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-rw-r--r--bitsandbytes/cuda_setup/main.py127
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+"""
+extract factors the build is dependent on:
+[X] compute capability
+ [ ] TODO: Q - What if we have multiple GPUs of different makes?
+- CUDA version
+- Software:
+ - CPU-only: only CPU quantization functions (no optimizer, no matrix multipl)
+ - CuBLAS-LT: full-build 8-bit optimizer
+ - no CuBLAS-LT: no 8-bit matrix multiplication (`nomatmul`)
+
+evaluation:
+ - if paths faulty, return meaningful error
+ - else:
+ - determine CUDA version
+ - determine capabilities
+ - based on that set the default path
+"""
+
+import ctypes
+from pathlib import Path
+
+from ..utils import execute_and_return
+from .paths import determine_cuda_runtime_lib_path
+
+
+def check_cuda_result(cuda, result_val):
+ # 3. Check for CUDA errors
+ if result_val != 0:
+ error_str = ctypes.c_char_p()
+ cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
+ raise Exception(f"CUDA exception! ERROR: {error_str}")
+
+
+def get_compute_capabilities():
+ """
+ 1. find libcuda.so library (GPU driver) (/usr/lib)
+ init_device -> init variables -> call function by reference
+ 2. call extern C function to determine CC
+ (https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__DEVICE__DEPRECATED.html)
+ 3. Check for CUDA errors
+ https://stackoverflow.com/questions/14038589/what-is-the-canonical-way-to-check-for-errors-using-the-cuda-runtime-api
+ # bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
+ """
+
+ # 1. find libcuda.so library (GPU driver) (/usr/lib)
+ try:
+ cuda = ctypes.CDLL("libcuda.so")
+ except OSError:
+ # TODO: shouldn't we error or at least warn here?
+ return None
+
+ nGpus = ctypes.c_int()
+ cc_major = ctypes.c_int()
+ cc_minor = ctypes.c_int()
+
+ result = ctypes.c_int()
+ device = ctypes.c_int()
+
+ check_cuda_result(cuda, cuda.cuInit(0))
+
+ check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
+ ccs = []
+ for i in range(nGpus.value):
+ check_cuda_result(cuda, cuda.cuDeviceGet(ctypes.byref(device), i))
+ ref_major = ctypes.byref(cc_major)
+ ref_minor = ctypes.byref(cc_minor)
+ # 2. call extern C function to determine CC
+ check_cuda_result(
+ cuda, cuda.cuDeviceComputeCapability(ref_major, ref_minor, device)
+ )
+ ccs.append(f"{cc_major.value}.{cc_minor.value}")
+
+ return ccs.sort()
+
+
+# def get_compute_capability()-> Union[List[str, ...], None]: # FIXME: error
+def get_compute_capability():
+ """
+ Extracts the highest compute capbility from all available GPUs, as compute
+ capabilities are downwards compatible. If no GPUs are detected, it returns
+ None.
+ """
+ if ccs := get_compute_capabilities() is not None:
+ # TODO: handle different compute capabilities; for now, take the max
+ return ccs[-1]
+ return None
+
+
+def evaluate_cuda_setup():
+ cuda_path = determine_cuda_runtime_lib_path()
+ print(f"CUDA SETUP: CUDA path found: {cuda_path}")
+ cc = get_compute_capability()
+ binary_name = "libbitsandbytes_cpu.so"
+
+ # FIXME: has_gpu is still unused
+ if not (has_gpu := bool(cc)):
+ print(
+ "WARNING: No GPU detected! Check your CUDA paths. Processing to load CPU-only library..."
+ )
+ return binary_name
+
+ # 7.5 is the minimum CC vor cublaslt
+ has_cublaslt = cc in ["7.5", "8.0", "8.6"]
+
+ # TODO:
+ # (1) CUDA missing cases (no CUDA installed by CUDA driver (nvidia-smi accessible)
+ # (2) Multiple CUDA versions installed
+
+ # FIXME: cuda_home is still unused
+ cuda_home = str(Path(cuda_path).parent.parent)
+ # we use ls -l instead of nvcc to determine the cuda version
+ # since most installations will have the libcudart.so installed, but not the compiler
+ ls_output, err = execute_and_return(f"ls -l {cuda_path}")
+ major, minor, revision = (
+ ls_output.split(" ")[-1].replace("libcudart.so.", "").split(".")
+ )
+ cuda_version_string = f"{major}{minor}"
+
+ def get_binary_name():
+ "if not has_cublaslt (CC < 7.5), then we have to choose _nocublaslt.so"
+ bin_base_name = "libbitsandbytes_cuda"
+ if has_cublaslt:
+ return f"{bin_base_name}{cuda_version_string}.so"
+ else:
+ return f"{bin_base_name}_nocublaslt.so"
+
+ return binary_name