127 lines
4.5 KiB
Python
127 lines
4.5 KiB
Python
#################################################################################################
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#
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# Copyright (c) 2017 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: BSD-3-Clause
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# 3. Neither the name of the copyright holder nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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#################################################################################################
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"""
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Utility functions for interacting with the device
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"""
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from __future__ import annotations
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from cutlass_cppgen.utils.lazy_import import lazy_import
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cuda = lazy_import("cuda.cuda")
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cudart = lazy_import("cuda.cudart")
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import cutlass_cppgen
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from cutlass_cppgen.utils.datatypes import is_cupy_tensor, is_numpy_tensor, is_torch_tensor
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def check_cuda_errors(result: list):
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"""
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Checks whether `result` contains a CUDA error raises the error as an exception, if so. Otherwise,
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returns the result contained in the remaining fields of `result`.
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:param result: the results of the `cudart` method, consisting of an error code and any method results
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:type result: list
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:return: non-error-code results from the `results` parameter
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"""
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# `result` is of the format : (cudaError_t, result...)
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err = result[0]
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if err.value:
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raise RuntimeError("CUDA error: {}".format(cudart.cudaGetErrorName(err)))
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if len(result) == 1:
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return None
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elif len(result) == 2:
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return result[1]
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else:
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return result[1:]
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def device_cc(device: int = -1) -> int:
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"""
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Returns the compute capability of the device with ID `device`.
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:param device: ID of the device to query
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:type device: int
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:return: compute capability of the queried device (e.g., 80 for SM80)
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:rtype: int
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"""
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if device == -1:
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device = cutlass_cppgen.device_id()
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deviceProp = check_cuda_errors(cudart.cudaGetDeviceProperties(device))
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major = str(deviceProp.major)
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minor = str(deviceProp.minor)
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return int(major + minor)
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def device_sm_count(device: int = -1):
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if device == -1:
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device = cutlass_cppgen.device_id()
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err, device_sm_count = cuda.cuDeviceGetAttribute(
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cuda.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, device
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)
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if err != cuda.CUresult.CUDA_SUCCESS:
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raise Exception(
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"Failed to retireve SM count. "
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f"cuDeviceGetAttribute() failed with error: {cuda.cuGetErrorString(err)[1]}"
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)
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return device_sm_count
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def to_device_ptr(tensor) -> cuda.CUdeviceptr:
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"""
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Converts a tensor to a CUdeviceptr
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:param tensor: tensor to convert
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:type tensor: np.ndarray | torch.Tensor | cp.ndarray | int
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:return: device pointer
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:rtype: cuda.CUdeviceptr
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"""
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if is_numpy_tensor(tensor):
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ptr = cuda.CUdeviceptr(tensor.__array_interface__["data"][0])
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elif is_torch_tensor(tensor):
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ptr = cuda.CUdeviceptr(tensor.data_ptr())
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elif is_cupy_tensor(tensor):
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ptr = cuda.CUdeviceptr(int(tensor.data.ptr))
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elif isinstance(tensor, cuda.CUdeviceptr):
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ptr = tensor
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elif isinstance(tensor, int):
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ptr = cuda.CUdeviceptr(tensor)
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else:
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raise NotImplementedError(tensor)
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return ptr
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