gemm.h

Functions for matrix multiplication.

Functions

void nvte_cublas_gemm(const NVTETensor A, const NVTETensor B, NVTETensor D, const NVTETensor bias, NVTETensor pre_gelu_out, bool transa, bool transb, bool grad, NVTETensor workspace, bool accumulate, bool use_split_accumulator, int math_sm_count, cudaStream_t stream)

Compute matrix multiplication of 2 matrices, potentially fused with other operations.

Computes:

  • D = AB if both bias and pre_gelu_out are empty tensors

  • D = AB + bias if pre_gelu_out is empty and bias is not empty

  • D = GELU(AB + bias) if both bias and pre_gelu_out are not empty tensors

Parameters

  • A – [in] The A matrix.

  • B – [in] The B matrix.

  • D – [inout] Output matrix.

  • bias – [in] Bias tensor.

  • pre_gelu_out – [inout] Output matrix before GELU activation.

  • transa – [in] Whether A matrix is transposed.

  • transb – [in] Whether B matrix is transposed.

  • grad – [in] Whether this operation is part of the gradient computation.

  • workspace – [out] Workspace tensor.

  • accumulate – [in] Whether to accumulate the result into the D matrix.

  • use_split_accumulator – [in] Whether to use split accumulator in the FP8 GEMM.

  • math_sm_count – [in] Number of GPU SMs to use (default=0: use cuBLAS heuristics)

  • stream – [in] CUDA stream used for the operation.

void nvte_cublas_atomic_gemm(const NVTETensor A, const NVTETensor B, NVTETensor D, const NVTETensor bias, NVTETensor pre_gelu_out, bool transa, bool transb, bool grad, NVTETensor workspace, bool accumulate, bool use_split_accumulator, int math_sm_count, int m_split, int n_split, bool gemm_producer, const NVTETensor counter, cudaStream_t stream)

Compute matrix multiplication of 2 matrices with chunking and atomic counters.

Computes:

  • D = AB if both bias and pre_gelu_out are empty tensors

  • D = AB + bias if pre_gelu_out is empty and bias is not empty

  • D = GELU(AB + bias) if both bias and pre_gelu_out are not empty tensors

Warning

Cublas atomic gemm uses a beta API and is not tested for all use cases.

Parameters

  • A – [in] The A matrix.

  • B – [in] The B matrix.

  • D – [inout] Output matrix.

  • bias – [in] Bias tensor.

  • pre_gelu_out – [inout] Output matrix before GELU activation.

  • transa – [in] Whether A matrix is transposed.

  • transb – [in] Whether B matrix is transposed.

  • grad – [in] Whether this operation is part of the gradient computation.

  • workspace – [out] Workspace tensor.

  • accumulate – [in] Whether to accumulate the result into the D matrix.

  • use_split_accumulator – [in] Whether to use split accumulator in the FP8 GEMM.

  • math_sm_count – [in] Number of GPU SMs to use (default=0: use cuBLAS heuristics)

  • m_split – [in] Number of chunks/splits along m-dimension for Atomic GEMM.

  • n_split – [in] Number of chunks/splits along n-dimension for Atomic GEMM.

  • gemm_producer – [in] Whether Atomic GEMM is the producer or consumer.

  • counter – [inout] counter[chunk_i]=0 indicates chunk_i has been produced.

  • stream – [in] CUDA stream used for the operation.