colabfold-legacy-kernels
Prebuilt CUDA kernels to make ColabFold fast on Volta and Turning NVIDIA GPUs. This package has three kernels that replace the Ampere+ Pallas/Triton kernels: Attention, layer norm and the gated dual projection.
import colabfold_legacy_kernels as clk
clk.available(cc=70) # True if the wheel has kernels for sm_70
clk.library_path("attention", cc=70) # path of the shared library
clk.symbol("attention", cc=70) # XLA FFI target name to register
To build the kernels, run the build script. It needs nvcc and the XLA FFI headers, and fetches CUTLASS itself.
NVCC=/usr/local/cuda-12.9/bin/nvcc scripts/build_all.sh # sm_70 and sm_75
ARCH=75 scripts/build_kernels.sh # one architecture
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