Now determining cuda version via libcudart.so call.
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@ -28,10 +28,40 @@ def check_cuda_result(cuda, result_val):
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if result_val != 0:
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if result_val != 0:
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error_str = ctypes.c_char_p()
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error_str = ctypes.c_char_p()
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cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
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cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
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raise Exception(f"CUDA exception! ERROR: {error_str}")
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raise Exception(f"CUDA exception! Error code: {error_str.value.decode()}")
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def get_cuda_version(cuda, cudart_path):
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# https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION
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try:
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cudart = ctypes.CDLL(cudart_path)
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except OSError:
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# TODO: shouldn't we error or at least warn here?
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print(f'ERROR: libcudart.so could not be read from path: {cudart_path}!')
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return None
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version = ctypes.c_int()
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check_cuda_result(cuda, cudart.cudaRuntimeGetVersion(ctypes.byref(version)))
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version = int(version.value)
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major = version//1000
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minor = (version-(major*1000))//10
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return f'{major}{minor}'
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def get_compute_capabilities():
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def get_cuda_lib_handle():
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# 1. find libcuda.so library (GPU driver) (/usr/lib)
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try:
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cuda = ctypes.CDLL("libcuda.so")
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except OSError:
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# TODO: shouldn't we error or at least warn here?
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print('ERROR: libcuda.so not found!')
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return None
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check_cuda_result(cuda, cuda.cuInit(0))
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return cuda
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def get_compute_capabilities(cuda):
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"""
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"""
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1. find libcuda.so library (GPU driver) (/usr/lib)
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1. find libcuda.so library (GPU driver) (/usr/lib)
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init_device -> init variables -> call function by reference
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init_device -> init variables -> call function by reference
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@ -42,13 +72,6 @@ def get_compute_capabilities():
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# bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
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# bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
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"""
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"""
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# 1. find libcuda.so library (GPU driver) (/usr/lib)
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try:
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cuda = ctypes.CDLL("libcuda.so")
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except OSError:
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# TODO: shouldn't we error or at least warn here?
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print('ERROR: libcuda.so not found!')
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return None
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nGpus = ctypes.c_int()
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nGpus = ctypes.c_int()
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cc_major = ctypes.c_int()
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cc_major = ctypes.c_int()
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@ -57,8 +80,6 @@ def get_compute_capabilities():
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result = ctypes.c_int()
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result = ctypes.c_int()
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device = ctypes.c_int()
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device = ctypes.c_int()
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check_cuda_result(cuda, cuda.cuInit(0))
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check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
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check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
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ccs = []
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ccs = []
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for i in range(nGpus.value):
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for i in range(nGpus.value):
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@ -75,13 +96,13 @@ def get_compute_capabilities():
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# def get_compute_capability()-> Union[List[str, ...], None]: # FIXME: error
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# def get_compute_capability()-> Union[List[str, ...], None]: # FIXME: error
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def get_compute_capability():
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def get_compute_capability(cuda):
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"""
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"""
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Extracts the highest compute capbility from all available GPUs, as compute
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Extracts the highest compute capbility from all available GPUs, as compute
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capabilities are downwards compatible. If no GPUs are detected, it returns
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capabilities are downwards compatible. If no GPUs are detected, it returns
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None.
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None.
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"""
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"""
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ccs = get_compute_capabilities()
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ccs = get_compute_capabilities(cuda)
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if ccs is not None:
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if ccs is not None:
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# TODO: handle different compute capabilities; for now, take the max
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# TODO: handle different compute capabilities; for now, take the max
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return ccs[-1]
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return ccs[-1]
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@ -89,10 +110,19 @@ def get_compute_capability():
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def evaluate_cuda_setup():
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def evaluate_cuda_setup():
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cuda_path = determine_cuda_runtime_lib_path()
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print(f"CUDA SETUP: CUDA path found: {cuda_path}")
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cc = get_compute_capability()
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binary_name = "libbitsandbytes_cpu.so"
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binary_name = "libbitsandbytes_cpu.so"
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cudart_path = determine_cuda_runtime_lib_path()
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if cudart_path is None:
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print(
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"WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!"
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)
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return binary_name
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print(f"CUDA SETUP: CUDA path found: {cudart_path}")
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cuda = get_cuda_lib_handle()
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cc = get_compute_capability(cuda)
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cuda_version_string = get_cuda_version(cuda, cudart_path)
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if cc == '':
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if cc == '':
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print(
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print(
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@ -107,15 +137,8 @@ def evaluate_cuda_setup():
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# (1) CUDA missing cases (no CUDA installed by CUDA driver (nvidia-smi accessible)
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# (1) CUDA missing cases (no CUDA installed by CUDA driver (nvidia-smi accessible)
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# (2) Multiple CUDA versions installed
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# (2) Multiple CUDA versions installed
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# FIXME: cuda_home is still unused
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cuda_home = str(Path(cuda_path).parent.parent)
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# we use ls -l instead of nvcc to determine the cuda version
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# we use ls -l instead of nvcc to determine the cuda version
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# since most installations will have the libcudart.so installed, but not the compiler
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# since most installations will have the libcudart.so installed, but not the compiler
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ls_output, err = execute_and_return(f"ls -l {cuda_path}")
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major, minor, revision = (
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ls_output.split(" ")[-1].replace("libcudart.so.", "").split(".")
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)
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cuda_version_string = f"{major}{minor}"
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print(f'CUDA_SETUP: Detected CUDA version {cuda_version_string}')
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print(f'CUDA_SETUP: Detected CUDA version {cuda_version_string}')
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def get_binary_name():
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def get_binary_name():
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@ -123,4 +123,4 @@ def determine_cuda_runtime_lib_path() -> Union[Path, None]:
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warn_in_case_of_duplicates(cuda_runtime_libs)
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warn_in_case_of_duplicates(cuda_runtime_libs)
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return next(iter(cuda_runtime_libs)) if cuda_runtime_libs else set()
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return next(iter(cuda_runtime_libs)) if cuda_runtime_libs else None
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