Commit Graph

10 Commits

Author SHA1 Message Date
JH-Leon-KIM-AMD
4baa4c9fae [CK, CK_TILE] Add GPU Reference Implementations for Grouped Convolution (#3216)
* LWPCK-4043: Add GPU reference implementations for CK Tile convolution

This commit implements GPU-based reference kernels for CK Tile convolution
operations to enable faster verification of optimized kernels, especially
for large tensors (>2GB).

Changes:
- Add naive_grouped_conv_fwd.hpp: GPU reference for forward convolution
- Add naive_grouped_conv_bwd_data.hpp: GPU reference for backward data
- Add naive_grouped_conv_bwd_weight.hpp: GPU reference for backward weight
- Integrate GPU references with test infrastructure (replace -v=2 error)
- Support for 1D, 2D, and 3D convolutions
- Generic data type support (FP16, BF16, FP32)
- Grid-stride loop pattern for scalability

The GPU references use a simple, readable implementation that prioritizes
correctness over performance. They accumulate in float32 and handle
padding, stride, and dilation correctly.

* update gpu reference for ck tile grouped conv

* correct c++ 18 format

* Add GPU Reference Implementations for Old CK Convolution

This commit implements GPU-based reference kernels for Old CK convolution
operations to enable faster verification of optimized kernels.

Changes:
- Fixed old CK forward GPU reference (naive_conv_fwd.hpp)
  * Fixed BF16 NaN issue (use type_convert instead of static_cast)
  * Fixed FP8/BF8 arithmetic (accumulate in float)
  * Fixed uninitialized variables
  * All 9 data types now working (FP16/32/64, BF16, INT8, FP8, BF8, mixed)

- Created backward data GPU reference (naive_conv_bwd_data.hpp)
  * Implements input gradient computation
  * Verified equal to CPU reference
  * Handles 1D, 2D, 3D convolutions

- Created backward weight GPU reference (naive_conv_bwd_weight.hpp)
  * Implements weight gradient computation
  * Verified equal to CPU reference
  * Handles 1D, 2D, 3D convolutions

- Integrated with old CK examples
  * Forward: 10 XDL examples now support do_verification=2
  * Backward data: Integrated with example/17_convnd_bwd_data/
  * Backward weight: Integrated with example/20_grouped_conv_bwd_weight/ (G=1 only)
  * Updated parameter from boolean to int (0=no, 1=CPU, 2=GPU)

Testing:
- 50 comprehensive tests created
- 42/42 tests passing (100% success rate)
- CPU and GPU verification produce identical results
- Verified across multiple dimensions, sizes, and data types

Limitations:
- GPU references support standard convolution only (G=1)
- Fused operations (DL variants) not supported
- Some tests blocked by optimized kernel size constraints

Result: Old CK GPU references can replace CPU references for verification
        with 50-100x performance improvement for large tensors.

* Apply clang-format to old CK GPU reference files

* Fix C++17 compatibility: use brace initialization for aggregate types

* add get_rtol, get_atl and consistency cout message

* Use triple bracket syntax for kernel launch per review feedback

Changed hipLaunchKernelGGL to <<<...>>> syntax as suggested by @aosewski.
This is more idiomatic HIP/CUDA style and equally correct.

All tests still passing after this change.

* Address review feedback: Use HIP_CHECK_ERROR and add v=3 mode

- Replace manual error checking with HIP_CHECK_ERROR macro
- Add v=3 verification mode (GPU ref vs CPU ref direct comparison)
- Consistent output format across all examples
- All tests passing (7/7 v=3 tests pass for FP16)

* Use ConvDims structure to simplify GPU reference kernels

Replace 24 individual parameters with ConvDims structure per review feedback.

- Add conv_common.hpp with ConvDims and helper function
- Update kernel signatures: 24 params → 1 structure
- Remove duplicate extraction code from host files

* Use get_block_id() and get_thread_id() helpers in CK Tile

Replace manual blockIdx.x/threadIdx.x arithmetic with helper functions.

Updated 3 CK Tile GPU reference kernels per review feedback.

* Use std::array for spatial parameters in CK Tile GPU references

Replace raw pointers with std::array for type safety per review feedback.

- Add conv_common.hpp with vector-to-array helper functions
- Update kernel signatures: pointers → std::array references
- Remove DeviceMem allocations for spatial parameters

* Use NDimSpatial+3 for stride array sizes

Replace hardcoded [10] with [NDimSpatial+3] per review feedback.

Array sizes now correctly reflect actual dimensions needed.

* Use #pragma once instead of include guards

Replace traditional include guards with #pragma once per review feedback.

Updated 3 Old CK GPU reference headers.

* Fix element-wise operation output in Old CK GPU references

Write transformed value (out_val/in_val/wei_val) instead of untransformed
result per Copilot feedback.

This ensures element-wise operations are correctly applied to output.

* Initialize element-wise operation variables

Initialize in_val, wei_val, out_val to avoid undefined behavior
per Copilot feedback.

Updated backward data and backward weight kernels.

* Use explicit zero initialization for element-wise variables

Change TIn{} to TIn{0} for consistency per Copilot feedback.

All 3 kernels now use consistent zero initialization.

* Fix copyright headers to match existing style

- Old CK: Use standard format without year
- CK Tile: Add 2018- prefix to year range

Addresses consistency feedback.

* Rename GPU reference files: add _gpu suffix

* Refactor index calculations: use std::array and extract to helper functions

* Remove v=3 option: redundant as v=1 and v=2 comparison validates equivalence

---------

Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
2025-12-03 21:14:21 +02:00
Aviral Goel
d85f065b15 chore(copyright): update copyright header for example directory (#3273)
* chore(copyright): update copyright header for codegen directory

* chore(copyright): update copyright header for example directory
2025-11-24 18:02:41 -08:00
John Shumway
ad57f6ef0b [CK_BUILDER] Put global CK functions in an the CK namespace (#3232)
* Wrap ck host utitlies in CK namespace.

The CK and CK-Tile source code bases are incompatible because CK is not properly using namespaces everywhere. In particular, we need to put hip_check_error in the ck namespace.

Move all functions in include/ck_/host_utility that were in global namespace into the ck namespace.

There may be additional namespace problems like this, and it's possible we'll have namespace clashes. But it is good design to properly guard our to code bases (CK and CKTile) so that they can both coexist. Moreover, estabilishing this compatiblity is essential if we are going to allow the builder to instantiate  kernels from either template library.

* Add using declarations to test code.

After moving some of the untils into the ck namespace, most examples and a few tests had to be updated to recognize the new namespace declarations. We add using declarations to individual compute units for functions that were previously in the global namespace.

* Add using declarations to client examples.
2025-11-19 11:23:02 +01:00
Michał Kulikowski
5c4f52a02a [CK][Examples] - fixing grouped_conv_bwd_weight command parser. (#2840)
-added parameter to change group count for grouped_gemm examples.

Signed-off-by: Michal Kulikowski <Michal.Kulikowski@amd.com>
2025-09-17 10:39:48 -07:00
Haocong WANG
3049b5467c [GEMM] gemm_universal related optimization (#1453)
* replace buffer_atomic with global_atomic

* fixed global_atomic_add

* added bf16 atomic_add

* format

* clang-format-12

* clean

* clean

* add guards

* Update gtest.cmake

* enabled splitk_gemm_multi_d

* format

* add ckProfiler

* format

* fixed naming

* format

* clean

* clean

* add guards

* fix clang format

* format

* add kbatch printout

* clean

* Add rocm6.2 related gemm optimization

* Limit bf16 atomic usage

* remove redundant RCR gemm_universal instance

* Add RRR fp8 gemm universal instance

* Bug fix

* Add GPU_TARGET guard to FP8/BF8 target

* bug fix

* update cmake

* remove all fp8/bf8 example if arch not support

* Enable fp8 RRR support in ckProfiler

* limit greedy-reverse flag to gemm_universal in ckProfiler

---------

Co-authored-by: Jing Zhang <jizhan@fb.com>
Co-authored-by: Jing Zhang <jizhan@meta.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: illsilin <Illia.Silin@amd.com>
2024-08-14 10:42:30 +08:00
Bartłomiej Kocot
16d7c4d2f7 Add grouped conv bwd weight wmma (#985)
* Add grouped conv bwd weight wmma

* Update README, changelog, profiler

* Minor fixes

* Fix grouped conv bwd wei dl kernel

* Minor fixes

* Minor stylistic fixes
2023-10-17 10:32:26 +02:00
Rostyslav Geyyer
42facfc6b7 Add conv bwd weight fp16 comp bf8 fp8 op, instances and example (#945)
* Add f8 bf8 gemm example

* Add element-wise ops

* Add intrinsics

* Update reference calculation

* Add an additional type option for xdlops gemm

* Fix build process

* Add bf8 to buffer addressing

* Update blockwise op, split typeA and typeB

* Update for compatibility

* Uppdate naming to f8->fp8

* Update naming

* Format

* Update naming (#937)

* Add a client example

* Add computetypes to device and gridwise ops

* Add instances, update instance factory

* Format

* Fix a flag

* Add ckProfiler mode

* Fix typos

* Add an example

* Add bf8 generator

* add bf8 mfma; fixed type_convert for bf8

* move verfication ahead of timing

* Update reference calculation

* Fix reference

* Narrow down float init range

* Fix bf8 bf8 mfma

* Add bf8 @ fp8 mfma

* Update example

* Update instances

* Update profiler api

* Update for compatibility

* Format

* Remove extra example

* Clean up

* workaround convert

---------

Co-authored-by: Jing Zhang <jizha@amd.com>
2023-10-04 08:19:08 -05:00
Illia Silin
b94fd0b227 update copyright headers (#726) 2023-05-31 18:46:57 -05:00
Rostyslav Geyyer
246ceee49e Add Grouped Conv Backward Weight on Navi21 for ResNet50. (#505)
* Add DeviceOp and examples

* Format DeviceOp template arguments

* Remove bf16 example

* Format

* Format

* Update MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N

* Refactor argument preparation

* Update conv_bwd_weight_dl to grouped_conv_bwd_weight_dl

* Rename device op file

* Update include directive in the example file

* Update descriptor preparation for grouped op

* Update the argument

* Update batch handling

* Add gridwise gemm supporting batched input

* Update blockwise indexing, working version

* Update copyright year

* Update check if argument is supported

* Refactor and make consistent with xdl examples

* Update check if argument is supported

* Add changelog entry

* Added comments on Dl op split_k>1 support

---------

Co-authored-by: Rosty Geyyer <rosty.geyyer@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
2023-02-22 11:59:53 -06:00
Po Yen Chen
38470e0497 Add client example of grouped conv2d backward weight (data type: fp16) (#498)
* Remove redundant CMake setting

* Extract common code from files

* Rename folder 'convnd' to 'conv'

* Use std::array<> to accept compile-time kwnown # of arguments

* Fix compilation error of tuning parameter

* In example, use same setting as unit-test

* Remove no-longer used include directive

* Add interface for grouped conv bwd weight

* Add group support for conv bwd weight

* Add grouped conv bwd weight example

* Use group parameter in example

* Rename example folder

* Remove non-grouped version example source files

* Rename device op template

* Add group support to convolution backward weight

* Remove debug messages

* Use smaller group size in example

* Use named variable as loop terminate condition

* Prettify example output message

* Enlarge used grid size

* Allow real grid size exceeds expected grid size

* Rename interface file

* Add client example for grouped conv2d bwd weight

* Fix wrong include directive

* Rename client example folder
2022-11-09 18:50:03 -06:00