 Tri Dao
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f86e3dd919
[CI] Use MAX_JOBS=1 with nvcc 12.3, don't need OLD_GENERATOR_PATH
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hai 1 semana |
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Tri Dao
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9375ac9322
[CI] Don't include <ATen/cuda/CUDAGraphsUtils.cuh>
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hai 1 semana |
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Tri Dao
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073afd5931
[CI] Use torch 2.6.0.dev20241001, reduce torch #include
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hai 1 semana |
 Michael Melesse
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b518517cb8
[AMD] Triton Backend for ROCm (#1203)
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hai 1 semana |
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Tri Dao
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241c682c9f
[CI] Switch back to CUDA 12.4
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hai 1 mes |
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Tri Dao
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6ffeb572b1
[CI] Still use CUDA 12.3 but pull the right pytorch version
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hai 1 mes |
 Ethan Steinberg
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42f2b8be34
Use CUDA 12.4 in the build system (#1326)
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hai 1 mes |
 rocking
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e2182cc21d
Support page kvcache in AMD ROCm (#1198)
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hai 3 meses |
 juejuezi
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e371bea04f
feat: change minimal supported CUDA version to 11.7 (#1206)
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hai 3 meses |
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Tri Dao
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65f723bb9a
Split bwd into more .cu files to speed up compilation
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hai 4 meses |
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Tri Dao
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751c762c9c
Don't specialize for hdim 224 to speed up compilation
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hai 4 meses |
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rocking
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d8f104e97a
Support AMD ROCm on FlashAttention 2 (#1010)
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hai 4 meses |
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Tri Dao
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844912dca0
[CI] Switch from CUDA 12.2 to 12.3
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hai 5 meses |
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Tri Dao
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908511b2b6
Split into more .cu files to speed up compilation
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hai 5 meses |
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Tri Dao
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beb2bf2a32
Drop support for pytorch 1.12, 1.13, and python 3.7
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hai 5 meses |
 Nicolas Patry
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8f873cc6ac
Implement softcapping. (#1025)
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hai 5 meses |
 Corey James Levinson
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beb8b8ba9f
add exception to Timeout Error (#963)
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hai 6 meses |
 Wei Ji
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9c0e9ee86d
Move packaging and ninja from install_requires to setup_requires (#937)
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hai 7 meses |
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Tri Dao
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2aea958f89
[CI] Compile with torch 2.3.0.dev20240207
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hai 8 meses |
 Arvind Sundararajan
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26c9e82743
Support ARM builds (#757)
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hai 9 meses |
 Chirag Jain
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50896ec574
Make nvcc threads configurable via environment variable (#885)
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hai 9 meses |
 Qubitium
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f45bbb4c94
Optimize compile to 1: avoid oom 2: minimize swap usage 3: avoid threads starvation when letting ninja decide how many workers to spawn or manual MAX_JOBS "guesses". Logic is to take the min value of MAX_JOBS auto-calculated by two metrics: 1: cpu cores 2: free memory. This should allow flash-attn to compile close to the most efficient manner under any consumer/server env. (#832)
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hai 10 meses |
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Tri Dao
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d4a7c8ffbb
[CI] Only compile for CUDA 11.8 & 12.2, MAX_JOBS=2,add torch-nightly
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hai 1 ano |
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Tri Dao
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5e525a8dc8
[CI] Use official Pytorch 2.1, add CUDA 11.8 for Pytorch 2.1
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hai 1 ano |
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Tri Dao
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1879e089c7
Reduce number of templates for headdim > 128
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hai 1 ano |
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Tri Dao
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bff3147175
Re-enable compilation for Hopper
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hai 1 ano |
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Tri Dao
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dfe29f5e2b
[Gen] Don't use ft_attention, use flash_attn_with_kvcache instead
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hai 1 ano |
 Federico Berto
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fa3ddcbaaa
[Minor] add nvcc note on bare_metal_version `RuntimeError` (#552)
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hai 1 ano |
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Tri Dao
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799f56fa90
Don't compile for Pytorch 2.1 on CUDA 12.1 due to nvcc segfaults
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hai 1 ano |
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Tri Dao
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bb9beb3645
Remove some unused headers
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hai 1 ano |
