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* refactor: merge test CI workflow files into one * chore: set `UV_INDEX_STRATEGY=unsafe-best-match` * feat: add AST test with Python 3.8 * feat: implement manual caching mechanism for self-hosted runners * refactor: simplify cache logic for self-hosted runners * chore: clear uv cache on failure * chore: print format.sh output to logs * chore: improve uv caching * chore: disable parallel test * chore: use `PYTHONDEVMODE=1` in CI * feat: enable coredump generation * fix: fix perfbench condition * Revert "feat: enable coredump generation" This reverts commitc52da65cb5. * chore: move example CI down * Revert "chore: move example CI down" This reverts commit9d8e65055e. * chore: skip example `test_example_mha_sink_bwd_bhsd` * chore: skip example `test_example_gqa_sink_bwd_bhsd` * fix: fix example argument passing * fix: loosen test criteria * chore: rename `CMAKE_CONFIGURE_OPTIONS` -> `CLANG_TIDY_CMAKE_OPTIONS` for clarity * feat: enable parallel testings * chore: update pytest options * remove skipped test as now been resolved * chore: empty commit to re-trigger ci * test for n 1 * chore: remove ` --numprocesses=1` option in example * chore: disable failfast * chore: update cibw selection * fix: fix git submodule clone * chore: update cibw commands * fix: fix yapf multiprocessing * chore: setup ccache for CIBW on macOS only * chore: update comments * chore: update artifact listing * fix: do not fail if not found nvcc in PATH * fix: fix flash-attn installation * chore: update dist workflow trigger * chore: remove outdated comments * chore(workflows/dist): simplify build matrix strategy * fix: fix CUDA path finding * fix: fix CUDA path finding * chore: imcrease CI timeout * ci: disable failfast * fix: hide path prefix * chore: more verbose * chore: disable PR trigger for dist workflow * fix: seed for tests * fix: use nightly torch for ROCm tests * chore: enable PR trigger for dist workflow * chore: stop uploading debug wheels as artifacts in PR * chore: do not run workflows in forks * chore: housekeep requirements * chore: use Nightly-ROCm-6.3 for CI * chore: use Nightly-ROCm-6.4 for CI * Update ROCm toolkit version to 7.0 * chore: restore previous rocm-ci.yml for test * fix: cleanup PYTHONPATH * chore: remove previous rocm-ci.yml * ci fix * chore: remove previous rocm-ci.yml * chore: enable parallel example run --------- Co-authored-by: LeiWang1999 <leiwang1999@outlook.com> Co-authored-by: alex_xiao <xinyuxiao2024@gmail.com>
Dequantization GEMM
An example of implementing a dequantization GEMM:
@T.prim_func
def dequant_matmul(
A: T.Tensor(A_shape, in_dtype),
B: T.Tensor(B_shape, storage_dtype),
Ct: T.Tensor((N, M), out_dtype),
):
with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=threads) as (bx, by):
A_shared = T.alloc_shared(A_shared_shape, in_dtype)
B_shared = T.alloc_shared(B_shared_shape, storage_dtype)
B_local = T.alloc_fragment(B_shared_shape, storage_dtype)
B_dequantize_local = T.alloc_fragment(B_dequantize_shared_shape, in_dtype)
Ct_local = T.alloc_fragment((block_N, block_M), accum_dtype)
T.clear(Ct_local)
for k in T.Pipelined(
T.ceildiv(K, block_K),
num_stages=num_stages
):
T.copy(A[by * block_M, k * block_K], A_shared)
T.copy(B[bx * block_N, k * block_K // num_elems_per_byte], B_shared)
T.copy(B_shared, B_local)
for i, j in T.Parallel(block_N, block_K):
B_dequantize_local[i, j] = _tir_packed_to_unsigned_convert("int", 8)(
num_bits,
B_local[i, j // 2],
j % 2,
dtype=in_dtype,
)
T.gemm(B_dequantize_local, A_shared, Ct_local, transpose_B=True)
T.copy(Ct_local, Ct[bx * block_N, by * block_M])
Notes: Dequantize GEMM with magic layout transformations to get optimal performance can be found at project BitBLAS, example kernels can be found at testing/python/kernel/test_tilelang_dequantize_gemm.py, detailed explanation and examples is coming soon.