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
96 lines
985 B
Plaintext
96 lines
985 B
Plaintext
<algorithm>
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<any>
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<array>
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<atomic>
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<barrier>
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<bit>
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<bitset>
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<cassert>
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<ccomplex>
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<cctype>
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<cerrno>
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<cfenv>
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<cfloat>
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<charconv>
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<chrono>
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<cinttypes>
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<climits>
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<clocale>
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<cmath>
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<codecvt>
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<compare>
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<complex>
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<concepts>
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<condition_variable>
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<contract>
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<csetjmp>
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<csignal>
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<cstdarg>
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<cstddef>
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<cstdint>
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<cstdio>
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<cstdlib>
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<cstring>
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<ctime>
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<cuchar>
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<cwchar>
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<cwctype>
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<deque>
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<exception>
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<execution>
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<filesystem>
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<forward_list>
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<fstream>
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<functional>
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<future>
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<initializer_list>
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<iomanip>
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<ios>
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<iosfwd>
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<iostream>
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<istream>
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<iterator>
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<latch>
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<limits>
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<list>
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<locale>
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<map>
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<memory>
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<memory_resource>
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<mutex>
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<new>
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<numeric>
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<optional>
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<ostream>
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<queue>
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<random>
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<ranges>
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<ratio>
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<regex>
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<scoped_allocator>
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<semaphore>
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<set>
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<shared_mutex>
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<span>
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<sstream>
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<stack>
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<stdexcept>
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<streambuf>
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<string>
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<string_view>
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<strstream>
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<syncstream>
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<system_error>
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<thread>
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<tuple>
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<type_traits>
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<typeindex>
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<typeinfo>
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<unordered_map>
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<unordered_set>
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<utility>
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<valarray>
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<variant>
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<vector>
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<version>
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