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sm90_conv1d_wgrad_implicit_gemm_f16_f16_f32_tensorop_f16.cu
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sm90_conv1d_wgrad_implicit_gemm_f16_f16_f32_tensorop_f16.cu
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/***************************************************************************************************
* Copyright (c) 2023 - 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.
*
**************************************************************************************************/
#include "cutlass_unit_test.h"
#include "cutlass/cutlass.h"
#include "cute/tensor.hpp"
#include "cute/atom/mma_atom.hpp"
#include "cutlass/numeric_types.h"
#include "cutlass/conv/device/conv_universal_adapter.hpp"
#include "cutlass/conv/kernel/conv_universal.hpp"
#include "cutlass/conv/collective/collective_builder.hpp"
#include "cutlass/epilogue/collective/collective_builder.hpp"
#include "../testbed_conv.hpp"
using namespace cute;
#if defined(CUTLASS_ARCH_MMA_SM90_SUPPORTED)
//////////////////////////////////////////////////////////////////////////////////////////////////
// Tile shape 64x64x64
//////////////////////////////////////////////////////////////////////////////////////////////////
//
// Cluster 1x1x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 64x64x64_1x1x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_64, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_1,_1,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::TmaWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 1x2x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 64x64x64_1x2x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_64, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_1,_2,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 2x1x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 64x64x64_2x1x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_64, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_2,_1,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 2x2x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 64x64x64_2x2x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_64, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_2,_2,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//////////////////////////////////////////////////////////////////////////////////////////////////
// Tile shape 128x64x64
//////////////////////////////////////////////////////////////////////////////////////////////////
//
// Cluster 1x1x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 128x64x64_1x1x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_128, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_1,_1,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 1x2x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 128x64x64_1x2x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_128, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_1,_2,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 2x1x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 128x64x64_2x1x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_128, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_2,_1,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
//
// Cluster 2x2x1
//
TEST(SM90_device_conv1d_wgrad_implicitgemm_f16nwc_f16nwc_f32nwc_tensor_op_f16, 128x64x64_2x2x1) {
using ElementAct = cutlass::half_t;
using ElementFlt = cutlass::half_t;
using ElementOut = float;
using ElementAcc = cutlass::half_t;
using ElementCompute = float;
using TileShapeMNK = Shape<_128, Shape<_64>, Shape<_64>>;
using ClusterShapeMNK = Shape<_2,_2,_1>;
using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
TileShapeMNK, ClusterShapeMNK,
cutlass::epilogue::collective::EpilogueTileAuto,
ElementAcc, ElementCompute,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::half_t, cutlass::layout::TensorKCS, 8,
cutlass::epilogue::NoSmemWarpSpecialized
>::CollectiveOp;
using CollectiveMainloop = typename cutlass::conv::collective::CollectiveBuilder<
cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp,
cutlass::conv::Operator::kWgrad,
ElementAcc, cutlass::layout::TensorNWC, 8,
ElementFlt, cutlass::layout::TensorNWC, 8,
ElementAcc,
TileShapeMNK, ClusterShapeMNK,
cutlass::conv::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
cutlass::conv::collective::KernelScheduleAuto
>::CollectiveOp;
using ConvKernel = cutlass::conv::kernel::ConvUniversal<
CollectiveMainloop,
CollectiveEpilogue
>;
using Conv = cutlass::conv::device::ConvUniversalAdapter<ConvKernel>;
EXPECT_TRUE(test::conv::device::TestAllConv<Conv>());
}
#endif // defined(CUTLASS_ARCH_MMA_SM90_SUPPORTED)