Files
cutlass/include/cutlass/gemm/kernel/params_sparse_base.h
2024-03-19 17:51:04 -04:00

116 lines
3.8 KiB
C++

/***************************************************************************************************
* Copyright (c) 2017 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* 3. Neither the name of the copyright holder nor the names of its
* contributors may be used to endorse or promote products derived from
* this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/*! \file
\brief Base functionality for common types of sparse GEMM kernel parameters
*/
#pragma once
#include "cutlass/cutlass.h"
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace gemm {
namespace kernel {
/////////////////////////////////////////////////////////////////////////////////////////////////
/// Parameters structure
template <
typename ThreadblockSwizzle,
typename ParamsA,
typename TensorRefA,
typename ParamsB,
typename TensorRefB,
typename ParamsE,
typename TensorRefE>
struct SparseParamsBase
{
//
// Data members
//
cutlass::gemm::GemmCoord problem_size{};
cutlass::gemm::GemmCoord grid_tiled_shape{};
int swizzle_log_tile;
ParamsA params_A{};
TensorRefA ref_A{};
ParamsB params_B{};
TensorRefB ref_B{};
ParamsE params_E{};
TensorRefE ref_E{};
int gemm_k_iterations{0};
int gemm_k_size{0};
//
// Host dispatch API
//
/// Default constructor
SparseParamsBase() = default;
/// Constructor
CUTLASS_HOST_DEVICE
SparseParamsBase(
cutlass::gemm::GemmCoord const & problem_size,
cutlass::gemm::GemmCoord const & grid_tiled_shape,
TensorRefA ref_A,
TensorRefB ref_B,
TensorRefE ref_E,
int const mma_shape_k)
:
problem_size(problem_size),
grid_tiled_shape(grid_tiled_shape),
swizzle_log_tile(ThreadblockSwizzle().get_log_tile(grid_tiled_shape)),
params_A(ref_A.layout()),
ref_A(ref_A),
params_B(ref_B.layout()),
ref_B(ref_B),
params_E(ref_E.layout()),
ref_E(ref_E)
{
int total_gemm_k_iterations = (problem_size.k() + mma_shape_k - 1) / mma_shape_k;
int gemm_k_iterations = (total_gemm_k_iterations + grid_tiled_shape.k() - 1) / grid_tiled_shape.k();
gemm_k_size = gemm_k_iterations * mma_shape_k;
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace kernel
} // namespace gemm
} // namespace cutlass
/////////////////////////////////////////////////////////////////////////////////////////////////