[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] Fix latest build issues with staging compiler.
## Motivation
Fixing new warnings with 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] Allow skipping split-K C-buffer zero-init in
xdl_cshuffle blockscale GEMM (#7935)
Add a `skip_zero_init` flag (default false) to the Problem/Argument of
the xdl_cshuffle block-scale GEMM device ops (multiple_d ab_scale and
blockscale b-preshuffle). When the flag is set, the device invoker skips
the internal hipMemsetAsync that zeroes p_c_grid before the KBatch > 1
split-K atomic-accumulation path. The flag is declared on the gridwise
Problem struct (inherited by Argument), so it is visible on both the
rotating-cache (arg_) and the normal (arg) launch paths in each device
op.
Why: callers that already pre-zero the output buffer otherwise pay for a
redundant device-wide memset before split-K atomic accumulation. Gating
the memset behind an opt-in flag lets such callers avoid the duplicate
work. Because the flag defaults to false, every existing call site is
unaffected and the observable behavior is unchanged.
## Motivation
<!-- Explain the purpose of this PR and the goals it aims to achieve.
-->
## 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: Cursor <cursoragent@cursor.com>
[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] Grouped Convolution Global Load/Store support (#7631)
## Motivation
Grouped Convolution Global Load/Store support to cover large tensor
cases.
## Technical Details
Utilize global load for grouped convolution forwad kernels. Update
Indexes to use int64.
## Test Plan
- test utils
- test conv kernels in next pr with instances
## Test Result
CI pending
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
AICK-1255
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
[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.
[CK] Decouple EpilogueArgs from GridwiseGemm implementation (#4871)
This is duplicate of #4537. I could not re-open it since te target
branch got deleted and could not change the target branch since it was
closed... :)
## Motivation
Right now, all the Epilogues structs are declared inside the base
gridwise struct. They should be independent of it and the specialization
of the selected Epilogue Type should be declared within the the kernel
function.
## Technical Details
All Epilogue structs depend on template parameters that are known to the
base Gridwise Gemm struct. In this PR, we export them to be used
independently by any struct that might need to extract them. This
approach will serve the decoupling purposes for the Epilogues, but also
enable future constructs to use and expand this approach. See
30e2a4c01b64bdea68857c7badd9d7cffbf1adb9.
Right now an issue that arises is that when implementing a new Epilogue
Type, the developer is not forced to decide where this struct should/can
be used or not. To fix this I propose defining an `enum struct
EpilogueType` that will be used to fetch the Epilogue specialization
through a helper struct. See a943ac8d130e12d6843715b322181186e54ba15c.
Note that all the instantiation details will stay in this helper struct.
Also note the static assertion in the else statement.
## Test Plan
Test with existing CI, as nothing is added/removed.
## Test Result
All relevant existing CI tests should pass.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
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.
projects/composablekernel: add SwigluStep support for MoE blockscale (#6118)
## Summary
- add `swiglustep_and_mul` to the composablekernel MoE blockscale
activation enum
- implement the corresponding blockscale epilogue path for `SwigluStep`
- keep existing `silu` and `gelu` paths unchanged
## Scope
This PR covers the classic composablekernel blockscale MoE path under
`projects/composablekernel`.
This is separate from the `ck_tile` / FlatMM path being discussed in
ROCm/rocm-libraries#5992.
## Motivation
`Step-3.5-Flash-FP8` uses `SwigluStep` in its MoE MLP path. The
dependent AITER change needs native support for this activation in the
classic composablekernel MoE blockscale path.
## Validation
- patch is limited to two composablekernel files under
`projects/composablekernel`
- existing `silu` / `gelu` paths are unchanged
- dependent AITER runtime validation hit the classic CK 2-stage path
with AITER MoE enabled
[CK] Fix MOE FP8 SplitK buffer descriptor OOB (#5086)
When SplitK is enabled, kernel entry shifts A/B/AScale/BScale base
pointers by SplitKBatchOffset, but make_dynamic_buffer element spaces
are still based on full K dimension. This causes hardware buffer
resource descriptors to extend beyond the actual tensor allocation,
leading to GPU memory access faults when the tensor happens to be placed
at the end of an allocated memory pool region.
Fix by subtracting the split offset from each buffer's element space in
both Run() (v1 pipeline) and Run_2Lds() (v2/v3 pipeline), so the buffer
descriptor range [shifted_base, shifted_base + reduced_space) exactly
covers the valid allocation.
Also refactor SplitKBatchOffset to accept const Problem& (instead of
Argument&) and add a default constructor, enabling direct reuse in
Run/Run_2Lds without duplicating offset calculation logic.
Made-with: Cursor
## Motivation
<!-- Explain the purpose of this PR and the goals it aims to achieve.
-->
## 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
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Yi DING <yi.ding@amd.com>
[CK] Unify the grouped convolution gridwise Run() functions (#4421)
## Motivation
There are currently three different grouped convolution related Run()
function overloads that exist in `gridwise_gemm_wmma_cshuffle_v3.hpp`.
These are used for the different types of grouped convolution: Forward,
Backward weights, and Backward data.
The functions are very similar and should be unified to a single `Run()`
function for all types of grouped convolution.
## Technical Details
The three old `Run<>()` functions were replaced with a single unified
function.
The new `Run<>()` function is run from device implementations:
- DeviceGroupedConvFwdMultipleABD_Wmma_CShuffle_V3
- DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffleV3
- DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3
- DeviceGroupedConvBwdWeightTwoStage_Wmma_CShuffleV3
- DeviceGroupedConvBwdWeight_Wmma_CShuffleV3
The DeviceGroupedConvFwdMultipleD_Wmma_CShuffle_V3_Large_Tensor
implementation uses a different `Run<>()` overload and was therefore not
modified.
## Test Plan
Run the following grouped convolution tests on `gfx1201`, as this
architecture is WMMA-capable:
- `test_grouped_convnd_fwd`
- `test_grouped_convnd_bwd_weight`
- `test_grouped_convnd_bwd_data`
Compilation and testing were also executed on `gfx1100` to avoid CI
problems.
## Test Result
First part (unification of `Run<>()` function): All tests successful.
Second part (integration of single `Run<>()` function as a direct call):
All tests successful.
## 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] use int64 for ptr offset (#5094)
## Motivation
When the number of experts (E) is large (e.g., E=257 in DeepSeek-V3),
the `expert_id * expert_stride` calculation in MOE GEMM kernels
overflows `int32` (`index_t`), causing the weight matrix (B) pointer to
wrap to an invalid address and triggering a GPU memory access fault.
For example, with `N=1024, K=7168, IsInputGemm=true`:
- `expert_stride = N * K * 2 = 14,680,064`
- `INT32_MAX / expert_stride ≈ 146`
- Any `expert_id >= 147` causes overflow → negative offset → illegal
memory access → GPU crash
## 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
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
Co-authored-by: Thomas Ning <Thomas.Ning@amd.com>
Co-authored-by: amd-shiraz <shiraz.ali@amd.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>
Revert "[ck] Support VGPR estimate in GridwiseGemm_wmma_cshuffle_v3" (#4762)
Reverts ROCm/rocm-libraries#4638
unfortunately, this PR interfered with the PR#4299 and caused build
errors for gfx11:
In file included from
/rocm-libraries/projects/composablekernel/library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk/device_grouped_gemm_wmma_fixed_nk_bf16_bf16_bf16_mk_kn_mn_instance.cpp:7:
In file included from
/rocm-libraries/projects/composablekernel/library/include/ck/library/tensor_operation_instance/gpu/grouped_gemm/device_grouped_gemm_wmma_fixed_nk_instance.hpp:11:
/rocm-libraries/projects/composablekernel/include/ck/tensor_operation/gpu/device/impl/device_grouped_gemm_wmma_fixed_nk.hpp:553:21:
error: no matching function for call to 'CheckValidity'
553 | if(!GridwiseGemm::CheckValidity(
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
[ck] Support VGPR estimate in GridwiseGemm_wmma_cshuffle_v3 (#4638)
1. Add GetEstimateVgprCount to estimate the VGPR usage in
GridwiseGemm_wmma_cshuffle_v3
2. Add IsValidCompilationParameter to disable kernel which use too many
vgprs.
- Currently, the threashold is AvailableVgprCount * 1.25
3. Modify examples to avoid test is disabled on gfx11
It is port from internal repo
PR[#192](https://github.com/ROCm/composable_kernel/issues/192)
## Motivation
<!-- Explain the purpose of this PR and the goals it aims to achieve.
-->
## 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: illsilin_amdeng <Illia.Silin@amd.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>
* [Compiler] Addressing new compiler warnings
Clang enables new lifetime warnings in production and we see build
errors due to this with the staging compiler.
The attributes added in this PR are suggested by the compiler. However,
I'm not very familiar with the code base, so the changes may be
incorrect.
* Update some more instances
* Adds file-level ignores via clang diagnostic pragma
The number of instances was large, so I decided to use file-level scope
to disable the warning via pragma clang diagnostic ignored.
It also showed this warning coming from the gtest dependency. For that,
I did add the respective command line flag to the CMake variables. I
don't know if this is acceptable or not.
* This adds the remaining instances
For a build on gfx90a.
* fix clang format
* Adding couple more instances from gfx1200 build
* Fixed another few instances
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: illsilin_amdeng <Illia.Silin@amd.com>
* Add multi AB support to wave transfer
* Improviments to multi ABD examples
* Add instances and use intrawave v1 instead of interwave
* Apply changes to other transfers
* Wave transfer: add support for multiple internal vgpr buffers
* Fix compilation error gfx11
1. Add base class GridwiseGemm_xdl_cshuffle_base for all gridwise_gemm_xdl classes.
- to select correct LDS layout and epilogue behavior , three additional parameters is added.
- ForceNaiveLdsLayout: disable XOR based LDS layout when it is true
- DirectLoad: pipeline only use directload, we need force naive layout and ignore any padding on gfx9
- IsMxGemm: epilogue has two addtional dimensions
2. Move all LDS descriptor layout related fucntion to base class, including
- GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1
- GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1
- GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
3. Move several LDS related helper funtions to base class, including
- GetSharedMemoryNumberOfByte
- GetABlockDescriptor_AKB_AK0PerBlock_MPerBlock_AK1
- GetBBlockDescriptor_BKB_BK0PerBlock_NPerBlock_BK1
- GetCBlockDescriptor_MBlock_NXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl
4. Move all c epilogue related code to base class, and 4 kind of implementation are provided
- RunEpilogueNoShuffle
- RunEpilogue
- RunMultiDEpilogue
- RunMoeEpilogue
* Add padding support with transpose
Also move check before writing storing is_src_valid during reading
* Add/modify instances to use wave transfer for gemm universal
Condition is changed so now the vectorsize of vmem reading and lds
writing must be equal to 8 in order to use the wave transfer
* Fix clang format
* Modify example
* Fix bwd data
* Add restriction for wave transfer with padding and transpose
Add test case which shows this limitation
* Fix validity checks 8 bit types
* Add validity check gemm_bias_add_reduce
* Add validity check grouped gemm tile loop
* Fix validity checks new flavours
* Minor fixes
* Fix clang format
* Moved device struct for batched gemm wmma to a common file
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
* Use the common device struct in the scaled batched gemm wmma implementation
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
* Boy-scout: Remove unused includes and ambiguous comment
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
* Moved pointer offset calculation and gridwise argument to common struct
This change enables further code reduction by re-using the common structs for the batched gemm and batched gemm b scale wmma implementations.
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
* Moved type string to the common struct of DeviceBatchedGemm_Wmma_CShuffleV3_Common"
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@streamhpc.com>
---------
Signed-off-by: Chris Tsiaousis <chris.tsiaousis@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>
* 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
* nt on fp8 blockscale
* some improve and tests needs to be fixed
* update
* fix format
* revert useless change
* revert any change in amd_buffer_coherence
* Take split_k into account when checking 2GB tensor limit.
* Revert "Take split_k into account when checking 2GB tensor limit."
This reverts commit adf35c91be.
* Optimize grouped conv bwd wei split_k off calc
(cherry picked from commit 6f61dd56c5)
* Update gridwise_gemm_xdl_cshuffle_conv_v3.hpp
(cherry picked from commit b33877c10f)
* Fix tensor descriptors and stride calculations
* Don't miss half of the elements
* Fix buffer size calculations
* Disable hack if stride not divisible by k_batch
* Clean up comments
* Disallow hack in non-contiguous edge cases
* Index -> Dim
* Fix broken test
* Refactor applicability checks into separate function
* fix missed variable name
* Fix variable name in info print
* update V3 2GB check
* No more regression, use templates instead
* Code deduplication
* Regression fix for cshuffle
* arch-guarded atomic_add implementations for gfx11
* Similar for half(4|8)_t as well
* Only use both offset hacks at the same time
* Revert "arch-guarded atomic_add implementations for gfx11"
This reverts commit 3883fe6935.
This reverts commit 5311ec608d.
* Reapply "arch-guarded atomic_add implementations for gfx11"
This reverts commit 1972adeddc.
* Only remove float4 atomic_add
* Refactor to single flag
* Consolidate template parameters
* Consolidate flag in transformers
---------
Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
* 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>
* Fixed typos for padded instances
* Added tests for fp16, KM_KN and KM_NK
* Padding not supported for when BDataType is pk_i4_t. Added fix for correct check and removed padding instances.
* Fixed typos
* Updated the set of tests for FP16
* Updated the set of tests for FP16
* Fix typo
* Moved f16xi4 test under the correct data layout group
* example for gemm_universal_bf16
* Adding examples for gemm_wmma instances
* Added the missing parameters
* Fixed review comments and added executable to cmakeLists
* Fixing clang format
* Fixing build erros
* Fixed compilation failure.
* Modified some code as per gemm_universal_examples
* Fixed the gemm specialization error
* Fixed the build errors.
* Fix strides of a/b_thread_desc
The descriptors are larger than needed (even though the compiler don't alloc registers for unused values).
* Load in M/NRepeat dims with thread copy's slice instead of a loop
* Clone BlockwiseGemmXdlops_pipeline_v1 for WMMA implementation
* Implement Intrawave and Interwave variants of pipeline v1
* Add instances for Interwave and Intrawave v1
* Add instances with ABlockLdsExtraM and BBlockLdsExtraN = 0
* Remove instances that are too slow (mostly because of register spilling)
* Add a workaround for fp8/bf8->f32 packed conversion issue
* Add instances for Interwave and Intrawave v1
* Enable profiling of mixed precision with f8 and int4 on WMMA
* Fix segfault in profiler when B is pk_i4_t
b_device_buf's size in bytes is larger than b_k_n_permute so b_device_buf.ToDevice reads out-of-bounds.
* Remove instances that are too slow (mostly because of register spilling)
* Add missing add_device_gemm_wmma_universal_f8_f8_bf16 declarations
* Add test case for bf16_i4
* Add missing Regular tests
* Add test_gemm_universal_xdl/wmma_fp16 to REGRESSION_TESTS
They take more than 30 seconds
* Fix a bug that fp16_i4 validation passes only with PermuteB
A permutation required by conversion from pk_i4_t to half_t does not
depend on PermuteB, they can be used independently.
* Use PermuteB with f16_i4 in most instances (as xdl)
Some instances use PermuteB = false for checking correctness.
See also the previous commit.
* Fix cache flushing for pk_i4
* Add mixed precision examples
* Disable all tests and instances with f8 on gfx11
Even though f8_f16 and f16_f8 don't require f8 WMMA instructions,
gfx11 still lacks hardware instructions for fast f8->f32 conversion.
* Add FP16 KM_NK and KM_KN test suites for XDL
These tests were added to common .inc for better testing of WMMA instances
* Support multiple D in GridwiseGemm_wmma_cshuffle_v3
DeviceGemm_Wmma_CShuffleV3 is changed for new template parameters.
* Use ThreadGroupTensorSliceTransfer_v7r3
* Clone for device_gemm_wmma_cshuffle_v3.hpp for future Multiple D support
* Clone example/65_gemm_multiply_multiply/gemm_add_add_xdl_fp16.cpp for wmma
* Implement DeviceGemmMultipleD_Wmma_CShuffleV3
* Make gemm_add_add_wmma to work with DeviceGemmMultipleD_Wmma_CShuffleV3
* Prepare gemma_add tests for adding wmma
* Add gemm_add_fastgelu instances and test
* Add a special wrapper to use DeviceGemmMultipleD_Wmma_CShuffleV3 with old API
ckProfiler uses DeviceGemmMultipleD (tests also call its functions), the wrapper allows to use
DeviceGemmMultipleDSplitK instances there.
* removed unnecessary ck parts from compilation
* initial gemm_add_multiply instance implementations
* fixed profiler help message for gemm_add_multiply
* improved multiply_add profiler layout help
* fixed template arguments for test instances
* added test for gemm_add_multiply
* Support multiple D in GridwiseGemm_wmma_cshuffle_v3
DeviceGemm_Wmma_CShuffleV3 is changed for new template parameters.
* Use ThreadGroupTensorSliceTransfer_v7r3
* Clone for device_gemm_wmma_cshuffle_v3.hpp for future Multiple D support
* Clone example/65_gemm_multiply_multiply/gemm_add_add_xdl_fp16.cpp for wmma
* Implement DeviceGemmMultipleD_Wmma_CShuffleV3
* Make gemm_add_add_wmma to work with DeviceGemmMultipleD_Wmma_CShuffleV3
* Prepare gemma_add tests for adding wmma
* Add gemm_add_fastgelu instances and test
* Add a special wrapper to use DeviceGemmMultipleD_Wmma_CShuffleV3 with old API
ckProfiler uses DeviceGemmMultipleD (tests also call its functions), the wrapper allows to use
DeviceGemmMultipleDSplitK instances there.
* switched to splitK interface
* log print added to splitk benchmarks
* revert main cmake comments
* newline change reverted
* added add_fastgelu instances
* revert unintended change in xdl add_fastgelu
* created gemm_add_add_fastgelu instances
* created fastegelu instances
* added tests for all splitk fastgelus
* Added tests.
* multiply_add instances created
* updates to add_multiply splitk instances
* splitk xdl test fixes
* added wmma multiply_multiply instances
* fixed ONLY_XDL_AND_WMMA_KERNELS tag
* Added gemm_add examples for wmma v1 and v3
* fixed / workarounded i8 instances
* Modified the v3 code to added one fp16 bxdl instance.
* added bf16 xdl instance.
* adding gemm_add wmma_cshuffle and other support
(cherry picked from commit ec447e7f564095ea969eddc39ec77b843aa52976)
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
* add instances into camkelists
(cherry picked from commit 23bf2d2771c939ea3ca7f493433c55255bffd08e)
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
* This is work in progress, edited the template parameters in order to build
(cherry picked from commit b4fde8a3314cb44659c4bbda35f1a0133c63dc41)
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
* temp work saved, changed the BDataType to f16 or bf16 since wmma currently not support non-equal A and B datatype
(cherry picked from commit 22fbd68f1db458ab50780a394ee2544c7a1484d1)
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
* added datatype and use clang-format-12
(cherry picked from commit ae4e853682ef1bb27784b2f965b4a66b3751ceec)
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
* Fixing build errors
* Added instances for v3
* Adding instances and executables
* Code update of template parameters modified.
* Renamed file.
* Added tests.
* resolved error tests.
* Fixing build errors
* Updated comments
* removed the changes as per the MR review comment.
* Updated tests.
* fp8 instances - not tested
* Restored the Cmake file that was reverted by mistake during rebase.
* fixed wmma_op test
* Updated comments.
* Updated the template parameter description
* fixed rdna4 instances
* fixed back compatibility on gfx11
* cleanups
* fix ckProfiler
* one more cmake fix
* added fp8 instances
* Updated tests to ad BF16 instances as per review comment
* Added include file and cleaned up(as per review comment)
* Updated and optimized the example code for all types.
* Fixed clang format
* Resolve "Implement `device_gemm_bilinear` for RDNA4"
* test generalization to handle FP16 shuffle better
* added missing changes
* Added bf16 wmma instance for add_relu
* Added f16 wmma instance and corrected bf16 instance errors.
* Added instances to Cmake
* Modified the template parameters to make the instances work.
* Fixed typo in profiler
* Added v3 instances for gemm_add_relu
* addressed core review comments
* Added test for gemm_add_relu wmma instance
* Cleaned up the code.
* Added examples for gemm_add_relu
* Fixing typo to resolve build errors.
* Fixes applied to fix the precision loss.
* fix billinear test after merge
* Removed the old wmma instances.
* Added wrapper and renamed the wmma_v3 instances
* Updated copyrights and added wrappers.
* Fixes applied according to review comments
* Apply 1 suggestion(s) to 1 file(s)
Co-authored-by: Robin Voetter <robin@streamhpc.com>
* Removed the old wmma instances.
* Updated wrapper for the v3 instances
* removed the old wmma examples
* Renamed the v3 instances
* Deleted the gtest file added by mistake.
* Updated thge profiler with wrapper
* Fixed test errors.
* Fixed the review comments
* Fixed the if condition MACROS.
* REVERTED THE PROFILER CHANGES
* Revert "REVERTED THE PROFILER CHANGES"
This reverts commit 21cb98546c.
* Revert "Fixed test errors."
This reverts commit 13efcc6fe1.
* Revert "Updated thge profiler with wrapper"
This reverts commit 536f86661d.
* Added missing wrapper instances
* Updated copyrights.
* Fixed typo.
* Fixed copyrights.
* Updated copyrights.
* updated copyrights.
* comments on the atomics workaround
* fixed cmake comment
* Fix bug from merge
* clang-format-18
* Fix compilation error
* multi_abd wmma support:
- Add multiple A and B support to multiple D implementation (gridwise level)
- Add multi_abd GEMM (device level)
- Add instances (xdl parity)
- Add tests (both xdl and wmma)
- Add examples
- Add ckProfiler support (both xdl and wmma)
* Fix bug in device print function
* Fix unused template parameter
* Add support for fwd conv in gridwise implementation. Identical to run function for bwd data.
* Initial device implementation for grouped conv fwd multiABD wmma cshuffleV3. Functional but needs some fixups and extra features in the future.
* Make relevant profilers print the number of valid instances to aid testing.
* Add instances for all vanilla 2D and 3D flavors for f16 and bf16, only one instance per instance list to save compile time for now. Also added incomplete set of comp instances and bias_clamp for f16 2D, just to make sure the multiple-D aspects of the device implementation are working.
* Reset output buffer after each run in profile_grouped_conv_fwd_impl().
* Disable sharding for the new instances for now, has tendency to lead to linker errors on repeat builds.
* Add CTranspose optimization for NCHW cases just like in xdl cshuffle non-v3 device implementation.
* Add instances for all 8-bit 3D vanilla grouped conv fwd types, including mixed types but with the exception of deprecated f16 comp fp8. Adapt test so we can test 8-bit and mixed types.
* Add int8 instances for 2D vanilla grouped conv fwd all layouts.
* Implement merged groups in device impl and add instances for merged groups 3D vanilla conv fwd
* Add merged groups instances for all 2D vanilla grouped conv fwd types and layouts.
* Implement multi-AB support for grouped conv fwd and add example.
* Add 1D instances
* Add D layout tests to IsSupportedArgument()
* Add comp and mem instances for all vanilla 2D grouped conv fwd types. Skipping "x2" and "part2" instance lists, can be added later without special names if necessary.
* Add comp and mem instances for vanilla 3D grouped conv fwd. Skipped 2x and part2 instances, can be added later in the same instance lists.
* Add some more tests for vanilla grouped conv fwd
* Add 2D bias clamp instances and tests
* Add 3D bias clamp instances and tests
* Add 2D and 3D clamp instances and tests
* Unify problem sizes across vanilla and clamp flavor tests
* Clean up device implementation: remove old todos, remove unnecessary comments and print statements, tweak description, wrap all prints in env check.
* Implement rotating memory and flush cache. Requires ad-hoc buffer size calculations.
* Remove wmma fp8 and bf8 instances when not targetting gfx12
* Add newer instances to DEVICE_INSTANCES so the main ckProfiler can build
* Remove old years for newly created files.
* No need to time kernels for now.
* Fixup comments
* Pass struct args to Gridwise Run() function by reference.
* Don't use workspace memory in the case where A needs explicit transposition but B does not.
* Move calculation of rotating memory buffer sizes to Argument member functions.
* After the convolution to gemm transformation, the resulting 2D tensor descriptors are not necessarily RowMajor or ColumnMajor, so things should not rely on this distinction. Therefore, pass all RowMajor to the Gridwise and use a special version of CheckValidity that does not rely on 2D tensor layouts.
* Unify xdl and wmma example code for grouped conv fwd scaleadd ab
* Go back to passing RCR 2D tensor layouts to gridwise gemm, and use CRC for the CTranspose case. Also remove the special convolution version of checkValidity(). It seems like no matter what 2D tensor layouts you pass to the gridwise gemm, and no matter if you are using extraMN, and no matter if you are using the convolution version of checkvalidity, the results of all tests are the same.
* Add wmma scaleadd ab instances to the device factory and add a completely new scaleadd_ab gtest test for wmma cshufflev3 and xdl. Currently there is no profiler for scaleadd_ab so I made my own inside the test. Furthermore for XDL only the (NDHWGC, GKZYXC, NDHWGK) layout combination existed in the instance factory so that is the only one I added for wmma cshufflev3 and the gtest test as well. Another layout is tested in example 62, for xdl and wmma cshufflev3.
* Add support for V3 pipeline (tested). To be able to support num_loop < 3 we need the fixes from the batched gemm gemm MR which was already merged upstream, so just need to rebase or merge.
* Small post-merge fixup, everything seems to work.
* Do not build or run Xdl operations with Wmma backend for now. Will be reverted before upstreaming.
* Extend scaleadd_ab instance lists
* Extend merged groups instance lists, including adaptations of xdl "2x" instances.
* Extend "comp" instance lists, including "2x" and "part2" instances. 2x instances disabled for now since they do not compile.
* Extend "mem" instance lists.
* Extend regular instance lists.
* Fixup comments and ignored kernel arg name
* Properly use the splitN offsets for D tensors in the gridwise Run() function. Was necessary to pass the bias_clamp_large_cases test.
* Make sure all strides in ComputePtrOffset are at least value initialized to avoid undefined strides. Not convinced this struct is properly initialized in other code / future code.
* Re-enable sharding for wmma cshufflev3 instances
* Post merge fix to vanilla test
* Optionally allow num_k_loop <= PrefetchStages in gridwise CheckValidity. Use this for grouped conv fwd but not in general.
* Remove spurious ck_tile changes that were presumably introduced somewhere in the repeated merging from develop.
* Post-merge fixes. Make sure the new gridwise gemm wmma v3 common Run function can be used. Remove splitK, and forceThreadTileTransfer for now. Also add CShuffle epilogue argument.
* Disable FP8 / BF8 testing on CDNA1/2, it doesn't work anymore and needs to be either fixed or removed.
* Re-enable old wmma instances
* Re-enable Linqun's Xdl Wmma instances
* Small post-merge fixes
* Fix copyright headers
* Remove commented code snippet in gridwise
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
* Limit the explicit cast added in threadwise_tensor_slice_transfer_v7r3 to only be used for f8, just in case it hurts performance.
* Adding tuned instace list for groupoed conv fwd (#3288)
Following flavors are updated with tuned instance list:
- grouped_conv2d_fwd
- grouped_conv2d_fwd_bias_clamp
- grouped_conv2d_fwd_clamp
- grouped_conv3d_fwd
- grouped_conv3d_fwd_bias_clamp
- grouped_conv3d_fwd_clamp
- grouped_conv3d_fwd_scaleadd_ab
Re-factored instance selection:
- removed all the unnecessary instance tuples (comp/mem/16x16/generic)
- removed all unnecessary layouts and data types
* Do not use std::remove_cvref_t, does not exist in C++17, use custom one.
* Splitting grouped conv fwd instances (#3449)
* Disable unnecessary and failing tests related to experimental CK builder
* Disable unnecessary ck builder experimental tests fully
---------
Co-authored-by: Anca Hamuraru <anca@streamhpc.com>
Co-authored-by: apoorva <apoorva@streamhpc.com>
Co-authored-by: Anton Gorenko <anton@streamhpc.com>
Co-authored-by: Zoltan Lakatos <zoltan.lakatos@streamhpc.com>
Co-authored-by: Cenxuan <cenxuan@streamhpc.com>
Co-authored-by: Robin Voetter <robin@streamhpc.com>
Co-authored-by: Enrico Degregori <enrico@streamhpc.com>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
Co-authored-by: Wojciech Laskowski <77888887+wj-laskowski@users.noreply.github.com>
* Convolution bwd weight device implementation
* Merge branch 'grouped_conv_bwd_weight_device_impl_wmma' into 'feature/conv_bwd_weight_wmma'
Convolution bwd weight device implementation
See merge request amd/ai/composable_kernel!38
* Fix bug and disable splitK=-1 tests for wmma
* Add generic instances for bf16 f32 bf16
* check gridwise level validity in device impl for 1 stage D0
* Fix bugs in device implementation:
- rdna3 compilation error
- gridwise layouts (need to be correct to ensure that CheckValidaity()
works correctly)
* Add padding in conv to gemm transformers for 1x1Stride1Pad0 specialization
* Remove workaround for 1x1Stride1Pad0 conv specialization
* Add instances for xdl parity (for pipeline v1)
* Add two stage instances (xdl parity)
* Add multiple Ds instances
* Add examples
* Uncomment scale instances
* Fix copyright
* Fix examples compilation
* Add atomic add float4
* Fix compilation error
* Fix instances
* Compute tolerances in examples instead of using default ones
* Compute tolerances instead of using default ones in bilinear and scale tests
* Merge branch 'grouped_conv_bwd_weight_instances_examples' into 'feature/conv_bwd_weight_wmma'
Grouped conv: Instances and example bwd weight
See merge request amd/ai/composable_kernel!47
* Device implementation of explicit gemm for grouped conv bwd weight
Based on batched gemm multiple D
* Add instances for pipeline v1 and v3
* Add support for occupancy-based splitk
* Fix ckProfiler dependencies
* Review fixes
* Merge branch 'explicit_bwd_weight' into 'feature/conv_bwd_weight_wmma'
Device implementation of explicit gemm for grouped conv bwd weight
See merge request amd/ai/composable_kernel!52
* Fix cmake file for tests
* fix clang format
* fix instance factory error
* Adapt all grouped conv bwd weight vanilla Xdl instances to 16x16. MRepeat doubled for all but 12 of them (some static assert failure). Also added custom reduced profiler target for building grouped conv bwd weight vanilla only profiler. Verified with gtest test.
* Revert "Adapt all grouped conv bwd weight vanilla Xdl instances to 16x16. MRepeat doubled for all but 12 of them (some static assert failure). Also added custom reduced profiler target for building grouped conv bwd weight vanilla only profiler. Verified with gtest test."
This reverts commit d20c869d3d.
* Disable splitk for 2stage xdl on rdna (bug to be fixed)
* Fix add_test_executable
* Always ForceThreadTileTransfer for now, WaveTileTransfer does not work for convolution yet.
* Grab device and gridwise files from bkp branch, this should enable splitK support for convolution and also we no longer ForceThreadTileTransfer for explicit gemm. Also grab some updates from 7e7243783008b11e904f127ecf1df55ef95e9af2 to fix building on clang20.
* Fix bug in various bwd wei device implementations / profiler where the occupancy based split_k value could not be found because the Argument did not derive from ArgumentSplitK, leading to incorrect error tolerances.
* Actually print the reason when a device implementation is not supported.
* Print number of valid instances in profiler and tests.
* Fix clang format for Two Stage implementation
* Fix copyright
* Address review comments
* Fix explicit conv bwd weight struct
* Fix gridwise common
* Fix gridwise ab scale
* Remove autodeduce 1 stage
* Restore example tolerance calculation
* Fix compilation error
* Fix gridwise common
* Fix gridwise gemm
* Fix typo
* Fix splitk
* Fix splitk ab scale
* Adapt all grouped conv bwd weight vanilla Xdl instances to 16x16. MRepeat doubled for all but 12 of them (some static assert failure). Also added custom reduced profiler target for building grouped conv bwd weight vanilla only profiler. Verified with gtest test.
* Reduce instances to only the tuned wmma V3 ones for implicit v1 intra and explicit v1 intra pad/nopad.
* Add explicit oddMN support with custom tuned instances
* Add two stage instances based on the parameters from the tuned cshuffle V3 instances. CShuffleBlockTranserScalarPerVector adapted to 4, and mergegroups fixed to 1 for now. No more special instance lists.
* Replace cshuffle non-v3 lists with v3 lists, making sure to not have duplications. Also removing stride1pad0 support for NHWGC since we can use explicit for those cases.
* Remove some instances that give incorrect results (f16 NHWGC)
* Add bf16 f32 bf16 instances based on tuned b16 NHWGC GKYXC instances.
* Add back some generic instances to make sure we have the same shape / layout / datatype support as before the instance selection process.
* Add instances for scale and bilinear based on the bf16 NHWGC GKYXC tuning. Keep generic instances for support.
* Disable two stage f16 instances which produce incorrect results.
* Remove more instances which fail verification, for bf16_f32_bf16 and for f16 scale / bilinear.
* Disable all non-generic two-stage instances in the instance lists for NHWGC. They are never faster and support is already carried by CShuffleV3 and Explicit.
* Remove unused instance lists and related add_x_instance() functions, fwd declarations, cmakelists entries. Also merge the "wmma" and "wmma v3" instance list files, which are both v3.
* Re-enable all xdl instances (un-16x16-adapted) and dl instances. Remove custom ckProfiler target.
* Remove straggler comments
* Remove [[maybe_unused]]
* Fix clang format
* Remove unwanted instances. This includes all instances which are not NHWGCxGKYXC and F16 or BF16 (no mixed in-out types).
* Add comment
---------
Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
Co-authored-by: Kiefer van Teutem <50830967+krithalith@users.noreply.github.com>
