122 lines
4.3 KiB
Python
122 lines
4.3 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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import numpy as np
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import cutlass_cppgen
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from cutlass_cppgen.utils.datatypes import is_numpy_tensor
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from cutlass_cppgen.utils.lazy_import import lazy_import
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if cutlass_cppgen.use_rmm:
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import rmm
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else:
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cudart = lazy_import("cuda.cudart")
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class PoolMemoryManager:
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def __init__(self, init_pool_size: int, max_pool_size: int) -> None:
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self.pool = rmm.mr.PoolMemoryResource(
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rmm.mr.CudaMemoryResource(),
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initial_pool_size=init_pool_size,
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maximum_pool_size=max_pool_size
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)
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self.mr = rmm.mr.TrackingResourceAdaptor(self.pool)
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rmm.mr.set_current_device_resource(self.mr)
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def pool_size(self):
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return self.pool.pool_size()
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class DevicePtrWrapper:
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"""
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Wrapper around a pointer to device memory to provide a uniform interface with the RMM DeviceBuffer
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(at least in terms of the interface used by the CUTLASS Python interface)
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"""
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def __init__(self, dev_ptr):
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self.dev_ptr = dev_ptr
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@property
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def ptr(self):
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return self.dev_ptr
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def _todevice(host_data):
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"""
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Helper for transferring host data to device memory
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"""
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if cutlass_cppgen.use_rmm:
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return rmm.DeviceBuffer.to_device(host_data.tobytes())
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else:
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nbytes = len(host_data.tobytes())
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dev_ptr_wrapper = device_mem_alloc(nbytes)
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err, = cudart.cudaMemcpy(
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dev_ptr_wrapper.ptr,
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host_data.__array_interface__['data'][0],
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nbytes,
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cudart.cudaMemcpyKind.cudaMemcpyHostToDevice
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)
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if err != cudart.cudaError_t.cudaSuccess:
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raise Exception(f"cudaMemcpy failed with error {err}")
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return dev_ptr_wrapper
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def todevice(host_data, dtype=np.float32):
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"""
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Pass the host_data to device memory
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"""
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if isinstance(host_data, list):
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return _todevice(np.array(host_data, dtype=dtype))
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elif is_numpy_tensor(host_data):
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return _todevice(host_data)
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def device_mem_alloc(size):
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if cutlass_cppgen.use_rmm:
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return rmm.DeviceBuffer(size=size)
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else:
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err, ptr = cudart.cudaMalloc(size)
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if err != cudart.cudaError_t.cudaSuccess:
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raise Exception(f"cudaMalloc failed with error {err}")
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return DevicePtrWrapper(ptr)
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def align_size(size, alignment=256):
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return ((size + alignment - 1) // alignment) * alignment
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def create_memory_pool(init_pool_size=0, max_pool_size=2 ** 34):
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if cutlass_cppgen.use_rmm:
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memory_pool = PoolMemoryManager(init_pool_size=init_pool_size, max_pool_size=max_pool_size)
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return memory_pool
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else:
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return None
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