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CUTLASS 2.10 (#615)

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Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
This commit is contained in:
ANIKET SHIVAM
2022-09-03 15:48:46 -07:00
committed by GitHub
parent ca23ff7924
commit b72cbf957d
289 changed files with 43708 additions and 2513 deletions
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tools/library/scripts/pycutlass/src/cpp/test/gemm/gemm.h Normal file
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/***************************************************************************************************
* Copyright (c) 2017 - 2022 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 Bind gemm test to python
*/
#pragma once
#include <pybind11/pybind11.h>
#include <pybind11/stl_bind.h>
#include "host.h"
namespace py = pybind11;
void bind_gemm_test(py::module &m) {
py::module_ host_submodule = m.def_submodule("host");
bind_gemm_host_reference(host_submodule);
}

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tools/library/scripts/pycutlass/src/cpp/test/gemm/host.h Normal file
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/***************************************************************************************************
* Copyright (c) 2017 - 2022 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 Bind gemm test host functions to python
*/
#pragma once
#include <pybind11/pybind11.h>
#include <pybind11/stl_bind.h>
#include "cutlass/cutlass.h"
#include "cutlass/util/reference/host/gemm.h"
#include "cutlass/util/reference/host/tensor_compare.h"
#include "cutlass/util/host_reorder.h"
#include "cutlass/functional.h"
namespace py = pybind11;
template<
typename ElementA, typename LayoutA,
typename ElementB, typename LayoutB,
typename ElementC, typename LayoutC,
typename AccumulatorType, typename ComputeType,
typename InnerProductOp>
void bind_host_gemm_saturate(py::module &m) {
m.def("gemm_saturate", py::overload_cast<
cutlass::gemm::GemmCoord, ComputeType,
cutlass::TensorRef<ElementA, LayoutA>,
cutlass::TensorRef<ElementB, LayoutB>,
ComputeType,
cutlass::TensorRef<ElementC, LayoutC>,
cutlass::TensorRef<ElementC, LayoutC>,
AccumulatorType>(
&cutlass::reference::host::compute_gemm<
ElementA, LayoutA,
ElementB, LayoutB,
ElementC, LayoutC,
ComputeType,
AccumulatorType,
InnerProductOp,
cutlass::NumericConverterClamp<ElementC, AccumulatorType>>
));
}
template<
typename ElementA, typename LayoutA,
typename ElementB, typename LayoutB,
typename ElementC, typename LayoutC,
typename AccumulatorType, typename ComputeType,
typename InnerProductOp>
void bind_host_gemm(py::module &m) {
m.def("gemm", py::overload_cast<
cutlass::gemm::GemmCoord, ComputeType,
cutlass::TensorRef<ElementA, LayoutA>,
cutlass::TensorRef<ElementB, LayoutB>,
ComputeType,
cutlass::TensorRef<ElementC, LayoutC>,
cutlass::TensorRef<ElementC, LayoutC>,
AccumulatorType>(
&cutlass::reference::host::compute_gemm<
ElementA, LayoutA,
ElementB, LayoutB,
ElementC, LayoutC,
ComputeType,
AccumulatorType,
InnerProductOp,
cutlass::NumericConverter<ElementC, AccumulatorType>>
));
}
template<
typename ElementA, typename ElementB, typename ElementC,
typename AccumulatorType, typename ComputeType>
void bind_host_gemm_multiply_add(py::module &m) {
bind_host_gemm<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::RowMajor,
ComputeType, AccumulatorType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
}
template<
typename ElementA, typename ElementB, typename ElementC,
typename AccumulatorType, typename ComputeType>
void bind_host_gemm_multiply_add_saturate(py::module &m) {
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::RowMajor,
ComputeType, AccumulatorType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::RowMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::RowMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajor,
ElementB, cutlass::layout::ColumnMajor,
ElementC, cutlass::layout::ColumnMajor,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
}
template<
typename ElementA, typename ElementB, typename ElementC,
typename AccumulatorType, typename ComputeType>
void bind_host_gemm_multiply_add_interleaved(py::module &m) {
bind_host_gemm<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
ComputeType, AccumulatorType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
}
template<
typename ElementA, typename ElementB, typename ElementC,
typename AccumulatorType, typename ComputeType>
void bind_host_gemm_multiply_add_saturate_interleaved(py::module &m) {
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
ComputeType, AccumulatorType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::RowMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::RowMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::RowMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
bind_host_gemm_saturate<
ElementA, cutlass::layout::ColumnMajorInterleaved<32>,
ElementB, cutlass::layout::ColumnMajorInterleaved<32>,
ElementC, cutlass::layout::ColumnMajorInterleaved<32>,
AccumulatorType, ComputeType,
cutlass::multiply_add<AccumulatorType>>(m);
}
#define BIND_TENSOR_EQUAL(Element, Layout) { \
m.def("equals", py::overload_cast< \
const cutlass::TensorView<Element, Layout>&, const cutlass::TensorView<Element, Layout>&>( \
&cutlass::reference::host::TensorEquals<Element, Layout>)); \
}
void bind_gemm_host_reference(py::module &m) {
/// double
bind_host_gemm_multiply_add<double, double, double, double, double>(m);
/// float
bind_host_gemm_multiply_add<float, float, float, float, float>(m);
/// half_t
bind_host_gemm_multiply_add<cutlass::half_t, cutlass::half_t, cutlass::half_t, cutlass::half_t, cutlass::half_t>(m);
bind_host_gemm_multiply_add<cutlass::half_t, cutlass::half_t, cutlass::half_t, float, float>(m);
bind_host_gemm_multiply_add<cutlass::half_t, cutlass::half_t, float, cutlass::half_t, cutlass::half_t>(m);
bind_host_gemm_multiply_add<cutlass::half_t, cutlass::half_t, float, float, float>(m);
/// bfloat16
bind_host_gemm_multiply_add<cutlass::bfloat16_t, cutlass::bfloat16_t, cutlass::bfloat16_t, float, float>(m);
bind_host_gemm_multiply_add<cutlass::bfloat16_t, cutlass::bfloat16_t, float, float, float>(m);
/// s8
bind_host_gemm_multiply_add<int8_t, int8_t, int8_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int8_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int32_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int32_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int8_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int8_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int32_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int32_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_interleaved<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int8_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int8_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int32_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int32_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int8_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int8_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int32_t, int32_t, int32_t>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int32_t, int32_t, int8_t>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int8_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int32_t, int32_t, float>(m);
bind_host_gemm_multiply_add_saturate_interleaved<int8_t, int8_t, int32_t, int32_t, float>(m);
// float
BIND_TENSOR_EQUAL(float, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(float, cutlass::layout::ColumnMajor);
// double
BIND_TENSOR_EQUAL(double, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(double, cutlass::layout::ColumnMajor);
// half_t
BIND_TENSOR_EQUAL(cutlass::half_t, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(cutlass::half_t, cutlass::layout::ColumnMajor);
// bfloat16
BIND_TENSOR_EQUAL(cutlass::bfloat16_t, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(cutlass::bfloat16_t, cutlass::layout::ColumnMajor);
// int32_t
BIND_TENSOR_EQUAL(int32_t, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(int32_t, cutlass::layout::ColumnMajor);
// int8_t
BIND_TENSOR_EQUAL(int8_t, cutlass::layout::RowMajor);
BIND_TENSOR_EQUAL(int8_t, cutlass::layout::ColumnMajor);
BIND_TENSOR_EQUAL(int8_t, cutlass::layout::RowMajorInterleaved<32>);
BIND_TENSOR_EQUAL(int8_t, cutlass::layout::ColumnMajorInterleaved<32>);
}