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[rocm-libraries] ROCm/rocm-libraries#4797 (commit 1a30400)

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[CK_TILE] Add CK Tile bwd weight profiler
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## Motivation

To compare old CK and CK Tile, we need to extend the current CK profiler
to support running also CK Tile instance with the same API. In order to
have the same instance coverage in CK Tile compared to the old CK, I've
added code generation from old CK configurations to CK Tile instances
using the CK Builder.

## Technical Details

- The codegen python script for CK Tile fwd convs is extended to support
also bwd weight and bwd data.
- The generated instances are added to the CMake build (target
`device_grouped_conv_bwd_weight_tile_instance`s).
- A new profiler op (`grouped_conv_bwd_weight_tile`) has been added to
the CK Profiler.
This commit is contained in:
Ville Pietilä
2026-03-04 21:50:29 +00:00
committed by assistant-librarian[bot]
parent fc1e1a5155
commit ae4e632c7d
68 changed files with 5194 additions and 196 deletions
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4
experimental/grouped_convolution_tile_instances/instances/grouped_convolution_forward_tile.cpp.in → experimental/grouped_convolution_tile_instances/instances/grouped_convolution_tile.cpp.in
View File

@@ -1,6 +1,6 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "../instance_includes.inc"
#include "../../instance_includes.inc"
namespace ck_tile::builder::profiling {
constexpr auto SIGNATURE = gen_signature;
std::tuple<bool, float, std::string> run_gen_instance_name(const ckt::Args<SIGNATURE>& args,
@@ -14,6 +14,6 @@ std::tuple<bool, float, std::string> run_gen_instance_name(const ckt::Args<SIGNA
.with_tile_block_gemm(gen_block_gemm_desc)
.with_tile_transfer(gen_block_transfer)
.with_tile_optimizations(gen_optimizations);
#include "../instance_run.inc"
#include "../../instance_run.inc"
}
} // namespace ck_tile::builder::profiling

111
experimental/grouped_convolution_tile_instances/instances/instance_includes.inc
View File

@@ -1,5 +1,6 @@
#include "../../builder/test/utils/ckb_conv_tile_test_configs.hpp"
#include "ck_tile/builder/testing/conv/fwd.hpp"
#include "ck_tile/builder/testing/conv/bwd_weight.hpp"
#include "ck_tile/builder/testing/conv/ck_tile.hpp"
namespace ckb = ck_tile::builder;
@@ -62,4 +63,114 @@ constexpr auto SIGNATURE_NDHWGC_FP16_FWD =
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
// Backward Weight Signatures
constexpr auto SIGNATURE_NHWGC_FP32_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_BF16_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_FP16_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP32_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_BF16_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP16_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
// Backward Data Signatures
constexpr auto SIGNATURE_NHWGC_FP32_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_BF16_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_FP16_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP32_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_BF16_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP16_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
} // namespace ck_tile::builder::profiling