56fd68e7dd
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
26 lines
573 B
C++
26 lines
573 B
C++
#pragma once
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#include <thrust/system/cuda/memory.h>
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#include <thrust/system_error.h>
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#include <vector>
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#include <unittest/testframework.h>
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class CUDATestDriver : public UnitTestDriver
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{
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public:
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int current_device_architecture() const;
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private:
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std::vector<int> target_devices(const ArgumentMap& kwargs);
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bool check_cuda_error(bool concise);
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bool post_test_smoke_check(const UnitTest& test, bool concise) override;
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bool run_tests(const ArgumentSet& args, const ArgumentMap& kwargs) override;
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};
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UnitTestDriver& driver_instance(thrust::system::cuda::tag);
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