[INFRA] Import NVIDIA/CCCL upstream as optimization reference library
CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
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cccl_upstream/c/parallel.v2/test/freestanding/test_util.h
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cccl_upstream/c/parallel.v2/test/freestanding/test_util.h
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//===----------------------------------------------------------------------===//
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//
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// Part of CUDA Experimental in CUDA C++ Core Libraries,
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// under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#ifndef C_PARALLEL_FREESTANDING_TEST_UTIL_H
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#define C_PARALLEL_FREESTANDING_TEST_UTIL_H
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#include <cassert>
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#include <iostream>
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#include <cuda_runtime.h>
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#define CUDA_CHECK(call) \
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do \
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{ \
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cudaError_t err = call; \
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if (err != cudaSuccess) \
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{ \
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std::cerr << "CUDA error at " << __FILE__ << ":" << __LINE__ << ": " << cudaGetErrorString(err) << "\n"; \
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return 1; \
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} \
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} while (0)
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#endif // C_PARALLEL_FREESTANDING_TEST_UTIL_H
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