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* Use async cuda malloc managed with cuda 13 * add pool threshold * refactor for regular cuda malloc * load eval gpu for cuda * remove use of cuda pool, use cuda free async * fix * fix * fix * fix * fix + comment
51 lines
1.2 KiB
C++
51 lines
1.2 KiB
C++
// Copyright © 2023-2024 Apple Inc.
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#pragma once
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#include "mlx/backend/common/utils.h"
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namespace mlx::core {
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enum class CopyType {
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// Copy a raw scalar input into the full contiguous output
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Scalar,
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// Copy the raw input buffer contiguously into a raw output buffer of the same
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// size
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Vector,
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// Copy the full virtual input to the full contiguous output
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General,
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// Copy the full virtual input to the full virtual output. We assume the
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// input and output have the same shape.
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GeneralGeneral
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};
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inline bool set_copy_output_data(
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const array& in,
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array& out,
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CopyType ctype,
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std::function<allocator::Buffer(size_t)> mallocfn = allocator::malloc) {
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if (ctype == CopyType::Vector) {
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// If the input is donateable, we are doing a vector copy and the types
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// have the same size, then the input buffer can hold the output.
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if (is_donatable(in, out)) {
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out.copy_shared_buffer(in);
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return true;
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} else {
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out.set_data(
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mallocfn(in.data_size() * out.itemsize()),
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in.data_size(),
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in.strides(),
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in.flags());
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return false;
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}
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} else {
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out.set_data(mallocfn(out.nbytes()));
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return false;
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}
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}
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} // namespace mlx::core
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