mirror of
https://github.com/ROCm/composable_kernel.git
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Add fp16/fp8 support into Grouped gemm FixedNK (#874)
* move all arguments into device * add b2c_tile_map * add examples * add SetDeviceKernelArgs * dedicated fixed_nk solution * init client api * add grouped_gemm_bias example * add a instance * add instances * formatting * fixed cmake * Update EnableCompilerWarnings.cmake * Update cmake-ck-dev.sh * clean; fixed comments * fixed comment * add instances for fp32 output * add instances for fp32 output * add fp32 out client example * fixed CI * init commit for kbatch * add splitk gridwise * format * fixed * clean deviceop * clean code * finish splitk * fixed instances * change m_loops to tile_loops * add setkbatch * clean code * add splitK+bias * add instances * opt mk_nk instances * clean examples * fixed CI * remove zero * finished non-zero * clean * clean code * optimized global_barrier * fixed ci * fixed CI * instance and client * removed AddBias * format * fixed CI * fixed CI * move 20_grouped_gemm to 21_grouped_gemm * clean * formatting * clean * clean * fixed computeType --------- Co-authored-by: Jing Zhang <jizha@amd.com>
This commit is contained in:
zjing14
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <vector>
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#include <memory>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_grouped_gemm_fixed_nk.hpp"
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#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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namespace instance {
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// fp16_output
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void add_device_grouped_gemm_xdl_fixed_nk_f16_f16_f16_mk_kn_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Row,
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Empty_Tuple,
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Row,
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F16,
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F16,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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void add_device_grouped_gemm_xdl_fixed_nk_f16_f16_f16_mk_nk_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Col,
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Empty_Tuple,
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Row,
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F16,
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F16,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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// fp8_inputB
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void add_device_grouped_gemm_xdl_fixed_nk_f16_f8_f16_mk_kn_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Row,
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Empty_Tuple,
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Row,
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F16,
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F8,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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void add_device_grouped_gemm_xdl_fixed_nk_f16_f8_f16_mk_nk_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Col,
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Empty_Tuple,
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Row,
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F16,
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F8,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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// i8_inputB
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void add_device_grouped_gemm_xdl_fixed_nk_f16_i8_f16_mk_kn_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Row,
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Empty_Tuple,
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Row,
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F16,
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I8,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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void add_device_grouped_gemm_xdl_fixed_nk_f16_i8_f16_mk_nk_mn_instances(
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std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
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Col,
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Empty_Tuple,
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Row,
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F16,
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I8,
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Empty_Tuple,
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F16,
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PassThrough,
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PassThrough,
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PassThrough>>>& instances);
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template <typename ALayout,
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typename BLayout,
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typename ELayout,
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typename ADataType,
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typename BDataType,
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typename EDataType>
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struct DeviceOperationInstanceFactory<
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ck::tensor_operation::device::DeviceGroupedGemmFixedNK<ALayout,
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BLayout,
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Empty_Tuple,
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ELayout,
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ADataType,
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BDataType,
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Empty_Tuple,
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EDataType,
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PassThrough,
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PassThrough,
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PassThrough>>
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{
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using DeviceOp = DeviceGroupedGemmFixedNK<ALayout,
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BLayout,
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Empty_Tuple,
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ELayout,
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ADataType,
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BDataType,
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Empty_Tuple,
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EDataType,
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PassThrough,
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PassThrough,
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PassThrough>;
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static auto GetInstances()
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{
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std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
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// fp16_output
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if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
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is_same_v<EDataType, half_t>)
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{
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
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}
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
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}
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}
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// fp8_input
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if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> &&
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is_same_v<EDataType, half_t>)
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{
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_f8_f16_mk_kn_mn_instances(op_ptrs);
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}
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_f8_f16_mk_nk_mn_instances(op_ptrs);
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}
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}
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// i8_input
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if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, int8_t> &&
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is_same_v<EDataType, half_t>)
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{
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_i8_f16_mk_kn_mn_instances(op_ptrs);
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}
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if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
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is_same_v<ELayout, Row>)
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{
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add_device_grouped_gemm_xdl_fixed_nk_f16_i8_f16_mk_nk_mn_instances(op_ptrs);
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}
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}
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return op_ptrs;
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}
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};
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} // namespace instance
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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