Files
composable_kernel/test/ck_tile
Emily Martins 97ca00e449 [rocm-libraries] ROCm/rocm-libraries#7836 (commit cdd9958)
[CK Tile] Stream-K RDNA Support
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

## Motivation

Currently, CK Tile Stream-K only supports CDNA architectures. This
change adds Stream-K support on RDNA3/3.5 and RDNA4 architectures.

## Technical Details
Stream-K currently has 3 reduction strategies: 1) atomics, 2) linear,
and 3) tree. The linear and tree reductions require inter-workgroup
communication to a global flags buffer and a global partials buffer. To
ensure cache coherency, we use cache modifiers to skip cache levels that
are not visible to all workgroups. On CDNA architectures, scalar load
and scalar store instructions are available, which we use to read and
write to the flags buffer with appropriate cache skipping modifiers.
However, RDNA architectures do not support scalar store instructions, so
workgroups must use a buffer store instruction to write to flags.
Additionally, cache modifiers differ between CDNA and RDNA; they also
differ between RDNA3 and RDNA4. Given this information, the main changes
are as follows:
- Added RDNA flag signaling: Use buffer store instructions for writing
to global flags buffer
- Add appropriate cache modifiers for reading and writing to flags and
partials:
   - RDNA3 (gfx11): Use `glc | dlc` coherence flags
   - RDNA4 (gfx12): Use `DEVICE` coherence scope
- SFINAE-guarded overloads: Added compile-time dispatch for
`SignalStorePartialDone()` and `WaitStorePartialDone()` based on target
architecture
- RDNA alignment requirements: Increased flags buffer alignment from
128B to 256B due to RDNA cache line size

**A note about the `amd_buffer_coherence_enum`:**
- **Problem:** The `amd_buffer_coherence_enum` uses preprocessor
conditionals (`#if defined(__gfx12__)`) to define architecture-specific
values. Template specializations reference enum values from different
architectures (e.g., `glc_dlc` for GFX11). Due to C++ two-phase name
lookup, non-dependent names are resolved during template parsing
regardless of which architecture is being compiled, causing compilation
failures when referenced values do not exist in the active preprocessor
branch.
- **Temporary Solution**: Added compatibility enum values to each
architecture block. For example, I added `glc_dlc` in the `__gfx12__`
block. I will create a ticket to refactor this enum with a design that
has better scalability and tries to avoid the use of preprocessor
conditionals.

## Test Plan
### Summary
gtests were added to test wmma variants of Stream-K. These tests were
stressed tested locally on gfx11 and gfx12.
### More details
This PR makes the following changes/additions to the Stream-K gtests:
- Split tests into MFMA (CDNA) and WMMA (RDNA) variants
- Added 16 WMMA kernel types: FP16/BF16/FP8/BF8 × Linear/Tree reduction
- WMMA uses 16×16×16 wave tiles for RDNA (this is the only tile size
supported on RDNA)
- Fixed RDNA WGP mode: multiply multiProcessorCount by 2 for actual CU
count
- As described in [HIP
documentation](https://rocm.docs.amd.com/projects/HIP/en/docs-7.2.0/doxygen/html/group___global_defs.html#ggacc0acd7b9bda126c6bb3dfd6e2796d7ca3ac50041beb59111a5c76edf03da0898),
when in Workgroup Processor (WGP) mode, the value of
`hipDeviceAttributeMultiprocessorCount` is half of CUs, because a single
WGP contains two CUs. The default mode on RDNA is WGP mode, so when
creating (M, N, K) instances for gtests using the CU count, we need to
multiply the CU count by 2 to get the correct value. This is not needed
in the kernel host code, because the occupancy ensures that overall
`max_active_wgs` is correct.
## Test Result

All tests pass locally.

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
2026-06-08 22:48:10 +00:00
..

CK Tile Testing Guide

This document describes the test organization and available test targets for CK Tile operations.

Overview

CK Tile tests are organized with multiple levels of granularity to support different development workflows:

  1. Global test labels - Run tests across all operations
  2. Operation-specific umbrella targets - Run all tests for a specific operation
  3. Individual test executables - Run specific tests

Global Test Labels

These targets run tests across all CK operations (not just CK Tile):

ninja smoke

Run fast smoke tests (tests that complete within ~30 seconds on gfx90a).

ninja smoke

ninja regression

Run slower, more comprehensive regression tests.

ninja regression

ninja check

Run ALL available tests in the entire codebase.

ninja check

Operation-Specific Umbrella Targets

These targets allow you to run all tests for a specific CK Tile operation. This is useful when making changes to a particular operation and wanting to validate all related tests without running the entire test suite.

GEMM Operations

ck_tile_gemm_tests

Run all basic GEMM pipeline tests (memory, compute variants, persistent, etc.)

ninja ck_tile_gemm_tests

Test executables included:

  • test_ck_tile_gemm_pipeline_mem
  • test_ck_tile_gemm_pipeline_compv3
  • test_ck_tile_gemm_pipeline_compv4
  • test_ck_tile_gemm_pipeline_persistent
  • test_ck_tile_gemm_pipeline_compv6
  • test_ck_tile_gemm_pipeline_comp_async (gfx95 only)
  • test_ck_tile_gemm_pipeline_*_wmma variants (gfx11/gfx12 only)

ck_tile_gemm_block_scale_tests

Run all GEMM tests with block-scale quantization (AQuant, BQuant, ABQuant, etc.)

ninja ck_tile_gemm_block_scale_tests

Test executables included: 29 test executables covering:

  • AQuant tests (memory pipelines, base layouts, prefill, preshuffle, transpose)
  • ABQuant tests (base, padding, preshuffle)
  • BQuant tests (1D/2D variants, transpose)
  • BQuant with PreshuffleB (decode/prefill, 1D/2D)
  • BQuant with PreshuffleQuant (decode/prefill, 1D/2D)
  • RowColQuant and TensorQuant tests

ck_tile_gemm_streamk_tests

Run all GEMM StreamK tests (tile partitioner, reduction, smoke, extended)

ninja ck_tile_gemm_streamk_tests

Test executables included:

  • test_ck_tile_streamk_tile_partitioner
  • test_ck_tile_streamk_reduction
  • test_ck_tile_streamk_smoke
  • test_ck_tile_streamk_extended

ck_tile_grouped_gemm_quant_tests

Run all grouped GEMM quantization tests

ninja ck_tile_grouped_gemm_quant_tests

Test executables included:

  • test_ck_tile_grouped_gemm_quant_rowcol
  • test_ck_tile_grouped_gemm_quant_tensor
  • test_ck_tile_grouped_gemm_quant_aquant
  • test_ck_tile_grouped_gemm_quant_bquant
  • test_ck_tile_grouped_gemm_quant_bquant_preshuffleb

Other Operations

ck_tile_fmha_tests

Run all FMHA (Flash Multi-Head Attention) tests

ninja ck_tile_fmha_tests

Test executables included: Forward and backward tests for fp16, bf16, fp8bf16, fp32

ck_tile_reduce_tests

Run all reduce operation tests

ninja ck_tile_reduce_tests

Test executables included:

  • test_ck_tile_reduce2d
  • test_ck_tile_multi_reduce2d_threadwise
  • test_ck_tile_multi_reduce2d_multiblock

Individual Test Executables

You can also build and run individual test executables:

Build a specific test

ninja test_ck_tile_gemm_pipeline_mem

Run a specific test directly

./build/bin/test_ck_tile_gemm_pipeline_mem

Run a specific test through ctest

ctest -R test_ck_tile_gemm_pipeline_mem --output-on-failure