
        size_t workspaceSizeInBytesOnDevice,
        void* h_work,
        size_t workspaceSizeInBytesOnHost);

This function performs the matrix-matrix multiplication

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

where \(\alpha\) and \(\beta\) are scalars, and \(A\), \(B\), \(C\) and \(D\) are matrices stored in column-major format with dimensions \(\text{op}(A)\) \(m \times k\) , \(\text{op}(B)\) \(k \times n\), \(C\) \(m \times n\) and \(D\) \(m \times n\) , respectively. \(\text{op}(A)\) depends on the value of CUBLASMP_MATMUL_DESCRIPTOR_ATTRIBUTE_TRANSA attribute of the matmulDesc descriptor:

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

and \(\text{op}(B)\) is defined similarly for matrix \(B\) based on the CUBLASMP_MATMUL_DESCRIPTOR_ATTRIBUTE_TRANSB attribute.

Note

FP8 matrix multiplication is only supported for the TN format, i.e. \(A^T * B\), CUBLASMP_MATMUL_DESCRIPTOR_ATTRIBUTE_TRANSA == CUBLAS_OP_T, CUBLASMP_MATMUL_DESCRIPTOR_ATTRIBUTE_TRANSB == CUBLAS_OP_N.

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
matmulDesc	Host	In	Descriptor of the operation to perform, created with cublasMpMatmulDescriptorCreate().
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. c can be set to null if beta == 0.
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	Device	Out	Pointer to the first entry of the local portion of the global matrix D.
id	Host	In	Row index of the first row of the sub(D). id must be a multiple of the row blocking dimension mbD.
jd	Host	In	Column index of the first column of the sub(D). jd must be a multiple of the column blocking dimension nbD.
descD	Host	In	Matrix descriptor associated to the global matrix D.
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 cublasMpMatmul_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 cublasMpMatmul_bufferSize().

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype	Btype	Ctype	Dtype
CUBLAS_COMPUTE_16F or CUBLAS_COMPUTE_16F_PEDANTIC	CUDA_R_16F	CUDA_R_16F	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_16BF	CUDA_R_16BF
		CUDA_R_16F	CUDA_R_16F	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8I	CUDA_R_8I	CUDA_R_32F	CUDA_R_32F
		CUDA_R_16BF	CUDA_R_16BF	CUDA_R_32F	CUDA_R_32F
		CUDA_R_16F	CUDA_R_16F	CUDA_R_32F	CUDA_R_32F
		CUDA_R_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_8I	CUDA_C_8I	CUDA_C_32F	CUDA_C_32F
		CUDA_C_32F	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_32F	CUDA_R_32F
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_8F_E5M2
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_8F_E5M2
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_32F	CUDA_R_32F
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E5M2
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E5M2
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_32F	CUDA_R_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_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_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_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

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

See cublasMpStatus_t for the description of the return status.

---

cublasMpMatmul_bufferSize

cublasMpStatus_t cublasMpMatmul_bufferSize(
        cublasMpHandle_t handle,
        cublasMpMatmulDescriptor_t matmulDesc,
        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,
        const void* c,
        int64_t ic,
        int64_t jc,
        cublasMpMatrixDescriptor_t descC,
        void* d,
        int64_t id,
        int64_t jd,
        cublasMpMatrixDescriptor_t descD,
        size_t* workspaceSizeInBytesOnDevice,
        size_t* workspaceSizeInBytesOnHost);

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

Parameter	Memory	In/Out	Description
handle	Host	In	cuBLASMp library handle.
matmulDesc	Host	In	Descriptor of the operation to perform, created with cublasMpMatmulDescriptorCreate().
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.
d	Device	Out	Pointer to the first entry of the local portion of the global matrix D.
id	Host	In	Row index of the first row of the sub(D). id must be a multiple of the row blocking dimension mbD.
jd	Host	In	Column index of the first column of the sub(D). jd must be a multiple of the column blocking dimension nbD.
descD	Host	In	Matrix descriptor associated to the global matrix D.
workspaceInBytesOnDevice	Host	Out	On output, contains the size in bytes of the local device workspace needed by cublasMpMatmul().
workspaceInBytesOnHost	Host	Out	On output, contains the size in bytes of the local host workspace needed by cublasMpMatmul().

This routine supports the following combinations of data types:

Compute Type	Scale Type (alpha and beta)	Atype	Btype	Ctype	Dtype
CUBLAS_COMPUTE_16F or CUBLAS_COMPUTE_16F_PEDANTIC	CUDA_R_16F	CUDA_R_16F	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_16BF	CUDA_R_16BF
		CUDA_R_16F	CUDA_R_16F	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8I	CUDA_R_8I	CUDA_R_32F	CUDA_R_32F
		CUDA_R_16BF	CUDA_R_16BF	CUDA_R_32F	CUDA_R_32F
		CUDA_R_16F	CUDA_R_16F	CUDA_R_32F	CUDA_R_32F
		CUDA_R_32F	CUDA_R_32F	CUDA_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_8I	CUDA_C_8I	CUDA_C_32F	CUDA_C_32F
		CUDA_C_32F	CUDA_C_32F	CUDA_C_32F	CUDA_C_32F
CUBLAS_COMPUTE_32F	CUDA_R_32F	CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E4M3	CUDA_R_32F	CUDA_R_32F
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16BF	CUDA_R_8F_E5M2
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_16F	CUDA_R_8F_E5M2
		CUDA_R_8F_E4M3	CUDA_R_8F_E5M2	CUDA_R_32F	CUDA_R_32F
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_16BF
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E4M3
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16BF	CUDA_R_8F_E5M2
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_16F
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E4M3
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_16F	CUDA_R_8F_E5M2
		CUDA_R_8F_E5M2	CUDA_R_8F_E4M3	CUDA_R_32F	CUDA_R_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_R_32F	CUDA_R_32F
	CUDA_C_32F	CUDA_C_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_R_64F	CUDA_R_64F
	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F	CUDA_C_64F

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

See cublasMpStatus_t for the description of the return status.

---

cublasMpSyrk

cublasMpStatus_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 \(A\)

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

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 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	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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpSyrk_bufferSize

cublasMpStatus_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 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 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 provided to this function is used only for internal matrix-matrix multiplications.

See cublasMpStatus_t for the description of the return status.

---

cublasMpGeadd

cublasMpStatus_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 \(A\)

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

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	Device 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 cublasMpStatus_t for the description of the return status.

---

cublasMpGeadd_bufferSize

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.

---

cublasMpTradd

cublasMpStatus_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 \(A\)

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

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	Device 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 cublasMpStatus_t for the description of the return status.

---

cublasMpTradd_bufferSize

cublasMpStatus_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 cublasMpStatus_t for the description of the return status.