Commit Graph

7 Commits

Author SHA1 Message Date
Johannes Graner
58475d3f45 [rocm-libraries] ROCm/rocm-libraries#5393 (commit d51b649)
[CK Tile] StreamK support for Bwd Weight grouped convolutions
 (#5393)

## Motivation

Add StreamK work distribution to the CK Tile grouped convolution
backward weight kernel. Split-K divides the K-dimension uniformly across
a fixed `k_batch`, which causes load imbalance when the number of output
tiles doesn't evenly fill the GPU. StreamK distributes total
K-iterations evenly across workgroups, improving utilization on these
shapes.

## Technical Details

StreamK is added as an `if constexpr` branch in the existing kernel,
selected by the `TilePartitioner_` template parameter. Two reduction
strategies are supported:
- **Linear**: tile-starter sequentially accumulates partials from
contributing CTAs
- **Tree**: pairwise binary tree reduction (O(log n) depth, faster for
many contributors)

Both persistent and non-persistent data-parallel (DP) sections are
supported.

Key changes:
- `grouped_convolution_backward_weight_kernel.hpp`: StreamK execution
path with `RunStreamK`/`RunStreamKLoop`, partial store/load via
workspace, flag-based cross-CTA synchronization,
`GridSize`/`MakeKernelArgs`/`GetWorkSpaceSize` extensions
- `streamk_common.hpp`: Shared `StreamKReductionOps` (reduction helpers)
and `StreamKDispatch` (persistent/non-persistent DP dispatch), used by
both GEMM and Conv StreamK kernels
- `streamk_gemm_kernel.hpp`: Refactored to use shared helpers
- Merged split-K and StreamK example invokers via `PartitionerPolicy`
template parameter
- StreamK example binary with `--streamk_reduction=linear|tree` and
`--streamk_persistent=0|1`
- CK Builder integration: `SpecifiesStreamK` concept,
`TilePartitionerType` factory helper, `InstanceTraits` with StreamK
fields
- 30 tests: host-side, GPU end-to-end (Linear + Tree + Persistent DP),
negative, builder regression

### Performance (MI355X, gfx950)

Speedup relative to best split-K (sweep over k_batch={1,2,4,8,16,32}):

| Shape | 16x64 tiles | | 128x128 tiles | |
|---|---|---|---|---|
| | Split-K | StreamK | Split-K | StreamK |
| 1x1 128x128 N=32 28x28 | 1.00x | 0.54x | 1.00x | 0.81x |
| 3x3 128x128 N=32 14x14 | 1.00x | 0.59x | 1.00x | 0.62x |
| 1x1 256x64 N=32 56x56 | 1.00x | 0.83x | 1.00x | 1.83x |
| 3x3 512x512 N=2 7x7 | 1.00x | 1.12x | 1.00x | 0.62x |
| 1x1 1024x1024 N=4 7x7 | 1.00x | 1.09x | 1.00x | 0.60x |
| 3x3 128x128 N=32 28x28 | 1.00x | 0.44x | 1.00x | 0.96x |
| 3x3 256x256 N=32 14x14 | 1.00x | 0.67x | 1.00x | 0.93x |
| 3x3 512x512 N=32 7x7 | 1.00x | 0.98x | 1.00x | 1.16x |

StreamK's value depends on tile config: with larger tiles (fewer output
tiles), StreamK delivers up to 1.83x speedup on bottleneck shapes and up
to 1.16x on typical large-channel convolutions. Tree reduction
consistently outperforms Linear when multiple CTAs contribute to the
same tile (up to 2.87x faster), due to O(log n) reduction depth vs O(n)
sequential accumulation. The table reports the best of Linear and Tree
for each shape.

## Test Plan

```bash
ninja -C build test_ck_tile_grouped_conv_bwd_weight_streamk
./build/bin/test_ck_tile_grouped_conv_bwd_weight_streamk

# Builder tests (requires CK_EXPERIMENTAL_BUILDER=ON)
ninja -C build check-builder
```

30 tests covering:
- Host-side: type traits, kernel args construction, grid size, workspace
size
- GPU end-to-end (Linear + Tree): small/medium shapes, multi-group,
stride>1, pure-DP degeneration, single-tile all-SK, large GemmK, higher
occupancy
- Persistent DP: Linear + Tree with persistent data-parallel dispatch
- Negative: `IsSupportedArgument` rejects unaligned K and C
- Builder: Create (instance string validation) + Execution (reference
comparison) + instance string regression

## Test Result

All 30 conv StreamK tests pass on MI355X (gfx950). 64/64 GEMM StreamK
tests pass. Full `check-builder` suite passes. Tolerances computed
dynamically using `calculate_rtol_atol` pattern (fp16 ULP-aware).

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
2026-03-27 09:18:14 +00:00
Ville Pietilä
e2f5ab8000 [rocm-libraries] ROCm/rocm-libraries#5237 (commit ef10dc6)
[CK_TILE, CK_BUILDER] Add two-stage bwd weight kernels to CK
 Tile profiler (#5237)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

## Motivation

PR #4797 added CK Tile bwd weight kernels to the CK Profiler. The
two-stage kernels were not supported in the initial PR. This PR adds the
the missing bwd weight two-stage kernels to the CK Profiler.

## Technical Details

Extended the CK Tile conv builder factory to build also the elementwise
ops required for the two-stage kernels. Extended the CK Builder for CK
Tile instance to accept the two-stage flag as part of the algorithm
configuration.

## Test Plan

Added units tests for CK Builder that verify the two-stage kernel
construction.

## Test Result

If CI passes, the added unit tests are passing.

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
2026-03-13 01:21:08 +00:00
Robin Voetter
cc75948d1c [CK_BUILDER] conv bwd weight testing (#3618)
* ck-builder: restructure testing conv

In order to prepare for bwd of conv testing, this commit moves some
files and types around so that we can reuse ckt::Args for both forward
and backwards convolution.

* ck-builder: decouple fwd_ck.hpp and fwd_reference.hpp from fwd.hpp

This will allow us to more easily include fwd.hpp from backwards
definitions, which is required for initializing bwd values.

* ck-builder: fix layout of test_ckb_conv_bwd_weight_xdl_cshuffle_v3

Turns out that the supplied layout isn't actually supported...

* ck-builder: ck and reference conv integration for bwd weight

* ck-builder: ck bwd weight execution test

* ck-builder: ckt::run support for ck-tile bwd weight

* ck-builder: ck tile bwd weight execution test

* ck-builder: extra debug printing in MatchesReference

* ck-builder: make ckt::run return RunResult

This type is more convenient than std::tuple, as it will allow us to
use google test matchers with this in the future.

* ck-builder: RunResult matcher

Using EXPECT_THAT(..., SuccessfulRun()) will generate a check and a nice error
message about how and why running an algorithm failed.

* ck-builder: doc fixes

* ck-builder: add missing headers
2026-01-26 23:50:15 +01:00
Bartłomiej Kocot
0727e85e52 [CK_BUILDER] Add grouped conv fwd ck tile profiler (#3518)
* [BULDER] Add grouped conv fwd ck tile profiler

* [CK TILE] Fix grouped conv kernels splitk and double lds

* Updates

* Fixes

* Move to ckProfiler

* Fixes

* fix

* fix

* Change instances to empty list by default

* fix

* fix

* Update grouped_convolution_signatures.hpp

* Update grouped_convolution_forward_tile_algs.hpp

* [CK TILE] Add grouped convolution forward tests (#3556)

* [CK TILE] Add grouped convolution forward tests

* fix jenkins

* fixes

* comments fixes

* unit test

* unit test fix

* Move instances outside builder

* fix includes

* clang format fix

* readme fix

* fix includes

* fixes
2026-01-19 22:29:01 -07:00
Ville Pietilä
9908a87c31 [CK_BUILDER] Add bwd weight factories (#3509)
* Add placeholder test.

* Initial conv bwd weight factory.

* Conv builder test refactoring.

* Add missing pieces to bwd weight factory.

* Improve compile time erros message when no matching factory is found.

* Use amcro to ensure automatic macthing between concepts are their string representations.

* Improve compile time diagnostics.

* Small improvements.

* Improve missing member/wrong type compile-time errors.

* Improve compile time diagnostics.

* Concept bug fixes.

* Remove debug assert.

* Update algorithm signature diagnostics.

* Factory bug fixes.

* First functional version of bwd weight conv factory.

* Refactor handing of GEMM-K batch template parameter in conv bwd weight factory.

* Concept improvements.

* Improve concept diagnostics.

* Introduve a common size type for concepts.

* Update compiletime diagnostics to use the size type.

* Update conv specialization enum.

* Fix fwd conv builder tests.

* Fix smoke tests.

* Separate bwd weigth and bwd data tests into separate targets.

* Clean-up CK Tile builder tests.

* Add bwd weight XDL CShuffle V3 factory.

* Build conv bwd weigth v3 instances successfully.

* Add instance traits for DeviceGroupedConvBwdWeight_Xdl_CShuffleV3.

* Test fix.

* Add instance traits for bwd weight algorithms.

* Add unit tests for instance strings.

* Build new instance traits unit tests but exclude WMMA for now.

* Added factory for DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle.

* Conv bwd weight DL factory.

* Final implementation for bwd weight DL factory.

* Add test for creating DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle instance.

* Add factory for DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle

* Treat ref algorithm the same way as real algorithms in the dispatcher.

* Refactor large tensor support and WMMA configuration.

* Add factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffleV3.

* Update Readme.

* Fix WMMA bwd weight tests.

* Added factory and tests for DeviceGroupedConvBwdWeightTwoStage_Wmma_CShuffleV3.

* Factory and tests for DeviceGroupedConvBwdWeight_Wmma_CShuffle.

* Dispatching for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffle.

* Add factory for DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3

* Fix DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3 factory and  compute types for input and output tensor in bwd weigth convs.

* Fix fwd factories after refactoring.

* clang-format

* Move compile-time diagnostics to a separate branch.

* Fix ref algorithm dispatching.

* Fix smoke tests.

* clang-format

* Fix factory for regular WMMA conv bwd weight.

* Clarify builder Readme.

* Remove obsolete test file.

* Fix test after merge.

* clang-format

* Remove the C++26 extensions.

* Unify conv elementwise ops and layout definitions for fwd and bwd directions.

* Remove old layout and elementwise ops.

* Unify handling of conv tensor types between fwd and bwd directions.

* Unify block transfer for fwd and bwd directions. Rename ThreadSliceDim to ThreadClusterRank.

* Make BlockTransferDescriptor concept parametrized. Introduce a common TileTransferParameters concept for conv algorithms.

* clang-format

---------

Co-authored-by: Ville Pietilä <>
2026-01-13 18:12:38 +02:00
Max Podkorytov
e339101e9c [CK-Tile] move out memory operation from cshuffle epilogue class (#3359)
* initial poc

* factor out common parts in operator()

* cv4

* rest of the universal gemm pipelines

* fix test

* remove boilerplate from tile engine

* fix example

* fix example

* format

* fix tests build for gemm

* remove base pipeline codegen from gemm instance builder

* unify v3 logic with the rest of universal gemm pipelines

* fix build for multi abd test

* fix test gemm multi d

* fix build for weight preshuffle

* fix grouped gemm test

* fix grouped gemm multi d test

* fix grouped gemm preshuffle

* fix grouped gemm example except for quant

* fix gemm preshuffle

* fix splitk 2 stage example

* fix batched gemm example

* fix multid example

* fix multiabd example

* fix batched gemm test

* fixup

* fix examples build

* fix grouped gemm test build

* fix smoke builder

* hacky poc

* fix tile engine

* kill the lambda

* maybe fix test build

* more fixes

* clang-format

* save temp

* clang-format

* mostly fix examples

* clang-format

* remove dead code

* more cleanup

* fix fmha bwd build (default epilogue set/add appears to be broken)

* fix default epilogue tests but not correctness

* clang-format

* fix bquant

* clang-format

* cleanup dead code

* rearrange make windows for readability

* restore changes to IsSupportedArgument

* fix smoke-builder

* clang-format

* fixup rename class

* build fixes

* clang-format

* fix builder

* fixup

* remove set from builder tests

* fix test

* clang-format

* re-refactor the kernels

* clang-format

* fix header license

* remove memory operation from conv bwd test

* clang-format

* clang-format example,include

* clang-format test

* build fixes

* clang-format

* solve compilation error

* fix the CI

* solve compilation error

* clang format

* solve merge conflict

* solve merge conflict

* solve the gfx11 error

* solve test error

* moar build fixes

* remove AtomicAddRequiresKBatchGreaterThanOne test since the property is removed from the kernel scope

---------

Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
2026-01-04 03:28:14 -08:00
Bartłomiej Kocot
04612c30ce [CK_BUILDER] Ck Tile Grouped convolution factory (#3352)
* [BUILDER] Ck Tile Grouped convolution factory

* Part 2

* Fixes after rebase

* Remove leftovers
2025-12-08 10:32:56 +01:00