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|---|---|---|---|
| 1 | #include "karpich_i_bitwise_batcher/omp/include/ops_omp.hpp" | ||
| 2 | |||
| 3 | #include <algorithm> | ||
| 4 | #include <array> | ||
| 5 | #include <cstddef> | ||
| 6 | #include <cstdint> | ||
| 7 | #include <limits> | ||
| 8 | #include <random> | ||
| 9 | #include <utility> | ||
| 10 | #include <vector> | ||
| 11 | |||
| 12 | #include "karpich_i_bitwise_batcher/common/include/common.hpp" | ||
| 13 | #include "util/include/util.hpp" | ||
| 14 | |||
| 15 | namespace karpich_i_bitwise_batcher { | ||
| 16 | |||
| 17 | namespace { | ||
| 18 | |||
| 19 | constexpr int kBytesPerInt = 4; | ||
| 20 | constexpr int kBitsPerByte = 8; | ||
| 21 | constexpr int kRadixSize = 256; | ||
| 22 | constexpr uint32_t kSignBitMask = 0x80000000U; | ||
| 23 | constexpr uint32_t kByteMask = 0xFFU; | ||
| 24 | |||
| 25 | 102 | void RadixSortRange(std::vector<int> &arr, int lo, int hi) { | |
| 26 | 102 | int n = hi - lo; | |
| 27 |
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102 | if (n <= 1) { |
| 28 | 9 | return; | |
| 29 | } | ||
| 30 | |||
| 31 | 93 | std::vector<int> buf(n); | |
| 32 | |||
| 33 |
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465 | for (int byte_idx = 0; byte_idx < kBytesPerInt; byte_idx++) { |
| 34 | 372 | int shift = byte_idx * kBitsPerByte; | |
| 35 | 372 | std::array<int, kRadixSize> count{}; | |
| 36 | |||
| 37 |
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39228 | for (int i = lo; i < hi; i++) { |
| 38 |
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38856 | auto val = static_cast<uint32_t>(arr[i]); |
| 39 |
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38856 | if (byte_idx == kBytesPerInt - 1) { |
| 40 | val ^= kSignBitMask; | ||
| 41 | } | ||
| 42 | 38856 | count.at((val >> shift) & kByteMask)++; | |
| 43 | } | ||
| 44 | |||
| 45 | int prefix = 0; | ||
| 46 |
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95604 | for (int &c : count) { |
| 47 | 95232 | int tmp = c; | |
| 48 | 95232 | c = prefix; | |
| 49 | 95232 | prefix += tmp; | |
| 50 | } | ||
| 51 | |||
| 52 |
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39228 | for (int i = lo; i < hi; i++) { |
| 53 |
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38856 | auto val = static_cast<uint32_t>(arr[i]); |
| 54 |
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38856 | if (byte_idx == kBytesPerInt - 1) { |
| 55 | val ^= kSignBitMask; | ||
| 56 | } | ||
| 57 |
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38856 | buf.at(count.at((val >> shift) & kByteMask)++) = arr[i]; |
| 58 | } | ||
| 59 | |||
| 60 | 372 | std::copy(buf.begin(), buf.begin() + n, arr.begin() + lo); | |
| 61 | } | ||
| 62 | } | ||
| 63 | |||
| 64 | 86 | void CompareExchange(std::vector<int> &data, int pos_a, int pos_b, int len) { | |
| 65 | 86 | std::vector<int> merged(static_cast<size_t>(2) * len); | |
| 66 | 86 | std::merge(data.begin() + pos_a, data.begin() + pos_a + len, data.begin() + pos_b, data.begin() + pos_b + len, | |
| 67 | merged.begin()); | ||
| 68 | 86 | std::copy(merged.begin(), merged.begin() + len, data.begin() + pos_a); | |
| 69 |
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86 | std::copy(merged.begin() + len, merged.end(), data.begin() + pos_b); |
| 70 | 86 | } | |
| 71 | |||
| 72 | 44 | std::vector<std::pair<int, int>> BuildBatcherNetwork(int n) { | |
| 73 | 44 | std::vector<std::pair<int, int>> net; | |
| 74 |
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93 | for (int pw = 1; pw < n; pw *= 2) { |
| 75 |
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117 | for (int k = pw; k >= 1; k /= 2) { |
| 76 |
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145 | for (int j = k % pw; j <= n - 1 - k; j += 2 * k) { |
| 77 |
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163 | for (int i = 0; i < std::min(k, n - j - k); i++) { |
| 78 |
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86 | if ((j + i) / (2 * pw) == (j + i + k) / (2 * pw)) { |
| 79 |
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86 | net.emplace_back(j + i, j + i + k); |
| 80 | } | ||
| 81 | } | ||
| 82 | } | ||
| 83 | } | ||
| 84 | } | ||
| 85 | 44 | return net; | |
| 86 | } | ||
| 87 | |||
| 88 | } // namespace | ||
| 89 | |||
| 90 | 48 | KarpichIBitwiseBatcherOMP::KarpichIBitwiseBatcherOMP(const InType &in) { | |
| 91 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 92 | 48 | GetInput() = in; | |
| 93 | GetOutput() = 0; | ||
| 94 | 48 | } | |
| 95 | |||
| 96 | 48 | bool KarpichIBitwiseBatcherOMP::ValidationImpl() { | |
| 97 |
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48 | return GetInput() > 0 && GetOutput() == 0; |
| 98 | } | ||
| 99 | |||
| 100 | 48 | bool KarpichIBitwiseBatcherOMP::PreProcessingImpl() { | |
| 101 | 48 | int n = GetInput(); | |
| 102 | 48 | data_.resize(n); | |
| 103 | 48 | std::random_device rd; | |
| 104 | 48 | std::mt19937 gen(rd()); | |
| 105 | std::uniform_int_distribution<int> dist(0, n); | ||
| 106 |
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9752 | for (int i = 0; i < n; i++) { |
| 107 | 9704 | data_[i] = dist(gen); | |
| 108 | } | ||
| 109 | 48 | return true; | |
| 110 | } | ||
| 111 | |||
| 112 |
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48 | bool KarpichIBitwiseBatcherOMP::RunImpl() { |
| 113 | 48 | int n = static_cast<int>(data_.size()); | |
| 114 |
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48 | if (n <= 1) { |
| 115 | return true; | ||
| 116 | } | ||
| 117 | |||
| 118 | 44 | int num_thr = ppc::util::GetNumThreads(); | |
| 119 |
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44 | if (num_thr > n) { |
| 120 | num_thr = 1; | ||
| 121 | } | ||
| 122 | |||
| 123 | 44 | int chunk = (n + num_thr - 1) / num_thr; | |
| 124 | 44 | int padded = chunk * num_thr; | |
| 125 | 44 | data_.resize(padded, std::numeric_limits<int>::max()); | |
| 126 | |||
| 127 | auto &data_ref = data_; | ||
| 128 | 44 | #pragma omp parallel for default(none) shared(data_ref, chunk, num_thr) num_threads(num_thr) | |
| 129 | for (int tid = 0; tid < num_thr; tid++) { | ||
| 130 | RadixSortRange(data_ref, tid * chunk, (tid + 1) * chunk); | ||
| 131 | } | ||
| 132 | |||
| 133 | 44 | auto net = BuildBatcherNetwork(num_thr); | |
| 134 |
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130 | for (auto &[a, b] : net) { |
| 135 |
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86 | CompareExchange(data_, a * chunk, b * chunk, chunk); |
| 136 | } | ||
| 137 | |||
| 138 |
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44 | data_.resize(n); |
| 139 | return true; | ||
| 140 | } | ||
| 141 | |||
| 142 | 48 | bool KarpichIBitwiseBatcherOMP::PostProcessingImpl() { | |
| 143 |
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48 | GetOutput() = GetInput(); |
| 144 | 48 | return std::ranges::is_sorted(data_); | |
| 145 | } | ||
| 146 | |||
| 147 | } // namespace karpich_i_bitwise_batcher | ||
| 148 |