upd

.github/workflows/release_wheel.yml

@@ -18,7 +18,7 @@ on:
       #   required: true
 
 env:
-  TORCH_CUDA_ARCH_LIST: "8.0 8.9 9.0+PTX"
+  TORCH_CUDA_ARCH_LIST: "7.5 8.0 8.9 9.0+PTX"
 
 jobs:
   build:

docs/installation.rst

@@ -19,7 +19,7 @@ Prerequisites
 
   - Use ``python -c "import torch; print(torch.version.cuda)"`` to check your PyTorch CUDA version.
 
-- Supported GPU architectures: ``sm80``, ``sm86``, ``sm89``, ``sm90`` (``sm75`` / ``sm70`` support is working in progress).
+- Supported GPU architectures: ``sm75``, ``sm80``, ``sm86``, ``sm89``, ``sm90``.
 
 Quick Start
 ^^^^^^^^^^^

include/flashinfer/attention/decode.cuh

@@ -594,11 +594,7 @@ constexpr uint32_t get_heuristic_num_threads(uint32_t group_size, uint32_t sizeo
       return 512U;
     }
   } else {
-#ifdef FLASHINFER_ENABLE_BF16
     return 128U;
-#else
-    return 64U;
-#endif
   }
 }
 

python/setup.py

@@ -32,17 +32,14 @@
 
 root = pathlib.Path(__name__).parent
 
-enable_bf16 = True
-# NOTE(Zihao): we haven't utilized fp8 tensor cores yet, so there is no
 # cuda arch check for fp8 at the moment.
-enable_fp8 = True
 for cuda_arch_flags in torch_cpp_ext._get_cuda_arch_flags():
     arch = int(re.search("compute_\d+", cuda_arch_flags).group()[-2:])
     if arch < 75:
         raise RuntimeError("FlashInfer requires sm75+")
-    elif arch == 75:
-        # disable bf16 for sm75
-        enable_bf16 = False
+
+enable_bf16 = os.environ.get("FLASHINFER_ENABLE_BF16", "1") == "1"
+enable_fp8 = os.environ.get("FLASHINFER_ENABLE_FP8", "1") == "1"
 
 if enable_bf16:
     torch_cpp_ext.COMMON_NVCC_FLAGS.append("-DFLASHINFER_ENABLE_BF16")