squall/flash-attention
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
684 Commits 1 Branch 0 Tags 7.9 MiB
c7f32a8409
Commit Graph

201 Commits

Author SHA1 Message Date
Tri Dao
10dad61277 apply_dropout now takes tensor of rowcol layout 2024-01-14 01:03:23 -08:00
Tri Dao
d9cbcfb41c Remove dead code in philox.cuh 2024-01-13 02:02:03 -08:00
Tri Dao
a7b66ae25a Simplify writing softmax to gmem 2024-01-13 00:25:04 -08:00
Tri Dao
8d1b169ed1 Simplify SmemLayoutVtransposed in kernel_traits.h 2024-01-12 11:53:29 -08:00
Tri Dao
abbc131173 [LayerNorm] Switch from CUDA to Triton implementation 2024-01-05 00:31:17 -08:00
Tri Dao
0842ec0da4 Don't dispatch to local if window size >= seqlen_k 2023-12-23 20:59:26 -08:00
Tri Dao
732654583c Implement deterministic backward (thanks to Meituan) 2023-12-23 17:57:36 -08:00
Tri Dao
8448c02889 Update cutlass to v3.3.0 2023-12-21 23:25:50 -08:00
Tri Dao
5ab9b3667b Clean up alibi, implement non-causal alibi 2023-12-21 22:27:40 -08:00
Sanghun Cho
e4f726fc44
Support alibi, by Sanghun Cho from Kakao Brain 
* hard-code alibi in fwd

* use params.h as hun_heads

* hard-code alibi in bwd

* add alibi on/off option

* compute alibi_start, ratio outside of kernels

* fix minor merge conflict

* add test_alibi.py

* change apply_alibi() location before masking

* add alibi in splitkv kernel

* fix backward func # of returns

* add out-of-bound check in apply_alibi()

* update test_alibi.py

* update test_alibi.py for kvcache

* simplify alibi parameter interface

* fix performance issue
by computing alibi outside of branch

* update test_flash_attn_varlen_func() for left padding

* implement alibi_slopes (b, nh) loading

* optimize apply_alibi() a bit

* update test cases for alibi_slopes loading

* reflect stylistic comments

* disable "seqlenq_ngroups_swapped" when using alibi

---------

Co-authored-by: monk.detective <monk.detective@kakaobrain.com>
 2023-12-19 22:56:06 -08:00
Jeremy Reizenstein
ce3e7280f8
Allow varlen_fwd to take optional seqused_k (#647) 
Co-authored-by: bottler <bottler@users.noreply.github.com>
 2023-11-27 00:41:23 -08:00
Tri Dao
b4bf9cc1f3 Fix performance regression with causal 2023-11-26 19:07:25 -08:00
Tri Dao
db2f80692c Write zero to out / grad if seqlen_q or seqlen_k is zero 2023-11-19 22:20:01 -08:00
Tri Dao
43bb6d8aaa Update cutlass to 3.2.2 2023-11-19 21:43:48 -08:00
Driss Guessous
dc4b9ad6c4
add checks (#640) 2023-11-19 20:43:27 -08:00
Tri Dao
5a83425442 Change constexpr int to constexpr static int 2023-10-08 16:26:33 -07:00
Tri Dao
e279bf8ed9 [Gen] Accept cache_batch_idx to index into the KV cache 2023-10-03 16:27:26 -07:00
Tri Dao
083e8f525f Implement local attention 
Co-authored-by: Timothee Lacroix <t@mistral.ai>
 2023-09-26 16:31:08 -07:00
Tri Dao
812cb1c990 Switch cutlass to newer commit to avoid compilation warning 2023-09-24 00:42:50 -07:00
Tri Dao
65c234ed90 Don't over-allocate dq_accum in case of varlen 2023-09-24 00:36:07 -07:00
Tri Dao
1879e089c7 Reduce number of templates for headdim > 128 2023-09-23 22:24:30 -07:00
Tri Dao
2d8ea9a530 Swap seqlen_q and ngroups when seqlen_q=1 (h/t Daniel Haziza) 2023-09-20 23:38:22 -07:00
Tri Dao
dfe29f5e2b [Gen] Don't use ft_attention, use flash_attn_with_kvcache instead 2023-09-18 15:29:06 -07:00
Tri Dao
3250ff3d82 Swap seqlen_q, nheads for MQA when seqlen_q=1 for fwd (h/t Daniel H) 2023-09-18 14:52:16 -07:00
Tri Dao
43617deab9 Remove template for (IsEvenMN=T, IsEvenK=F) to speed up compilation 2023-09-18 12:21:36 -07:00
Tri Dao
c984208ddb Set block size to 64 x 64 for kvcache to avoid nvcc segfaults 2023-09-17 16:14:58 -07:00
Tri Dao
ccbb14f38e Implement rotary embedding in flash_attn_with_kvcache 2023-09-16 01:20:16 -07:00
Tri Dao
5400fdc4ac [CE] Implement CrossEntropyLoss in Triton 2023-09-15 20:05:28 -07:00
Tri Dao
56b7fc6ee0 Simplify the implementation of KVcache attn by appending KV first 2023-09-13 15:55:48 -07:00
Tri Dao
bb9beb3645 Remove some unused headers 2023-09-12 12:37:10 -07:00
Tri Dao
ee77b931b9 Swap seqlen_q and nheads for MQA to speed it up (h/t Daniel Haziza) 2023-09-10 22:56:33 -07:00
Tri Dao
37c6e05406 Implement flash_attn_with_kvcache 2023-09-04 00:11:44 -07:00
Tri Dao
6a89b2f121 Remove constexpr in launch template to fix CI compilation 2023-09-03 22:59:41 -07:00
Tri Dao
97ba7a62e9 Try switching back to Cutlass 3.2.0 2023-09-03 22:45:35 -07:00
Tri Dao
1dc1b6c8f2 Bump to v2.1.2 2023-09-03 22:23:05 -07:00
Tri Dao
5953c4f58c Remove unused sdPsum in dot_do_o function 2023-09-03 20:44:07 -07:00
Tri Dao
26d7d92f3d Fix splitKV combine function when local LSEs are all -inf 2023-09-03 11:39:09 -07:00
Sophia Wisdom
37e32febba
Remove commented out code in bwd (#512) 
* Remove lots of comments

* Remove unused traits
 2023-09-01 16:43:58 -07:00
Sophia Wisdom
dd8a754915
Remove old code in utils.h (#511) 2023-09-01 15:32:09 -07:00
Aman Gupta Karmani
866a9d33f9
bump cutlass submodule (#504) 2023-08-30 10:32:04 -07:00
Tri Dao
31920dda5f Fix typo with lse_max == -INFINITY 2023-08-29 21:48:59 -07:00
Tri Dao
b1fbbd8337 Implement splitKV attention 2023-08-29 00:58:29 -07:00
Tri Dao
7a983df742 Use generate_kernels.py script from Driss Guessous 2023-08-28 13:34:12 -07:00
dan_the_3rd
c3f2a632aa
[ft_attention] Fix for seqlen=8136 (#488) 
When seqlen=8136, `smem_sz = 48840`, and apparently starting the kernel returns an `invalid argument` CUDA error.

`48840 < 48 * 1024` but apparently it's still above the limit somehow..?
Tested on A100
 2023-08-28 10:00:22 -07:00
Tri Dao
757058d4d3 Update Cutlass to v3.2.0 2023-08-27 23:47:28 -07:00
Tri Dao
9e5e8bc91e Change causal mask to be aligned to bottom-right instead of top-left 2023-08-24 23:41:07 -07:00
BoxiangW
e07aa036db
Support flash attention 2 with causal masking when KV's seq length is longer than Q's seq length. (#436) 2023-08-24 16:42:34 -07:00
Tri Dao
bcfa7c9751 [FusedDense] Run black on fused_dense.py 2023-08-16 23:41:36 -07:00
Tri Dao
c65b5106ac Fix Bwd NaN for varlen when seqlen_q >> seqlen_k and causal 2023-08-16 15:12:36 -07:00
Tri Dao
dbd7923782 Prepare for Cutlass 3.2 2023-08-13 15:24:32 -07:00
Tri Dao
3524e13c11 Update to Cutlass 3.1 2023-08-13 13:53:17 -07:00
Tri Dao
1c41d2b0e5 Fix race condition in bwd (overwriting sK) 2023-08-01 09:00:10 -07:00
Tri Dao
a4f148b6ab Fix masking of bwd when seqlen is not divisible by 128 2023-07-31 17:46:34 -07:00
Kirthi Shankar Sivamani
a03f6f8e9e
Enable CUDA graphs (#386) 
* Add RNG state to kernel launch params

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Save seed and offset for backward

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Single thread write to global mem

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* compute_dq_dk_dv_1colblock get seed and offset from launch params

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* compute_dq_dk_dv_1rowblock get seed and offset from launch params

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Change forward c++ APIs to save RNG state for backward

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Change backward c++ APIs to set RNG state for bprop launcher

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Bug fixes

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Python side API changes

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Bug fix; only save seeds instead of full offset

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Account for 3D grid size

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
 2023-07-27 16:11:34 -07:00
Joel Lamy-Poirier
767b71ccf0
Fix random state for dropout_layer_norm (#315) 2023-07-23 15:05:13 -07:00
Tri Dao
a157cc8c9b [FT] Implement MQA/GQA 2023-07-22 23:47:01 -07:00
Tri Dao
9ee0ff1d9b Fix using dO stride for O, which can cause memory error in bwd 2023-07-20 17:39:57 -07:00
Ikko Eltociear Ashimine
dfc60f6b7d
[LayerNorm] Fix typo in ln_api.cpp 
unintialized -> uninitialized
 2023-07-20 01:16:16 +09:00
danthe3rd
538d570c96 Fix compile error on MSVC 
See also: https://stackoverflow.com/questions/55136414/constexpr-variable-captured-inside-lambda-loses-its-constexpr-ness
 2023-07-19 08:04:57 +00:00
Tri Dao
4f285b3547 FlashAttention-2 release 2023-07-17 06:21:34 -07:00
Tri Dao
2800efc71f [FT] rotary_cos/sin should have batch_size dimension 2023-07-06 15:33:33 -07:00
Tri Dao
3a9bfd076f [FT] rotary_cos/sin should have shape (dim) instead of (seqlen, dim) 2023-07-03 09:41:04 -07:00
Tri Dao
62e9814466 [Rotary] Make sure frequency calculation is in fp32 2023-07-02 16:39:39 -07:00
Tri Dao
27f8f890df [FusedDense] Allocate lt_workspace on input device 2023-05-30 14:17:26 -07:00
Tri Dao
48bc6eacd6 [Gen] Add rotary base as an argument to FT attention kernel 2023-05-30 13:38:34 -07:00
Tri Dao
ad113948a6 [Docs] Clearer error message for bwd d > 64, bump to v1.0.4 2023-04-26 09:19:48 -07:00
Tri Dao
311d6606bf [Gen] Fix FT kernel smem size, CG when batch size changed 2023-04-20 17:03:13 -07:00
Kirthi Shankar Sivamani
45567a25a2 only 1 thread writes to global mem in fprop 
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
 2023-04-15 06:09:41 +00:00
Kirthi Shankar Sivamani
7d25a4ec4f Handle FlashAttnQKVPackedSplitFunc by making rng_state optional in backward 
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
 2023-04-13 06:25:52 +00:00
Kirthi Shankar Sivamani
315fd31f0c
Merge branch 'HazyResearch:main' into enable_cuda_graph_capture 2023-04-12 22:42:24 -07:00
Kirthi Shankar Sivamani
31018c5fa0 Support CUDA graph capture 
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
 2023-04-12 16:53:22 -07:00
Tri Dao
dec4f2e910 [FusedDense] Set workspace size to 32M for Hopper and 4M for others 2023-04-06 23:40:15 -07:00
Tri Dao
393882bc08 [LayerNorm] Implement LN with parallel residual, support dim 8k 2023-03-31 14:23:45 -07:00
Tri Dao
f5d0fbd468 [FT] Fix FT's single query attention for bf16 hdim128 rotary 2023-03-28 21:27:00 -07:00
Tri Dao
dc08ea1c33 Support H100 for other CUDA extensions 2023-03-15 16:59:27 -07:00
Tri Dao
1b18f1b7a1 Support H100 2023-03-15 14:59:02 -07:00
Tri Dao
e45a46a5b7 [Rotary] Implement GPT-J style (interleaved) rotary 2023-03-14 14:35:53 -07:00
Tri Dao
6b4a48218e [FA] Remove unused variable rng_engine_inputs 2023-01-25 15:32:40 -08:00
Tri Dao
eb33e587e9 [LayerNorm] Rename x1 -> residual 2023-01-19 13:07:27 -08:00
Tri Dao
88173a1aaf [FusedDense] Support relu, rename FusedDenseGeluDense -> FusedMLP 2023-01-17 18:12:27 -08:00
Tri Dao
f1e01c27ba [Gen] Pass qkv_stride to ft_attention kernel for batched generation 2023-01-15 15:20:01 -08:00
Tri Dao
7c2191542a [Gen] Make generation work with Tensor Parallel 2023-01-15 11:34:27 -08:00
Tri Dao
6738d9477d [LayerNorm] Implement RMS Norm 2023-01-06 17:34:22 -08:00
Tri Dao
a1f49a2b92 [Compilation] Change BOOL_SWITCH to fix Windows compilation 
Follow xFormers's DISTPATCH_BOOL. Haven't tested it on Windows.
 2023-01-06 14:40:58 -08:00
Tri Dao
be1afaa276 [Gen, FT] Use fp32 accum for FMA 2023-01-03 22:09:22 -08:00
Tri Dao
f266fc7262 [Gen, FT] Use tlength instead of params.timestep for rotary 2023-01-03 17:46:55 -08:00
Tri Dao
a01d1213d7 [Gen] Add kernel from FasterTransformer for benchmarking 2023-01-03 17:37:43 -08:00
Tri Dao
a8cfe51551 Implement Tensor Parallel for transformer Block 2022-12-25 14:08:21 -08:00
Tri Dao
1e712ea8b0 Implement TensorParallel for MHA 2022-12-25 11:39:55 -08:00
Tri Dao
226a1b721d Implement TensorParallel for FusedDense and FusedDenseGeluDense 2022-12-24 11:48:56 -08:00
Tri Dao
dff68c2b22 Add smoothing for CrossEntropyParallel, rename to CrossEntropyLoss 2022-12-23 14:51:08 -08:00
Tri Dao
e68ebbe89a Simplify FusedDense 2022-12-22 21:25:31 -08:00
Tri Dao
5db330519a [LayerNorm] Support taking subset of input or subset of output 2022-12-12 22:16:14 -08:00
Tri Dao
ae137ed17a [LayerNorm] Fuse LayerScale 2022-12-10 23:28:23 -08:00
Tri Dao
8c6609ae1a [LayerNorm] Support all dimensions up to 6k (if divisible by 8) 2022-12-09 02:06:22 -08:00
Tri Dao
8a2ece89f7 Simplify BOOL_SWITCH macro to fix compiling error on gcc 7 2022-12-06 14:38:32 -08:00
Tri Dao
0bf5e50038 Release training code 2022-11-28 17:34:40 -08:00
Tri Dao
9bc63d1e2d Fix typo in comments 2022-11-25 16:35:08 -08:00
Tri Dao
d95ee1a95d Speed up compilation by splitting into separate .cu files 2022-11-25 16:30:18 -08:00
Tri Dao
39ed597b28 [LayerNorm] Compile for both sm70 and sm80 2022-11-17 11:45:11 -08:00