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cutlass/test/unit/gemm/warp/gemm_mixed_input_sm80.cu
Manish Gupta 7d8317a63e
Support for Mixed Input TensorOp (#1084) 
* Passing warp-level mixed input F16*(S8/U8) tests

* passing device-level mixed input F16*(S8/U8) tests

* add to profiler - I8 (111 TFLOPs), U (123 TFLOPs)

* fast numeric conversions (I8 = 132 TFLOPs, U8 = 148 TFLOPs)

* Speedup reference compilation (REVERT THIS COMMIT)

* wider_add.u32_packed_sub.f16x2 (I8 = 132TFLOP/s, U8 = 170 TFLOP/s)

* Improve s8->f16 cvt and support bf16*u8 @158 TFLOPs

* BF16 * S8 (142 TFLOPs)

* Handle mixed-input upcast on OperandA (Support [S8|U8]*[F16|BF16]

* rename OpMultiplyAddMixedInput to OpMultiplyAddMixedInputUpcast

* Add device-level test and profiler support for upcast on operand A

* Move shfl before the cvt and reduce #shfls by 1/2

* fix smem_usage calculation for mixed_input types

* uncomment the stuff (getting ready for merge)

* profiler changes and mixed-input reference

* mixed input reference are in a new file

* use platform instead of std

* comments and typo only

* Use CreateGemmOperator and delete CreateMixedInputGemmOperator

* copyright for new files

* rebase follow-up
2023-09-27 11:18:30 -04:00

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/***************************************************************************************************
* Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
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* contributors may be used to endorse or promote products derived from
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/*! \file
\brief Unit tests for thread-level GEMM
*/
#include "../../common/cutlass_unit_test.h"
#include "cutlass/aligned_buffer.h"
#include "cutlass/half.h"
#include "cutlass/gemm/warp/default_mma_tensor_op.h"
#include "cutlass/core_io.h"
#include "cutlass/util/host_tensor.h"
#include "cutlass/util/tensor_view_io.h"
#include "cutlass/util/reference/host/tensor_fill.h"
#include "cutlass/util/reference/host/tensor_compare.h"
#include "cutlass/util/reference/host/gemm.h"
#include "testbed.h"
#if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)
////////////////////////////////////////////////////////////////////////////////
/// F32 <= F16 * I8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_i8, 128x128x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::half_t;
using ElementB = int8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<128, 128, 64> >()
.run();
}
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_i8, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::half_t;
using ElementB = int8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= I8 * F16 + F32 (Upcast on Operand A)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_f16, 128x128x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = int8_t;
using ElementB = cutlass::half_t;;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<128, 128, 64> >()
.run();
}
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_f16, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = int8_t;
using ElementB = cutlass::half_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= F16 * U8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_u8, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::half_t;
using ElementB = uint8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_f16_u8, 128x128x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::half_t;
using ElementB = uint8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<128, 128, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= U8 * F16 + F32 (Upcast on Operand A)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_f16, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = uint8_t;
using ElementB = cutlass::half_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_f16, 128x128x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = uint8_t;
using ElementB = cutlass::half_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<128, 128, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= B16 * U8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_bf16_u8, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::bfloat16_t;
using ElementB = uint8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= B16 * U8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_u8_bf16, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = uint8_t;
using ElementB = cutlass::bfloat16_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= B16 * I8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_bf16_i8, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = cutlass::bfloat16_t;
using ElementB = int8_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
////////////////////////////////////////////////////////////////////////////////
/// F32 <= B16 * I8 + F32 (Upcast on Operand B)
////////////////////////////////////////////////////////////////////////////////
TEST(SM80_warp_gemm_mixed_input_tensor_op_crosswise_i8_bf16, 64x64x64_64x64x64_16x8x16) {
using Shape = cutlass::gemm::GemmShape<64, 64, 64>;
using InstructionShape = cutlass::gemm::GemmShape<16, 8, 16>;
using ElementA = int8_t;
using ElementB = cutlass::bfloat16_t;
using ElementC = float;
using LayoutA = cutlass::layout::RowMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementA>::value, 64>;
using LayoutB = cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise<
cutlass::sizeof_bits<ElementB>::value, 64>;
using MmaTensorOp = typename cutlass::gemm::warp::DefaultMmaTensorOp<
Shape, InstructionShape, ElementA, LayoutA, ElementB, LayoutB, ElementC,
cutlass::layout::RowMajor, cutlass::arch::OpMultiplyAddMixedInputUpcast>::Type;
test::gemm::warp::TransformTestbed<MmaTensorOp,
cutlass::gemm::GemmShape<64, 64, 64> >()
.run();
}
#endif // if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)
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