[CK Tile Engine] Daily tier sampling for tile engine GEMM (#7311)
Summary
- Replace uniform random instance sampling (random.shuffle) with
scrambled Sobol + Latin Hypercube + maximin space-filling
sampling, per the Tile Engine Benchmark Sampling RFC
- Add op-weighted budget allocation via new
TILE_ENGINE_SAMPLING_TIER=daily CMake knob that auto-distributes 8,000
instances across
ops proportional to registered weights in op_weights.json
- Emit chosen_instances.json manifests for reproducibility tracking
- Consolidate 5 copies of sampling logic into single _apply_sampling()
method on the base class
Jenkinsfile changes
Replace per-op -D *_MAX_INSTANCES=250 with single -D
TILE_ENGINE_SAMPLING_TIER=daily in gfx942/gfx950/gfx1201 stages. Budget
auto-distributes (8000 total per GPU target).
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Co-authored-by: Claude Sonnet 4 <noreply@anthropic.com>
[CK] [CK_Tile] Add FMHA scaffolding to CK kernel dispatcher (#5260)
## Motivation
The CK Tile dispatcher currently supports GEMM and Grouped Convolution
but has no support for Fused Multi-Head Attention (FMHA). The
example/ck_tile/01_fmha folder contains a comprehensive FMHA
implementation with forward, backward, split-KV, paged-KV, append-KV,
and batch-prefill kernels across multiple GPU architectures — but there
is no unified dispatch layer for it. This PR ports the FMHA stack into
the dispatcher, following the same architectural patterns established by
GEMM and Grouped Convolution, enabling runtime kernel selection, JIT
compilation from Python, and a declarative C++ example flow. Autotuning
heuristics to follow.
## Technical Details
This PR adds FMHA scaffolding to the CK dispatcher framework, mirroring
GEMM's layered architecture. Seven new C++ runtime headers provide type
definitions (coexisting with upstream headers via __has_include,
requiring zero modifications to example/ck_tile/01_fmha/), a problem
builder with 18+ setters, Signature + Algorithm kernel key matching, a
virtual kernel instance, a DECL_FMHA_KERNEL_SET macro with wildcard
support and named tile/wave/warp setters, arch-aware registry with JSON
export, and a dispatcher with seqtune-aware selection, configurable
timing, and multi-stage execution plans for split-KV (two-stage) and
backward (three-stage). The codegen pipeline is driven by a
fmha_arch_specs.json capturing per-arch tile tables and pipeline
constraints for five architectures (gfx90a/942/950/1100/1201), migrated
from hardcoded logic in 01_fmha/codegen/, with supporting modules for
C++ symbol mappings, validation rules, and named receipt profiles
(ck_default, flash, pytorch, aiter, fp32, fp8). Python integration
(fmha_utils.py) mirrors the C++ layer with JIT compilation, parallel
multi-kernel builds, HIP memory management via ctypes, tolerance-based
validation, and a NumPy CPU reference with GQA support. Twenty-seven C++
and thirty-two Python examples cover the full feature surface — forward,
split-KV, masks, bias, dropout, GQA, backward, append-KV, batch prefill,
fp8, logits soft cap, sink tokens, and parameter sweeps — all
JIT-compiled on the fly.
## Test Plan
Seven test files cover the runtime types, codegen, and end-to-end
correctness. C++ unit tests validate the problem builder, dispatcher
planning (single-stage for forward/paged-KV/append-KV; multi-stage for
split-KV and backward), registry operations, and the kernel-set
declaration macro. Python unit tests verify codegen emission, profile
filtering, and 15 validation rules for masks, hdim constraints, and
pipeline requirements. GPU execution validation in 01_basic_fmha
--validate reports zero errors across 65,536 elements with max absolute
error of 7.29e-05. A gold-standard parity suite (test_fmha_parity.py)
runs 14 configurations through both the upstream tile_example_fmha_fwd
and the dispatcher, comparing exit codes to confirm behavioral parity —
all 14 match.
## Test Result
The C++ smoke test builds and passes all 9 compiled examples, and a
Python JIT sweep (29_sweep_seqlen.py) passes 7/7 configurations reaching
up to 375 TFLOPS at seqlen 2048.
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
---------
Co-authored-by: Yaswanth Raparti <113389104+yraparti@users.noreply.github.com>
Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com>
Co-authored-by: Maksim (Max) Podkorytov <Maksim.Podkorytov@amd.com>
Co-authored-by: yashagar <yashagar@amd.com>
[CK_TILE] Restructure Tile Engine's benchmarking and profiling (#4769)
## Motivation
This PR introduces a restructure for the benchmarking and profiling
aspects of CK Tile's Tile Engine, expanding on the groundwork from this
previous https://github.com/ROCm/composable_kernel/pull/3434 and
outlined in this [design
document](https://amdcloud-my.sharepoint.com/:w:/r/personal/astharai_amd_com/Documents/Restructuring%20Tile%20Engine.docx?d=w14ea28a30718416988ed5ebb759bd3b2&csf=1&web=1&e=l3VBuX).
In PR 3434, to reduce repeated code we implemented:
- Base class that centralizes common functionality and provides a
default implementation (Universal GEMM)
- Child classes for GEMM variants override virtual functions to handle
variant-specific behavior
This refactoring in this PR follows the same process and should greatly
reduce the duplicated code present in Tile Engine and make it simpler to
add in new operations, increasing scalability.
## Technical Details
The files have been refactored around new base structs for benchmarks,
profiling and problem descriptions. The new base structs are:
- GemmProblem
- GemmBenchmark
- GemmProfiler
Universal GEMM, Preshuffle GEMM, and Multi-D GEMM all have child classes
that will inherit from these base structs overriding only what differs
per variant.
All common functions across the benchmarking and profiling files have
been moved into newly added common utility files under the commons/
directory. The new utility files are:
- utils.hpp: common functions for the benchmarking and profiling process
- benchmark_utils.py: common utility functions for the benchmark
generation
## Test Plan
I tested using the existing tests for Tile Engine.
## 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.
[CK][CK_Tile] Ensure CK Tile engine benchmarking targets are excluded from default build. (#6135)
## Motivation
Ensuring that tile engine benchmarking does not build by default and
slow other developers.
## Technical Details
- Added EXCLUDE_FROM_ALL to all add_subdirectory calls in
tile_engine/CMakeLists.txt and ops/gemm/CMakeLists.txt, so none of the
tile engine ops targets are part of the default all build.
- Added missing EXCLUDE_FROM_ALL to add_executable in
ops/pooling/CMakeLists.txt and ops/reduce/CMakeLists.txt (the GEMM
variants already had it).
- Downgraded message(STATUS ...) to message(VERBOSE ...) (or DEBUG for
per-target creation) in ops/pooling/, ops/gemm_streamk/, and ops/reduce/
CMakeLists. The other four GEMM variants (gemm_universal, gemm_multi_d,
gemm_preshuffle, grouped_gemm) already used VERBOSE.
- Targets can still be built on demand via their aggregate names (e.g.
make benchmark_pooling_all, make benchmark_gemm_streamk_all).
## Test Plan
Tile engine benchmark testing stage should be unaffected.
## Test Result
N/A
## Submission Checklist
- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
[CK_TILE] Add pooling in tile_engine (#4469)
## Motivation
<!-- Explain the purpose of this PR and the goals it aims to achieve.
-->
Add pooling in ck tile engine
## 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.
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Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
* WIP
* Add Unit tests for the Multi Reduction Kernel
* clang format
* Rename multiblock to threadwise
* Multiblock WIP
* Fix multi reduce multi block unit tests
* Multi Reduce Tile Engine: WIP
* refactoring + try addressing precision error
* Fix multiops examples
* Cleanup
* Clean up tile engine's reduce op
* Update changelog
* Fix remod/clang
* Fix dates
* Fix documentation & missing file
* Fix comments
* Use the update_tile api in the multi-block kernel
* Unify threadwise/multiblock into a single kernel + default multiblock output to float in tests
* Add TileParitioner
* Cleanup
* Add warning when no data to process, in the example
* Refactoring Reduce kernel Tile Partioner + cleanup
* Move the tile partioner to its own file
* Add missing includes
* Fix copyright header with update_amd_copyright_headers.py
* Fix change of interface in Reduce2dProblem
---------
Co-authored-by: Damien Lejeune <damien.lejeune@amd.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
* New branch for codegen changes
* Fix verify function for int4
* pk_int4 codegen
* Update to review comments
* Remove codegen directory and rename filenames
* Remove extra files; clean up CMake file
* New branch for codegen changes
* Fix verify function for int4
* pk_int4 codegen
* Update to review comments
* Remove codegen directory and rename filenames
* Remove extra files; clean up CMake file
* code changes for single instance
* config file rename, added few more combinations in json file
* Fix cmake file
* Addressing review comments
* Reverting files changed by merge to develop
---------
Co-authored-by: ThomasNing <thomas.ning@amd.com>
