[Setup] Enable TORCH_CUDA_ARCH_LIST for selecting target GPUs (#1074)

setup.py

@@ -3,6 +3,7 @@ import os
 import re
 import subprocess
 from typing import List, Set
+import warnings
 
 from packaging.version import parse, Version
 import setuptools
@@ -11,6 +12,9 @@ from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
 
 ROOT_DIR = os.path.dirname(__file__)
 
+# Supported NVIDIA GPU architectures.
+SUPPORTED_ARCHS = ["7.0", "7.5", "8.0", "8.6", "8.9", "9.0"]
+
 # Compiler flags.
 CXX_FLAGS = ["-g", "-O2", "-std=c++17"]
 # TODO(woosuk): Should we use -O3?
@@ -38,51 +42,82 @@ def get_nvcc_cuda_version(cuda_dir: str) -> Version:
     return nvcc_cuda_version
 
 
-# Collect the compute capabilities of all available GPUs.
+def get_torch_arch_list() -> Set[str]:
-device_count = torch.cuda.device_count()
+    # TORCH_CUDA_ARCH_LIST can have one or more architectures,
-compute_capabilities: Set[int] = set()
+    # e.g. "8.0" or "7.5,8.0,8.6+PTX". Here, the "8.6+PTX" option asks the
-for i in range(device_count):
+    # compiler to additionally include PTX code that can be runtime-compiled
+    # and executed on the 8.6 or newer architectures. While the PTX code will
+    # not give the best performance on the newer architectures, it provides
+    # forward compatibility.
+    valid_arch_strs = SUPPORTED_ARCHS + [s + "+PTX" for s in SUPPORTED_ARCHS]
+    arch_list = os.environ.get("TORCH_CUDA_ARCH_LIST", None)
+    if arch_list is None:
+        return set()
+
+    # List are separated by ; or space.
+    arch_list = arch_list.replace(" ", ";").split(";")
+    for arch in arch_list:
+        if arch not in valid_arch_strs:
+            raise ValueError(
+                f"Unsupported CUDA arch ({arch}). "
+                f"Valid CUDA arch strings are: {valid_arch_strs}.")
+    return set(arch_list)
+
+
+# First, check the TORCH_CUDA_ARCH_LIST environment variable.
+compute_capabilities = get_torch_arch_list()
+if not compute_capabilities:
+    # If TORCH_CUDA_ARCH_LIST is not defined or empty, target all available
+    # GPUs on the current machine.
+    device_count = torch.cuda.device_count()
+    for i in range(device_count):
         major, minor = torch.cuda.get_device_capability(i)
         if major < 7:
             raise RuntimeError(
-            "GPUs with compute capability less than 7.0 are not supported.")
+                "GPUs with compute capability below 7.0 are not supported.")
-    compute_capabilities.add(major * 10 + minor)
+        compute_capabilities.add(f"{major}.{minor}")
+
+nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME)
+if not compute_capabilities:
+    # If no GPU is specified nor available, add all supported architectures
+    # based on the NVCC CUDA version.
+    compute_capabilities = set(SUPPORTED_ARCHS)
+    if nvcc_cuda_version < Version("11.1"):
+        compute_capabilities.remove("8.6")
+    if nvcc_cuda_version < Version("11.8"):
+        compute_capabilities.remove("8.9")
+        compute_capabilities.remove("9.0")
 
 # Validate the NVCC CUDA version.
-nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME)
 if nvcc_cuda_version < Version("11.0"):
     raise RuntimeError("CUDA 11.0 or higher is required to build the package.")
-if 86 in compute_capabilities and nvcc_cuda_version < Version("11.1"):
+if nvcc_cuda_version < Version("11.1"):
+    if any(cc.startswith("8.6") for cc in compute_capabilities):
         raise RuntimeError(
-        "CUDA 11.1 or higher is required for GPUs with compute capability 8.6."
+            "CUDA 11.1 or higher is required for compute capability 8.6.")
-    )
+if nvcc_cuda_version < Version("11.8"):
-if 89 in compute_capabilities and nvcc_cuda_version < Version("11.8"):
+    if any(cc.startswith("8.9") for cc in compute_capabilities):
         # CUDA 11.8 is required to generate the code targeting compute capability 8.9.
         # However, GPUs with compute capability 8.9 can also run the code generated by
         # the previous versions of CUDA 11 and targeting compute capability 8.0.
         # Therefore, if CUDA 11.8 is not available, we target compute capability 8.0
         # instead of 8.9.
-    compute_capabilities.remove(89)
+        warnings.warn(
-    compute_capabilities.add(80)
+            "CUDA 11.8 or higher is required for compute capability 8.9. "
-if 90 in compute_capabilities and nvcc_cuda_version < Version("11.8"):
+            "Targeting compute capability 8.0 instead.")
+        compute_capabilities = set(cc for cc in compute_capabilities
+                                   if not cc.startswith("8.9"))
+        compute_capabilities.add("8.0+PTX")
+    if any(cc.startswith("9.0") for cc in compute_capabilities):
         raise RuntimeError(
-        "CUDA 11.8 or higher is required for GPUs with compute capability 9.0."
+            "CUDA 11.8 or higher is required for compute capability 9.0.")
-    )
-
-# If no GPU is available, add all supported compute capabilities.
-if not compute_capabilities:
-    compute_capabilities = {70, 75, 80}
-    if nvcc_cuda_version >= Version("11.1"):
-        compute_capabilities.add(86)
-    if nvcc_cuda_version >= Version("11.8"):
-        compute_capabilities.add(89)
-        compute_capabilities.add(90)
 
 # Add target compute capabilities to NVCC flags.
 for capability in compute_capabilities:
-    NVCC_FLAGS += [
+    num = capability[0] + capability[2]
-        "-gencode", f"arch=compute_{capability},code=sm_{capability}"
+    NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=sm_{num}"]
-    ]
+    if capability.endswith("+PTX"):
+        NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=compute_{num}"]
 
 # Use NVCC threads to parallelize the build.
 if nvcc_cuda_version >= Version("11.2"):