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Add support for FP8 on compute capability >=8.0, <8.9 #2213

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merged 1 commit into from
Jul 11, 2024
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Add support for FP8 on compute capability >=8.0, <8.9 #2213

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15 changes: 15 additions & 0 deletions server/marlin/marlin_kernels/__init__.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -59,3 +59,18 @@ def marlin_gemm(
Matrix multiplication using Marlin kernels.
"""
...

# fp8 marlin
def fp8_marlin_gemm(
a: torch.Tensor,
b_q_weight: torch.Tensor,
b_scales: torch.Tensor,
workspace: torch.Tensor,
num_bits: int,
size_m: int,
size_n: int,
size_k: int,
) -> torch.Tensor:
return torch.ops._C.fp8_marlin_gemm(
a, b_q_weight, b_scales, workspace, num_bits, size_m, size_n, size_k
)
2 changes: 2 additions & 0 deletions server/marlin/marlin_kernels/ext.cpp
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Expand Up @@ -9,4 +9,6 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("gptq_marlin_repack", &gptq_marlin_repack,
"Repack GPTQ parameters for Marlin");
m.def("marlin_gemm", &marlin_gemm, "Marlin gemm");
// fp8_marlin Optimized Quantized GEMM for FP8 weight-only.
m.def("fp8_marlin_gemm", &fp8_marlin_gemm);
}
5 changes: 5 additions & 0 deletions server/marlin/marlin_kernels/ext.hh
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Expand Up @@ -27,4 +27,9 @@ torch::Tensor marlin_gemm(torch::Tensor &a, torch::Tensor &b_q_weight,
torch::Tensor &b_scales, torch::Tensor &workspace,
int64_t size_m, int64_t size_n, int64_t size_k);

torch::Tensor fp8_marlin_gemm(torch::Tensor& a, torch::Tensor& b_q_weight,
torch::Tensor& b_scales, torch::Tensor& workspace,
int64_t num_bits, int64_t size_m, int64_t size_n,
int64_t size_k);

#endif
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