Create more detailed setup.py

setup.py

 import os
+import torch
 from setuptools import setup, find_packages
-from torch.utils.cpp_extension import BuildExtension, CUDAExtension
+from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
+
+if CUDA_HOME is None:
+    raise RuntimeError(
+        f"Cannot find CUDA_HOME. CUDA must be available to build the package.")
+
+# Collect the compute capabilities of all available GPUs.
+compute_capabilities = set()
+for i in range(torch.cuda.device_count()):
+    major, minor = torch.cuda.get_device_capability(i)
+    if major < 8:
+        raise RuntimeError("GPUs with compute capability less than 8.0 are not supported.")
+    compute_capabilities.add(major * 10 + minor)
 
 # Get environment variables
 build_cuda_extension = os.environ.get('BUILD_CUDA_EXT', '1') == '1'
@@ -22,6 +35,11 @@ if not torch_is_prebuilt:
 ext_modules = []
 
 if build_cuda_extension:
+    n_threads = min(os.cpu_count(), 8)
+
+    cxx_args = ["-g", "-O3", "-fopenmp", "-lgomp", "-std=c++17"]
+    nvcc_args = ["-O3", "-std=c++17", "--threads", n_threads]
+
     ext_modules.append(
         CUDAExtension(
             name="awq_inference_engine",
@@ -32,25 +50,36 @@ if build_cuda_extension:
                 "awq_cuda/position_embedding/pos_encoding_kernels.cu"
             ],
             extra_compile_args={
-                "cxx": ["-g", "-O3", "-fopenmp", "-lgomp", "-std=c++17"],
-                "nvcc": ["-O3", "-std=c++17"]
+                "cxx": cxx_args,
+                "nvcc": nvcc_args
             },
         )
     )
 
 setup(
-    name="awq",
+    name="autoawq",
     version="0.1.0",
-    description="An efficient and accurate low-bit weight quantization(INT3/4) method for LLMs.",
+    author="Casper Hansen",
+    license="MIT",
+    description="AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference.",
     long_description=open("README.md", "r").read(),
     long_description_content_type="text/markdown",
     python_requires=">=3.8",
+    url="https://github.com/casper-hansen/AutoAWQ",
+    keywords=["awq", "autoawq", "quantization", "transformers"],
     classifiers=[
-        "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: Apache Software License",
+        "Environment :: GPU :: NVIDIA CUDA :: 11.8",
+        "Environment :: GPU :: NVIDIA CUDA :: 12",
+        "License :: OSI Approved :: MIT License",
+        "Natural Language :: English",
+        "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3.11",
+        "Programming Language :: C++",
     ],
     install_requires=dependencies,
-    packages=find_packages(exclude=["results*", "scripts*", "examples*"]),
+    packages=find_packages(exclude=["examples*"]),
     ext_modules=ext_modules,
     cmdclass={"build_ext": BuildExtension}
 )