Commit Graph
15 Commits
Author SHA1 Message Date
ViperEkura c5fba9c238 perf: flatten paged prefill tile dispatch
- remove the host-provided max_q_len argument
- dispatch only the ragged prefill tile upper bound
- validate the rebuilt CUDA backend end to end
2026-08-09 23:12:53 +08:00
ViperEkura cd31f1f62f refactor: tidy attention params and launcher interfaces
- rename output pointer field o to o_ptr for consistency with q_ptr/k_ptr/v_ptr
- regroup AttentionParams fields by responsibility and fix misleading comments
- drop unused max_seq_len/total_q fields and paged decode max_seq_len arg
- drop redundant group_size param from decode launchers (computed from p)
2026-08-09 20:52:06 +08:00
ViperEkura a5a3cc1fc2 refactor: unify attention param field names
- rename q_stride_* to q_*_stride to match mask stride convention
- rename mask_q_stride to mask_l_stride for consistent l-dim naming
- merge k/v and k_cache/v_cache into k_ptr/v_ptr; rename q to q_ptr
- KVSource policy selects contiguous vs paged mode at compile time
2026-08-09 20:23:58 +08:00
ViperEkura d565d44c43 fix: harden attention kernel boundaries
- fix scalar prefill head_dim=32 out-of-bounds via G=4 dispatch
- fix MMA decode 4D mask head indexing and invalid-row mask access
- add q_head/kv_head divisibility and head-dim contiguity checks
- validate split-KV scratch and decode out_buf layout in bindings
- set max dynamic shared memory for scalar decode D=256
- cover scalar prefill D=32 in pure C test
2026-08-09 14:53:24 +08:00
ViperEkura 2667b8116d refactor: unify paged and contiguous attention kernels via KVSource policy
- merge AttentionParams and PagedAttentionParams into one struct
- add attn_kv_source.cuh with ContigKV/PagedKV addressing policies
- template prefill/decode kernels (MMA + scalar) on the KV policy, deleting the four duplicated attn_paged_*.cuh variants
- template dispatcher launchers on KV; single combine kernel
- verify: all correctness tests pass and SASS matches baseline (no perf regression)
2026-08-05 14:06:13 +08:00
ViperEkura 3067a8e1a6 feat: unify attention backend with multi-dim mask support
- Add attention() functional entry delegating to active backend
- GQA/MLA forward calls attention() instead of inline cache/SDPA
- CUDA kernels support 2D/3D/4D mask via mask_h_stride field
- CudaBackend.fwd_decode builds 2D padding mask for mixed seq_lens
- KVCache.max_len precomputed in bind_tasks to avoid GPU sync
- batch==1 decode short-circuits mask=None
- Split tests into conftest, test_backend, test_backend_equivalence, test_kernel_mask
- 440 tests pass, L20 decode 1.44-1.60x speedup vs torch native
2026-07-30 20:38:34 +08:00
ViperEkura a01e8bbe98 refactor: adopt FA2-style KernelTraits + compile-time causal/mask dispatch
- Introduce KernelTraits<HEAD_DIM, BC, WARPS, STAGES> compile-time config bundle, replacing scattered <KD, NC8, KT2, ...> template params
- Template all MMA and scalar kernels on IsCausal/HasMask bools to eliminate inner-loop runtime branches
- Dispatch to 4-path IsCausal/HasMask kernel variants at entry points based on p.causal_offset and p.use_mask
- Update standalone test files with new kernel signatures, add causal test cases
- Fix duplicate using bf16 in MMA kernels that include attn_mma_utils.cuh
2026-07-21 21:52:46 +08:00
ViperEkura 0654b4b916 refactor: template combine kernel, fix mask bug, unify dispatch
- Template combine kernel, share macros, extract entry_utils helpers
- Fix mask indexing (pass stride not pre-multiplied base)
- Remove !p.use_mask — MMA handles mask
2026-07-15 21:44:17 +08:00
ViperEkura 1f0be382ad refactor: extract load_q_mma_frags template, unify comment style
- Add load_q_mma_frags<KD>() shared template in attn_mma_utils.cuh
- Replace ~15 duplicated Q-load lines in 3 MMA kernels
- Unify section header comment style to // ---- Section ----
- Remove duplicate separator line in attn_mma_utils.cuh
2026-07-15 19:07:18 +08:00
ViperEkura 57729fd92d refactor: stride-based attn interface with layout and causal mask
- Replace is_causal + causal_offset with unified causal_offset (-1 = off, >=0 = first Q pos)
- Causal and mask can now coexist (was mutually exclusive)
- Add stride-based addressing for Q/KV/O (layout-agnostic, zero-copy)
- Add layout param ("bhld"/"blhd") parsed in Python, passed as int to C++
- Support 2D [batch, kv_len] and 3D [batch, q_len, kv_len] mask
- Vectorize paged KV gather in Python fallback (was per-token Python loop)
- Extract shared helpers: compute_num_splits, alloc_split_partials, dispatch_head_dim
- Unify paged_decode entry via attn_pack_paged_params
- Update mma_softmax_tile for 3D mask with per-row qrow indexing
2026-07-14 21:34:42 +08:00
ViperEkura 9aca62c26c perf: remove per-element sentinel checks in softmax + fix stale comments
- Replace 4*NC8 per-element -FLT_MAX comparisons with 2 row-level pn guards; masked entries naturally underflow via expf(-FLT_MAX - nm) ≈ 0; pn only guards all-masked-row edge where nm == -FLT_MAX (exp(0)=1 not 0); ~1-3% speedup on prefill (verified via standalone CUDA bench); correctness verified: prefill 4/4, decode 3/3, paged decode 13/13
- Fix stale comments: remove false 'pre-scale Q' claim, correct occupancy numbers, remove phantom sQ from smem description
2026-07-12 15:45:08 +08:00
ViperEkura b5cdea98ad refactor: remove ineffective __launch_bounds__ from prefill kernel
- Remove MIN_BLOCKS template param and __launch_bounds__ attribute
- Profiling shows smem (not registers) is the occupancy bottleneck for D>=64, making the hint a no-op
- D=64 sees 2-4% speedup, D=128 unchanged (smem-capped at 1 block/SM)
- Update comment blocks in kernel header and both dispatch sites
- Verified correctness via standalone CUDA test (max_err ~1e-4)
2026-07-12 15:00:53 +08:00
ViperEkura 8a8550184f refactor: template AttentionParams, rename .cuh to .h
- Convert AttentionParams to a template struct supporting arbitrary types
- Rename attn_common.cuh -> attn_common.h (no CUDA-specific code remains)
- Include standard headers explicitly in each .cuh instead of via attn_common.cuh
- Allow .h files in csrc/ via .gitignore
2026-07-11 11:03:14 +08:00
ViperEkura 41cd40363a perf: post-multiply attention scale in float instead of pre-scaling Q in bf16
- Replace bf16 pre-scale Q loading with direct 32-bit aligned bf16x2 reads
- Apply scale in float32 after Q@K^T, before online softmax
- Reduces causal max error from 2^-6 to 2^-8 with zero perf cost
2026-07-11 00:13:32 +08:00
ViperEkura d923ebe38d refactor: rename gqa_* to attn_*, split-KV for all decode paths
- Rename all csrc/kernels/gqa_*.cuh/cu to attn_*, with _split_q / _split_kv
  strategy suffix and optional _mma compute suffix
- Remove non-split MMA decode kernel, keep only split-KV path
- Convert scalar decode fallback to split-KV (o_part/ml_part + combine)
- Move combine kernel to attn_decode_split_kv.cuh (shared by both paths)
- Rename GQAParams to AttentionParams
- Update all C++ #include, PYBIND11, and Python extension references
2026-07-10 23:35:14 +08:00