[CK] Remove Stream-K from old CK
## Motivation
Since Stream-K has a CK Tile implementation, we no longer need Stream-K
in old CK. Hence, this PR removes Stream-K from old CK.
## Technical Details
All Stream-K artifacts in old CK have been removed including examples,
tests, kernels, and CK profiler artifacts.
## Test Plan
Ran a CI run on the branch before publishing PR.
## Test Result
All tests passed.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
Co-authored-by: Claude Sonnet 4 <noreply@anthropic.com>
[CK] Grouped Convolution Global Load/Store instances
## Motivation
Support global load and store in grouped convolutions using instance
factory.
## Technical Details
- add new instances for each direction
- add new tests for large cases
## Test Plan
New test for large cases
## Test Result
pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-1255
[ck] Enforce ASCII-only C/C++ sources for hipRTC
compatibility (#7829)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
## Summary
CK source files must be compilable via **hipRTC (HIP runtime
compilation)**, whose preprocessor does not accept non-ASCII bytes
anywhere in a translation unit — **including in comments**. Bytes that
are harmless under `hipcc` (em-dashes, smart quotes, multiplication
signs, Greek letters, box-drawing glyphs, etc.) cause hipRTC to fail at
preprocessing time. These regularly leak in via LLM-assisted authoring
or copy/paste from formatted documents and silently break hipRTC paths
that are not exercised by the default `hipcc`-based build matrix.
This PR (a) cleans every existing violation (53 files) and (b) adds a
pre-checkin gate so new violations are rejected before merge.
## File extensions covered
Both the cleanup scan and the new Jenkins enforcement stage use the same
predicate:
```
*.h *.hpp *.cpp *.h.in *.hpp.in *.cpp.in *.inc *.cl
```
(excluding `*/build/*` and `*/include/rapidjson/*`). This is a strict
superset of the existing `Clang Format` stage's predicate — `*.inc` is
added so test-fixture include files are also gated. The local pre-commit
hook's `c++/inc` type filter covers the same set.
## Why no enforcement today
CK is opted out of the rocm-libraries root `.pre-commit-config.yaml`, so
the existing `pre-commit` workflow doesn't touch CK. The local CK
`.pre-commit-config.yaml` only runs for developers who installed hooks.
The **authoritative gate is therefore the new Jenkins stage** in this
PR; the local hook is convenience.
## Commit layout (bisect-friendly)
1. `79798aa6261` — **`[ck] Convert reflect/ rendering to ASCII for
hipRTC compatibility`**
Behavior change, isolated. `TreeFormatter` swaps `├─ / └─ / │ ` for `|-
/ +- / | ` (3-col width preserved so alignment is unchanged).
`conv_description.hpp` swaps `×` for `x` as the dimension separator.
`test_conv_description.cpp` expected strings updated in lockstep so the
snapshot test stays green. This is the only commit in the series with
observable runtime impact.
2. `738fdb0d81c` — **`[ck] Strip non-ASCII bytes from C++ sources for
hipRTC compatibility`**
Mechanical text cleanup across 53 files. Replacements happen in comments
or in `std::cout` strings that are not asserted on by any test. None of
the 174 `.inc` files in the tree required edits, but they were in the
scan's predicate so the enforcement stage's predicate is a superset of
what was scanned. Full replacement table in the commit message.
3. `1d7cd8ba235` — **`[ck] Enforce ASCII-only C/C++ sources for hipRTC
compatibility`**
- New `projects/composablekernel/script/check_ascii_only.sh` (modeled on
`check_copyright_year.sh`).
- New entry in `projects/composablekernel/.pre-commit-config.yaml` under
the local-hooks block (`types_or: [c++, inc]`).
- New `ASCII Only Check` parallel stage in
`projects/composablekernel/Jenkinsfile`'s `Static checks` block,
mirroring the existing `Clang Format` stage but with `*.inc` added to
the find predicate. Always-on, no `RUN_CPPCHECK` gate.
The tree is buildable at every commit boundary. Commit 1 leaves 50 known
violations; commit 2 leaves 0; commit 3 wires the gate.
## Demo
Script output on a synthesized violation:
```
$ printf '// em-dash test \xe2\x80\x94 here\n' > /tmp/bad.cpp
$ projects/composablekernel/script/check_ascii_only.sh /tmp/bad.cpp
ERROR: /tmp/bad.cpp contains non-ASCII bytes:
1:// em-dash test — here
Fix: replace with ASCII (em-dash -> --, smart quotes -> ", arrows -> ->, etc.)
$ echo $?
1
```
Full repo scan after the cleanup commits (note the `-name '*.inc'`
clause):
```
$ cd projects/composablekernel && find . -type f \( -name '*.h' -o -name '*.hpp' -o -name '*.cpp' \
-o -name '*.h.in' -o -name '*.hpp.in' -o -name '*.cpp.in' -o -name '*.inc' -o -name '*.cl' \) \
-not -path '*/build/*' -not -path '*/include/rapidjson/*' -print0 \
| xargs -0 -P 8 -n 64 script/check_ascii_only.sh
$ echo $?
0
```
## Test plan
- [ ] Jenkins PR build: confirm new `Static checks -> ASCII Only Check`
stage runs green over the full predicate (incl. `*.inc`) and existing
`Clang Format` stage is unaffected.
- [ ] `test_conv_description` passes against the ASCII tree-formatter
output (touched in commit 1).
- [ ] Local: `pre-commit run ascii-only-checker --all-files` runs
cleanly after installing CK pre-commit hooks via
`script/install_precommit.sh`.
- [ ] Manually inject a non-ASCII byte in any `.cpp/.hpp/.inc` file,
push: confirm Jenkins fails the new stage with a clear error.
- [ ] Spot-check a representative subset of touched files under hipRTC
compilation to confirm no remaining hipRTC-blocking content (optional,
since the static byte check is a sufficient condition for hipRTC
preprocessor acceptance on this dimension).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
[CK] suppress compiler warnings while building pytorch. (#7760)
## Motivation
Recently added compiler flags that are required to suppress false
warnings by latest staging compiler are not recognized by older compiler
versions and are triggering an avalanche of warnings. Previous attempt
to suppress them by using -Wno-unknown-warning-option flag didn't help,
because that flag wasn't recognized either and just added more warnings.
I've verified that current approach by checking the clang version
actually works as intended and makes the warnings go away.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK] Fix grouped conv bwd data stride>1 silent miscompute (ALMIOPEN-1959) (#7732)
## Motivation
Fix silent miscompute in the grouped convolution backward-data kernel
(`DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1`) when stride >
dilation (ALMIOPEN-1959). PR #6208 introduced a flat-descriptor fast
path that dropped all but the first sub-GEMM, producing zeroed slices of
`dx` on
the (G=1, stride>1, 2D, NumDTensor=0) intersection. Restore correctness
without giving up the perf gains PR #6208 delivered on stride=1 shapes.
## Technical Details
- Tighten the flat-descriptor fast-path gate to require
`arg.gemms_count_ == 1` (i.e. a single sub-GEMM per dispatch — its
original purpose). For stride > 1, the implicit GEMM is split into
`gemms_count_` sub-GEMMs whose output cells tile `dx` disjointly;
routing them through the flat path required dropping all but the first,
which was the source of the bug.
- Stride > 1 now falls through to the existing grouped CShuffle path,
which packs all sub-GEMMs into one descriptor array and walks them
on-device in a single kernel launch. This is the pre-PR-6208 production
path; correctness is established and per-dispatch launch count is
minimised.
- Add regression coverage for the (G=1, stride>1, 2D, NumDTensor=0)
intersection in
`test/grouped_convnd_bwd_data/test_grouped_convnd_bwd_data.cpp` with
`gemms_count` ∈ {4, 9, 36}. Pre-existing cases did not hit this
intersection (all stride>1 cases used G=2; all G=1 cases used stride=1),
which is why PR #6208's regression slipped past CI.
## Test Plan
- `ctest -L SMOKE_TEST -R 'grouped_convnd_bwd_data'` on gfx942 (smoke
tier — runs on every PR via `smart_build_and_test.sh`).
- End-to-end verify (`verify=1`) via
`example_grouped_conv_bwd_data_xdl_fp16` on stride 1/2/3/6 shapes
including the original ALMIOPEN-1959 case and a cross-bucket
(`gemms_count=36`) case spanning two `MaxGroupedGemmGroupsNum=32`
buckets.
- ckProfiler A/B sweep on MI300X (gfx942) toggling the flat-path gate
via an environment variable: full kernel-family enumeration, winning
kernel + its avg_time reported under each gate. 33/41 shapes completed
before the sweep was stopped; the remaining 8 were the largest
i2v/synthetic shapes where ckProfiler exceeded its 300s per-shape
enumeration budget (not relevant to the verdict).
## Test Result
### Correctness
| Test | Result |
|---|:---:|
| `test_grouped_convnd_bwd_data` (12 type parameterizations × Test2D,
includes 3 new regression shapes) | **12/12 PASSED** in 14.18 s |
| `test_grouped_convnd_bwd_data_interface` (API checks) | **PASSED** in
0.28 s |
| ALMIOPEN-1959 stride=2 (`verify=1`) | **PASSED** |
| stride=1 K3 (`verify=1`) | **PASSED** |
| stride=3 K3 `gemms_count=9` (`verify=1`) | **PASSED** |
| stride=6 K6 `gemms_count=36` cross-bucket (`verify=1`) | **PASSED** |
### Performance (ckProfiler A/B on gfx942 / MI300X)
Comparing the **post-fix gate** (flat path only when `gemms_count_==1`,
column "B") vs the **inner-loop variant** that keeps the flat path on
stride>1 (column "A") across 25 stride>1 shapes where production picks
a `_v1` instance (so the gate actually fires):
| Stride | Shapes | A wins | Tie | B wins | Notes |
|:------:|:------:|:------:|:---:|:------:|---|
| 1 (sanity, gate moot) | 3 | 0 | 3 | 0 | gate doesn't differentiate — A
== B as expected |
| > 1 (gate fires) | 25 | **0** | 11 | **14** | B wins +6% to +32%; A
never wins |
Highlights from the firing-gate cases:
| Shape (G=1, stride=2 unless noted) | A ms | B ms | B vs A |
|---|---:|---:|---:|
| ALMIOPEN-1959 (N=16, K=256, C=128, 5×5, 40×175) | 0.183 | 0.171 | **B
+6%** |
| Retinanet-L61 (N=32, K=C=256, 3×3, 25×25) | 0.054 | 0.045 | **B +17%**
|
| i2v-010 (N=1, K=C=384, 3×3, 277×209) | 0.174 | 0.125 | **B +28%** |
| Synthetic 50×50 K3 N=32 K=C=256 | 0.131 | 0.088 | **B +32%** |
Why B wins everywhere the gate fires: for `gemms_count = N`, the flat
path needs N kernel launches (one per sub-GEMM), while the grouped path
loops over the same N sub-GEMMs on-device in 1 launch. The (N−1) ×
launch-tax is a structural disadvantage A can't recover from.
### Diff
| File | Lines |
|---|---:|
|
`include/.../device_grouped_conv_bwd_data_multiple_d_xdl_cshuffle_v1.hpp`
| +14 / −8 (one extra condition + expanded dispatch comment) |
| `test/.../test_grouped_convnd_bwd_data.cpp` | +9 / −0 (3 new shapes) |
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
Revert "[CK] Enable grouped conv bwd data to match non-grouped perf" (#7664)
## Motivation
Incorrect results has been introduced for some conv bwd cases.
## Technical Details
This reverts commit 33424f65346d6330d0fd94b5a4e6f843f24e52c3.
## Test Plan
CI
## Test Result
Pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
ALMIOPEN-1959
[CK] upgrade CI to rocm7.13 as default compiler (#7612)
## Motivation
Upgrade the default docker and compiler version in CI to rocm7.13.
In order to pass all the checks I had to also clean up a lot of
non-ascii characters in the source code comments and modify a couple of
tests that were affected by a new compiler logic.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Aviral Goel <aviral.goel@amd.com>
[CK] add composable kernel support on gfx1250 (#6978)
## Motivation
Add composable kernel support on gfx1250.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Qun Lin <qlin@amd.com>
Co-authored-by: jialuo12_amdeng <jia.luo@amd.com>
Co-authored-by: Andriy Roshchenko <andriy.roshchenko@amd.com>
Co-authored-by: hsivasun_amdeng <haresh.sivasuntharampillai@amd.com>
[CK] Suppress new staging compiler errors (#7384)
## Motivation
This should make new builds with staging compiler pass.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK] Fix latest batch of staging compiler warnings (#7111)
## Motivation
Suppress the new batch of clang lifetimebound and invalidation warnings
with the latest staging compiler.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_TILE] Grouped Convolution Backward Data Direct Load (#6624)
## Proposed changes
Add Grouped Convolution Backward Data with Direct Load into
DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffleV3 device implementation.
This enables direct global memory loading (bypassing LDS) for the
backward data convolution path on gfx950, following the same pattern
used in both backward weight and forward convolution.
Direct load convolution backward data improves performance by avoiding
LDS round-trips for certain configurations on gfx950, which supports a
wider range of instructions. Currently correctness is checked only at
usage point, but should be extended to a standalone UT in the future.
[CK] Fix/suppress clang lifetimebound warnings with staging compiler. (#6550)
## Motivation
New changes from upstream llvm-project cause an avalanche of warnings in
CK. Gonna disable them by ignoring the
lifetime-safety-intra-tu-suggestions flag until a better permanent
solution is found.
## Technical Details
<!-- Explain the changes along with any relevant GitHub links. -->
## Test Plan
<!-- Explain any relevant testing done to verify this PR. -->
## Test Result
<!-- Briefly summarize test outcomes. -->
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[MIOpen][CK] Fix bwd weight conv test failures by disabling one block-GEMM V5 instance for 3D convs (#6421)
## Motivation
Due to compiler version update, there are test failures in the test
target `test_grouped_convnd_bwd_weight` when running on `gfx90a`. There
are four failing tests for FP16/BF16 that arise from a single kernel
instance. As the problem is in the current develop branch, the test
failures are blocking any PR merges into develop. An example of a failed
CI runs is here:
[http://micimaster.amd.com/blue/organizations/jenkins/rocm-libraries-folder%2FComposable%20Kernel/detail/develop/558/pipeline/](http://micimaster.amd.com/blue/organizations/jenkins/rocm-libraries-folder%2FComposable%20Kernel/detail/develop/558/pipeline/).
The underlying compiler problem is potentially the same as described in
#6342 as the tests are passing for clang compiler version 20.0 and
failing for clang compiler version 22.0.
First attempt to fix this problem had to be reverted in #6400 because it
broke MIOpen internal DB sync tests.
## Technical Details
The root cause for the test failures are the block-GEMM V5 instances of
`DeviceGroupedConvBwdWeight_Xdl_CShuffleV3` that have large tile size.
The V5 pipeline uses double register buffer that in combination with
large tile size causes high register pressure. The latest version of
compiler handles the register spillage incorrectly for `gfx90a`, which
cause the kernel to output incorrect results.
The BF16/FP16 instances of `DeviceGroupedConvBwdWeight_Xdl_CShuffleV3`
that do not use direct load for are divided into two groups
- Base instances
- Instances that result into high register usage (currently only one
instance - one that causes the test failures).
This division allows to disable only the V5 block-GEMM flavor of
`DeviceGroupedConvBwdWeight_Xdl_CShuffleV3<64, 128, 32, 32, Default, 8,
4, 1, 8, 8, 8, 8, 1, 1, 2>` for 3D convolutions on `gfx90a`. The
selective disabling leaves the set of instances for 1D and 2D
convolutions unaffected, and removes at runtime two V5 block-GEMM
instances (`ConvBwdWeightDefault` and
`ConvBwdWeightFilter1x1Stride1Pad0`) per data type (FP16/BF16) when the
device is `gfx90a`.
Because MIOpen uses CK's type string (provided by method
`GetTypeString`) to identify the instances, the DB sync tests are
expected to unaffected since there are still the V2 block-GEMM instances
that result in the same type string
(`DeviceGroupedConvBwdWeight_Xdl_CShuffleV3<64, 128, 32, 32, Default, 8,
4, 1, 8, 8, 8, 8, 1, 1, 2>`). This expectation needs to be verified by
running the MIOpen DB sync tests that are not part of the normal CK PR
build.
## Test Plan
Running all CI tests + the MIOpen internal DB sync tests is sufficient
to verify the correctness of the code changes.
## Test Result
Verified locally that the previously failing tests
`TestGroupedConvndBwdWeight3d/4.Test3D` and
`TestGroupedConvndBwdWeight3d/4.Test3D` have instance counts
- 231 on `gfx90a`
- 233 on `gfx942`
and are currently passing. This confirms the expectation that two
instances per data type should be disabled on `gfx90a`.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
Co-authored-by: Ville Pietilä <>
[MIOPEN] [CK] Revert "[CK] Disable test cases affected by compiler codegen bugs on gfx90a" (#6400)
Reverts ROCm/rocm-libraries#6343
This is causing failures in miopen, namely Dbsync gfx942 even though it shouldn't be affected so this needs to be investigated. Please add miopen as a label to the new PR for addressing the compiler codegen bug so that this can be addressed simultaneously.
[CK] Disable compilation of problematic bwd weight conv instances for gfx90a (#6343)
## Motivation
Due to compiler version update, there are test failures in the test
suite `test_grouped_convnd_bwd_weight` when running on `gfx90a`. There
are four failing tests for FP16/BF16 that arise from a single kernel
instance. As the problem is in the current `develop` branch, the test
failures are blocking any PR merges into `develop`. An example of a
failed CI runs is here:
[http://micimaster.amd.com/blue/organizations/jenkins/rocm-libraries-folder%2FComposable%20Kernel/detail/develop/558/pipeline/](http://micimaster.amd.com/blue/organizations/jenkins/rocm-libraries-folder%2FComposable%20Kernel/detail/develop/558/pipeline/).
The underlying compiler problem is potentially the same as described in
#6342 as tests are passing for clang compiler version 20.0 and failing
for clang compiler version 22.0.
## Technical Details
This PR disables the compilation of the problematic bwd weight conv
instance for `gfx90a` by adding a new CMake flag `CK_USE_GFX90A` that
allows us to detect when we are compiling for `gfx90a`. Using the new
CMake flag, compilation of instance
`DeviceGroupedConvBwdWeight_Xdl_CShuffleV3<64, 128, 32, 32, Default, 8,
4, 1, 8, 8, 8, 8, 1, 1, 2>` is disabled for `gfx90a`.
Co-authored-by: Ville Pietilä <>
[CK] Add BF16^3 support to grouped conv bwd weight: bilinear and scale (#4591)
## Motivation
Until now, XDL grouped conv bwd weight for bilinear and scale only
supported bf16f32bf16.
Therefore, bf16bf16bf16 support should be added.
## Technical Details
Instances were added to the relevant files in
`library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/`
folder. In addition, `add()` functions were included in new files in
`library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/xdl/`
and
`library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_scale/xdl/`
folders. The new .cpp files were also included in the `CMakeFiles.txt`
files of both folders.
## Test Plan
Execute `grouped_convnd_bwd_weight` tests to check execution on
different architectures.
The tests for bilinear and scale already include the tuple
`std::tuple<ck::half_t, ck::half_t, ck::half_t, ck::Number<3>>`, so in
principle, there is nothing to modify in the tests themselves.
## Test Result
`gfx1201`: Tests passed.
`gfx1100`: Tests passed.
`gfx90a`: Tests passed.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Fernando Jiménez <fernando.jimenez@streamhpc.com>
[CK] Replace tuple value construction with tuple_element_t type extraction [1A] (#5030)
## Summary
### Rationale
CK's device operation instance registration uses
`add_device_operation_instances` at ~1,850
call sites to register GPU kernel configurations. The existing
implementation constructs
`std::tuple` values just to extract their types via `decltype`, then
copy-constructs each
instance into `make_unique`. This is wasteful — only the types matter,
not the values — and
forces the compiler to instantiate the full `std::tuple` constructor and
`std::get` machinery
at every call site.
### What changed
- Replace `remove_cvref_t<decltype(std::get<i>(tuple_obj))>` with
`std::tuple_element_t<i.value, TupleType>`, which extracts the type
directly without constructing any values
- Replace copy-from-default `make_unique<T>(value)` with direct default
construction `make_unique<T>()` — all CK device operation instances are
stateless structs with configuration encoded in template parameters
- Add `static_assert(std::is_default_constructible_v<NewOpInstance>)` to
enforce this contract at compile time with a clear error message
- Add Doxygen documentation for this high-traffic public API
### Value
- Eliminates unnecessary template instantiation of `std::tuple`
constructors and `std::get` across ~1,850 call sites
- Establishes a cleaner, more intention-revealing pattern for type-only
tuple usage
- The `static_assert` prevents silent breakage if a
non-default-constructible type is ever added
- No runtime behavior change — zero risk
### Files changed (9)
- `add_device_operation_instance.hpp`: Core pattern change
- 3 example files, 3 reduce instance headers, 1 convolution header, 1
profiler header
## Test plan
- [ ] Existing CI tests cover all ~1,850 call sites (GEMM, reduce,
softmax, convolution)
- [ ] `static_assert` provides compile-time validation stronger than
runtime tests
- [ ] No runtime behavior change — stateless struct default construction
is identical to copy-from-default
- [ ] Compatible with both `std::tuple` and `ck::type_list` containers
🤖 Generated with [Claude Code](https://claude.com/claude-code)
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
[CK] Port non-grouped convolution instances to the grouped kernels (#4875)
## Motivation
Port non-grouped convolution instances to the grouped kernels to
deprecated older non-grouped implementations.
## Technical Details
Add the same instances as non-grouped but using grouped kernel.
## Test Plan
test_grouped_convnd_fwd
## Test Result
pass
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-724
Implement device_grouped_gemm_fixed_nk_bias for RDNA4 (#4340)
## Proposed changes
Summary:
- Modified implementation for grouped_gemm_fixed_nk_bias
- FP16 WMMA examples
- WMMA instances
- Profiler for grouped_gemm_fixed_nk_bias
- Add WMMA instances to existing tests
**This PR depends on PR https://github.com/ROCm/rocm-libraries/pull/4299
and should be merged after it.
Only the last 6 commits are in the scope of this PR.**
## Checklist
Please put an `x` into the boxes that apply. You can also fill these out
after creating the PR. If you're not sure, please don't hesitate to ask.
- [x] I have added tests relevant to the introduced functionality, and
the unit tests are passing locally
- [x] I have added the test to REGRESSION_TESTS list defined at the top
of CMakeLists.txt in tests/CMakeLists.txt, **IF** the test takes more
than 30 seconds to run.
- [x] I have added inline documentation which enables the maintainers
with understanding the motivation
- [x] I have removed the stale documentation which is no longer relevant
after this pull request
- [ ] (If this change is user-facing) I have added release notes which
provide the end users with a brief summary of the improvement from this
pull request
- [x] I have run `clang-format` on all changed files
- [ ] Any dependent changes have been merged
## Discussion
If this is a relatively large or complex change, feel free to start a
discussion by explaining why you chose the solution you did and what
alternatives you considered
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
[CK] Implement device grouped gemm fixed nk multi abd for rdna4 (#4425)
## Motivation
Add support for grouped gemm multi ABD fixed NK. MR
## Technical Details
Changes from the reverted PR:
- Device struct for grouped gemm with multiple ABD and fixed NK
(DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK).
- Wmma versions of existing example codes: 59_grouped_gemm_multi_ABD
- Unit tests for both new wmma implementation and the reference xdl code
(previously missing)
- Note: Some Xdl instances were commented out because of unit test
failures. As mentioned apparently for xdl this feature was missing tests
so our assumption is either there is an implemenetation bug or these
instances were not set up correctly. Has the potential for a follow-up
issue.
- Generic ck profiler interface with the purpose of calling unit tests.
- Gemm instances with specific elementwise operations for gemm bias gelu
calculations.
- Added class for grouped gemm multi ABD reference calculations.
Fix epilogue selection in device implementation that caused unit test
failures
## Test Plan
Covered by added unit tests
## Test Result
CI successfully passing
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Zoltán Lakatos <zoltan.lakatos@streamhpc.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
173 implement device grouped gemm fixed nk for rdna4 (#4299)
## Proposed changes
This PR adds an RDNA4 implementation of the device_grouped_gemm_fixed_nk
instance library using for WMMA.
The implementation is based on the existing
DeviceGroupedGemm_Xdl_Fixed_NK design and reuses the same high-level
structure, but replaces the XDL kernel with a WMMA-based one. It uses
the GridwiseGemm_wmma_cshuffle_v3 kernel.
At this stage, the focus is functional correctness and compatibility,
not performance tuning.
## Technical Details
- Device struct for grouped gemm fixed NK
- Example code for the WMMA version
- Unit tests for both new wmma implementation and the reference XDL code
(previously missing)
- Generic ck profiler interface with the purpose of calling unit tests.
## Checklist
Please put an into the boxes that apply. You can also fill these out
after creating the PR. If you're not sure, please don't hesitate to ask.
- [x] I have added tests relevant to the introduced functionality, and
the unit tests are passing locally
- [x] I have added the test to REGRESSION_TESTS list defined at the top
of CMakeLists.txt in tests/CMakeLists.txt, **IF** the test takes more
than 30 seconds to run.
- [ ] I have added inline documentation which enables the maintainers
with understanding the motivation
- [ ] I have removed the stale documentation which is no longer relevant
after this pull request
- [x] (If this change is user-facing) I have added release notes which
provide the end users with a brief summary of the improvement from this
pull request
- [x] I have run on all changed files
- [x] Any dependent changes have been merged
## Discussion
If this is a relatively large or complex change, feel free to start a
discussion by explaining why you chose the solution you did and what
alternatives you considered
---
🔁 Imported from
[ROCm/composable_kernel#3668](https://github.com/ROCm/composable_kernel/pull/3668)
🧑💻 Originally authored by @bidlekm
---------
Co-authored-by: Marton Bidlek <marton.bidlek@streamhpc.com>
Co-authored-by: Erwin Terpstra <erwin.terpstra@streamhpc.com>
Co-authored-by: bidlekm <bidlekmarton@gmail.com>
Co-authored-by: assistant-librarian[bot] <assistant-librarian[bot]@users.noreply.github.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: illsilin_amdeng <Illia.Silin@amd.com>
Revert "[CK] Add new fwd conv fp16/bf16 instances optimized for unit group size." (#4652)
PR ROCm/rocm-libraries#4275 contains CK fwd conv instances optimized for
`gfx950` and they do not compile for other architectures such as
`gfx940`. To ensure that the optimized instances are compiled only for
`gfx950`, compile-time guard `#if defined(CK_USE_GFX950)` was used. This
approach works correctly when we compile for a single architecture, but
when we compile simultaneously for multiple architectures, flag
`CK_USE_GFX950` is set for non-gfx950 archs as well. As a result, the
multi-arch compilation fails. The problem doesn't appear in the ROCm
libraries CI/CD pipeline since only one architecture is compiled at a
time. Hence, the CI/CD passed for the original PR.
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Revert "[CK Conv] Add bwd weight instance for large-k shape"
(#4506)
Reverts ROCm/rocm-libraries#4266 due to CI failures. Should be
investigated by @johannes-graner
[CK Conv] Add bwd weight instance for large-k shape
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
## Proposed changes
This instance improves the shape used in `./bin/ckProfiler
grouped_conv_bwd_weight 1 2 0 2 0 1 2 1 32 2376 256 3 3 100 100 1 1 1 1
1 1 1 1 all` from 10.3 ms to 6.6 ms.
## Checklist
Please put an `x` into the boxes that apply. You can also fill these out
after creating the PR. If you're not sure, please don't hesitate to ask.
- [ ] I have added tests relevant to the introduced functionality, and
the unit tests are passing locally
- [ ] I have added the test to REGRESSION_TESTS list defined at the top
of CMakeLists.txt in tests/CMakeLists.txt, **IF** the test takes more
than 30 seconds to run.
- [ ] I have added inline documentation which enables the maintainers
with understanding the motivation
- [ ] I have removed the stale documentation which is no longer relevant
after this pull request
- [ ] (If this change is user-facing) I have added release notes which
provide the end users with a brief summary of the improvement from this
pull request
- [ ] I have run `clang-format` on all changed files
- [ ] Any dependent changes have been merged
## Discussion
If this is a relatively large or complex change, feel free to start a
discussion by explaining why you chose the solution you did and what
alternatives you considered
* Adding remaining flavors for grouped conv fwd
As titled. Following variants are added:
- grouped_conv2d_fwd_dynamic_op
- grouped_conv3d_fwd_dynamic_op
- grouped_conv3d_fwd_bilinear
- grouped_conv3d_fwd_convscale
- grouped_conv3d_fwd_convinvscale
- grouped_conv3d_fwd_convscale_add
- grouped_conv3d_fwd_convscale_relu
- grouped_conv3d_fwd_scale
- grouped_conv3d_fwd_combconvscale
- grouped_conv3d_fwd_scaleadd_scaleadd_relu
* Fix incomplete parsing of types from source names in add_instance_library() cmakelists function so we don't build f8 on RDNA3.
* Do not build f8 / bf8 only flavor tests on RDNA3
* Make sure we have proper generic instances for all instance lists related to the post-ces extra flavors, with scalarPerVector = 1. Then disable all but one generic instance per instance list to reduce compile time.
* Post rebase fix: Template parameters for Grouped Conv Fwd Device Impl got tweaked upstream.
* adding int8 and fp16 overloads to the elementwise operations
* fixed copilot nits
* Addressing review comments:
- removed unnecessary examples for dynamic op
- removed unnecessary conv specalizations for all the flavors
- removed spurious bilinear and scale source files
* clang-format
* reduced no of tests
---------
Co-authored-by: Wojciech Laskowski <wojciech.laskowski@streamhpc.com>
* Added bias_bnorm_clamp for WMMA conv fwd large tensor.
Following operations are added for FP16/BF16 data type and NHWGCxGKYXC layout.
- grouped_conv2d_fwd_bias_bnorm_clamp
- grouped_conv3d_fwd_bias_bnorm_clamp
* changed strategy to handle GemmArgs array
* Adding generic instance
* fixed last nits from reviewers and copilot
* Additional flavors for WMMA conv fwd large tensor
- added F16/BF16 clamp operation
- added F16/BF16 bias_clamp operation
- small modification to the device code to accomodate extra tensors
* changed strategy to handle GemmArgs array
* Adding generic instance
* Added generic instance to clamp and bias_clamp ops
* Added bias_bnorm_clamp instances.
* fwd_bias_bnorm_clamp comp instances
* fwd_bias_bnorm_mem_inter and mem_intra instances
* fwd_bias_bnorm_merged_group_instances
* fwd_bias_bnorm_clamp_conv3d_bf16 and f16 instances
* Device level changes for fwd_bias_bnorm_clamp
* Added the test to the regression test list.
* Removed the part 2 and 2x instances
* Removed the irrelevant checks in wmma
* Refactored the instances to adapt to new device implementation
* Updated the reference and include files
* enabling tests
* Added missing profiler
* Added missing instance entry , deleted by mistake
* Reduce bias bnorm clamp instances to only a single generic one.
* Clean up cmakelists file
* clang-format
* Change bias bnorm clamp tests to use monotone initialization values to avoid tiny off-integer gemm results on RDNA3 from blowing up.
* Renaming some instance lists and add functions to be more standardized.
* Commented out non default instances.
---------
Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
* wip: test suite for batched gemm multiple d gemm multiple d, working on gridwise implenentation
* wip: many fixes in implementation of batched gemm gemm multiple d
* wip: batched gemm gemm multiple d gridwise op compiling, not working yet
* fix: incorrect d0 grid indexing in batched gemm gemm multipled
* feat: add instances for batched gemm add relu gemm add
* chore: configure instance with low vector transfer size for odd sizes
* chore: add some more validation to device batched gemm gemm multiple d, and removed template parameter that didn't really make sense
* fix: upate device_batched_gemm_gemm_wmma to work with new gridwise changes
* fix: disable odd size tests on XDL archs
* chore: removed temporary logging
* chore: update some references to C tensor to E tensor
* Tentative fix for example template params
* Tentative fix for non-multi-D batched gemm gemm device impl.
* Tentative fix for xdl example template params
* Tentative fix for profiler build on gfx90a
* chore: improve device batched gemm gemm multi D comment to include all ops and dimensions
* chore: explicitly call ck::make_tuple to prevent issues when std::make_tuple would apply
* fix: make the gemm1 data types match what happens in the device op
* feat: add d0s/d1s datatypes and layouts to the device op type string
* chore: change element-wise op so addition happens in fp32
* chore: add static asserts for gemm0/gemm1 calculated wave sizes
* chore: also updated other element-wise ops to use fp32 calculations
* chore: log number of supported instances
* chore: update instance comment
* chore: disable kernel timing in example by default
* fix: gemm1 wave size calculation
* fix: make sure batched gemm multiple d gemm multiple d profiler performs correct type conversions
* chore: remove increased tolerance in batched gemm gemm multiple d example
* chore: add comment explaining that verification fails for certain input values
* chore: clarify instance comment
---------
Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
* Add support to fp16 + compute fp16 and bf16 + compute bf16 contractions
Enables hipTensor to access the WMMA HW functionalities
for these combinations of datatype on gfx11 and gfx12.
* Fix change to contraction scale tests
* Fix clang-format
* feat: test setup for batched contraction (aka batched gemm multiple d e permute)
* wip: device struct for WMMA batched contraction multiple d based on new gridwise op
* feat: working batched contraction on RDNA, non-naive tensor descriptors for gridwise_gemm_wmma_cshuffle_v3, test setup for odd cases
* fix: failure to resolve template parameters when calling new function overload
* fix: passing reference type as parameter instead of underlying types
* fix: merge error caused duplicate definitions
* fix: make sure constness of template and parameters types match
* fix: don't compile batched contraction test on unsupported architectures
* feat: add example for new wmma implementation, and consolidate example code between platforms
* style: return inline instead of with branch
* chore: add extra assert on vector memory access sizes
* chore: clean up some unused variables
* fix: correct tail number calculation, added small cases and extra instances to the test
* fix: properly support wave transfer by generating correct grid descriptors dependent on the transfer method
- Add support for direct store in epilogue instead of cshuffle
- Add padding support for wave transfer without transpose
- Add wave transfer with interleaved layout to support direct store
- Enable new functionalities on GEMMs
- Add optional new functionality support for grouped convolution fwd
- Add some fast instances for grouped convolution fwd with new functionalities (proper tuning needed)
* feat: grouped gemm tile loop support for RDNA4
* fix: removed extra parameter from grouped gemm example instance
* fix: FP8 check incorrectly enabling FP8 on RDNA3
* Implement grouped gemm fastgelu for RDNA4
* chore: some cleanup and minor inconsistencies in grouped gemm profiler
* chore: clarified logic and reporting of supported instance warnings
* Added device level implementation for bwd_data_wmma_v3.
* Added first instance of bwd_data_wmma_v3(f16).
* Add support for bwd data in gridwise implementation
Some changes are general for convolution and some are specific for bwd
data. We need to generalize them once we have fwd, bwd data and bwd
weight
* Initial device implementation of bwd data
* Remove unused template parameters in device impl
* Add one instance for different layout
initial check of device implementation
* Add tests for splitk and for different layouts
* Appended more instances to wmma_v3_f16.
* Added conv_2d bf16 wmma_v3 instances.
* Added conv_3d_bf16 wmma_v3_instances.
* Added conv_3d_f16_wmma_v3_instances.
* Added SplitN test cases for wmma.
* Conv3d_bwd_data_scale_wmma_v3 instances.
* Conv3d_bwd_data_bilinear_wmma_v3_instances
* Renaming the device level instances file to common name , since it is defined for different DataTypes.
* Renaming the instances and fixing typo
* Added the test cases to regression test list
* NCHW support for wmma_v3
* Examples for bf16 and f16 bwd_data_wmma_v3
* Added transpose conditons for device impl
* fixing bugs
* Added the gemm_args array implmentation
* WIP debug conv bwd
* fix splitk
* Grouped gemm fix
* Update CmakeLists with EOF
* Added more instances for tests
* Fixed the run time error in examples and removed 3d conv examples.
* Fixed a typo.
* Updated CmakeLists to removed the 3d convultion deleted files
* Added print error statements for unsupoorted argument
* Added the merge conflict related changes
* Fixed compilation error
* Fixed the InstanceFactory duplication error.
* Removed the print statements and added logs to Arg function
* All the merge conflict related errors resolved
* Added d_tensor tests.
* Added the missing example types of wmm_v3
* Merge error fix
* Corrected the instance name
* Reverted the bias relu change
* Revereted the transpose load local change
* Updated the regression test list with bwd_data_scale
* Revert "Revereted the transpose load local change"
This reverts commit 0b7281edb2bf008e407006690a00621174d9d19b.
* Revert "Merge error fix"
This reverts commit f3c85daa474b1b83d10c8a3ce077354e71d91a2b.
* Reverting the local change
* Added merge error fix
* Build error fix due to merge conflicts
* Added bias_relu example for wmma_v3
* Modified the main method in dtensor tests
* Updated the dtensor tests to pick all the shapes
* Updated the dtensor test shapes.
* Updated the mem operations in tests.
* Added reference func
* Fixed typos in device impl
* Added new header file and modified the include file for 3d tests
* Renamed the test file and added reference func call.
* clang format fix
* Added ignore params
* Modified device impl and tests
* Removed debug print statements and updated dtensor test shapes
* Fixing merge conflicts
* Fixing more merge conflicts
* Fixed copyrights
* Updated the tuned instances to bilinear and scale.
* Adding tuned instances to vanilla wmma_v3
* Removed all unused instances and modified test layouts.
* Cleaned up all instances , reverted back fwd fp16 instances and updated tuned fp16 instances.
* Fix clang format
* Updated tuned f16/-genric instances
* Formatting the instances file
* Fixed copyrights and clang issues
* Nonsense commit to force git to force
* Removed the transpose instances
* Added verified genric instances
* Fixing namespace errors
* Added todo for failing shapes
* Formatting instance file
* Fix instance list formatting
* Removing unnecessary formats
* Renamed the common file
* Unification of xdl and wmma bwd_data tests
* Updated Cmake
* Added all layout types and deleted code.
* Updated Cmake to add the condition to all tests.
---------
Co-authored-by: Enrico Degregori <enrico@streamhpc.com>
Co-authored-by: Anton Gorenko <anton@streamhpc.com>
Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
* Replace grouped convolution bwd weight wmma v3 bilinear and scale bf16f32bf16 support with bf16bf16bf16 support. Update tests.
* Tentative fix for bwd weight bilinear bf16bf16bf16, seems like the bilinear elementwise overload for this case (bf16, f32 accu, bf16) was wrong.
