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feat: CK Tile unification - swizzle support + gfx950 mixed prec scale + misc (#8315) ISSUE ID #8960 https://github.com/ROCm/rocm-libraries/issues/8960 ## Motivation This MR is about adding Swizzle support to the Tile Distribution Encoding Calculator and Mma Pipelines in the Unification framework. Swizzle is a modifier for Tile Distribution Encodings that effectively performs a permutation in the M dimension. This means that it affects the Tile Distribution Encodings of A and C. When combined with CTranspose, it affects the Encodings of B and C instead. In principle, for a regular gemm, the Swizzle factor does not affect the correctness of the kernel, since matrix multiplication is symmetric under permutations of rows and columns (M). However, this is only true if the same Encodings are used for the loading and storing of the data. For consecutive matrix multiplications, we may be in a situation where we use Swizzle to account for the effective layout of an intermediate result, so that it can immediately be used in another matrix operation without additional shuffling. In these cases, the Swizzle factor is crucial for correctness. As far as I know, this seems most likely to occur in attention kernels. ### Changes - I adapted the Tile Distribution Encoding Calculator to accept any Swizzle modifier, and use this to modify the layouts just like in CK Tile. Note that Swizzle is only compatible with certain intrinsics, due to the restriction that the Swizzle factor divides kCMNumAccess. This is possible for 32x32 MFMA instructions with SFactor 2 or 4, and for gfx11 WMMA instructions with SFactor 2, 4, or 8, although this is not used in CK Tile. - I adapted the layout test to check the correctness of layout *with* Swizzle modification, for all possible Swizzle factors for each intrinsic. - I adapted the Unification Dispatcher to take a Swizzle Factor and pass it on to the MmaPipelines. Note that the original dispatcher takes a boolean instead, which I convert to an SFactor of 2 when true. I believe this is correct since in all cases where CK Tile previously used the old dispatcher, and SFactor of 2 ended up being used. However, there are two named WarpGemms (WarpGemmMfmaFp8Fp8F32M32N32K32SwizzleBTransposedCDistribution and WarpGemmMfmaI8I8I32M32N32K32SwizzleBTransposedCDistribution) which can support any Swizzle factor, and are actually used with Swizzle factors up to 4. These were not used in the old dispatcher but instead always used directly in CK Tile pipelines. - I added custom named WarpGemms in case the Unification flag is ON, for the named WarpGemms using Swizzle that are directly used in CK Tile pipelines. There are only two of them and they are the ones mentioned in the previous point. ### Changes part 2 While trying to get a swizzle example to work, I ended up having to add a lot of other changes which would have normally been their own issue. We have: - Adding all mixed precision gfx950 scale intrinsics (50 in total) - Adding these intrinsics to the layout test - Tile distribution encoding tweak: Allow for simplified C layouts in blockless cases - MmaPipelines tweaks: Make pretty much all old-style layout params available ### Note on AttrNumAccess For the scale gfx950 intrinsics, the "canonical" layouts for A and B have NumAccess 1 or 2, depending on the A and B types. The 8-bit types have a canonical NumAccess of 2, and the others 1. So overall we may have (1, 1), (2, 1), (1, 2), or (2, 2). This is reflected in the intrinsic definitions. However, for the fully 8-bit intrinsics I still define them with (1, 1). The reason for this is that it is in principle possible to use these intrinsics with (1, 1) as long as you don't use scale. This may actually happen in CK Tile. Furthermore, there are some pipelines that instantiate a WarpGemm with (1, 1) just to peek at some parameters. Note that the (1, 2) and (2, 1) cases MUST have these NumAccess values or the base MMA does not work (regardless of scale). This is because you can't just permute K for A without doing the same for B and vice versa. ### Tests Layout tests with swizzle work. tile_example_fmha_fwd and tile_example_fmha_bwd now compile and run, with correct verification for default settings. With fp8bf16 and init=3, get 5% wrong results on both this branch and develop, and this one is definitely sensitive to swizzle, because without swizzle it's 50% wrong. Better test: test_ck_tile_fmha_fwd_fp8bf16. This one behaves as expected and confirms that swizzle is genuinely necessary for correctness and working properly in the unification framework. It passed on develop and on my this branch with unification on, and failed when I forced a swizzlefactor of 1 (failed 40 out of 43 unskipped tests).
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:
- Global test labels - Run tests across all operations
- Operation-specific umbrella targets - Run all tests for a specific operation
- 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_memtest_ck_tile_gemm_pipeline_compv3test_ck_tile_gemm_pipeline_compv4test_ck_tile_gemm_pipeline_persistenttest_ck_tile_gemm_pipeline_compv6test_ck_tile_gemm_pipeline_comp_async(gfx95 only)test_ck_tile_gemm_pipeline_*_wmmavariants (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_partitionertest_ck_tile_streamk_reductiontest_ck_tile_streamk_smoketest_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_rowcoltest_ck_tile_grouped_gemm_quant_tensortest_ck_tile_grouped_gemm_quant_aquanttest_ck_tile_grouped_gemm_quant_bquanttest_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_reduce2dtest_ck_tile_multi_reduce2d_threadwisetest_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