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402 lines
13 KiB
402 lines
13 KiB
// Copyright 2013 Google Inc. All Rights Reserved. |
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// |
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// Licensed under the Apache License, Version 2.0 (the "License"); |
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// you may not use this file except in compliance with the License. |
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// You may obtain a copy of the License at |
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// |
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// http://www.apache.org/licenses/LICENSE-2.0 |
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// |
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// Unless required by applicable law or agreed to in writing, software |
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// distributed under the License is distributed on an "AS IS" BASIS, |
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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// See the License for the specific language governing permissions and |
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// limitations under the License. |
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// |
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// Block split point selection utilities. |
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#include "./block_splitter.h" |
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#include <math.h> |
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#include <stdio.h> |
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#include <stdlib.h> |
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#include <string.h> |
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#include <algorithm> |
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#include <map> |
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#include "./cluster.h" |
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#include "./command.h" |
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#include "./fast_log.h" |
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#include "./histogram.h" |
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namespace brotli { |
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static const int kMaxLiteralHistograms = 100; |
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static const int kMaxCommandHistograms = 50; |
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static const double kLiteralBlockSwitchCost = 28.1; |
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static const double kCommandBlockSwitchCost = 13.5; |
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static const double kDistanceBlockSwitchCost = 14.6; |
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static const int kLiteralStrideLength = 70; |
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static const int kCommandStrideLength = 40; |
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static const int kSymbolsPerLiteralHistogram = 544; |
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static const int kSymbolsPerCommandHistogram = 530; |
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static const int kSymbolsPerDistanceHistogram = 544; |
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static const int kMinLengthForBlockSplitting = 128; |
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static const int kIterMulForRefining = 2; |
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static const int kMinItersForRefining = 100; |
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void CopyLiteralsToByteArray(const Command* cmds, |
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const size_t num_commands, |
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const uint8_t* data, |
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std::vector<uint8_t>* literals) { |
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// Count how many we have. |
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size_t total_length = 0; |
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for (int i = 0; i < num_commands; ++i) { |
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total_length += cmds[i].insert_len_; |
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} |
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if (total_length == 0) { |
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return; |
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} |
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// Allocate. |
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literals->resize(total_length); |
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// Loop again, and copy this time. |
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size_t pos = 0; |
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size_t from_pos = 0; |
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for (int i = 0; i < num_commands && pos < total_length; ++i) { |
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memcpy(&(*literals)[pos], data + from_pos, cmds[i].insert_len_); |
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pos += cmds[i].insert_len_; |
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from_pos += cmds[i].insert_len_ + cmds[i].copy_len_; |
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} |
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} |
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void CopyCommandsToByteArray(const Command* cmds, |
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const size_t num_commands, |
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std::vector<uint16_t>* insert_and_copy_codes, |
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std::vector<uint8_t>* distance_prefixes) { |
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for (int i = 0; i < num_commands; ++i) { |
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const Command& cmd = cmds[i]; |
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insert_and_copy_codes->push_back(cmd.cmd_prefix_); |
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if (cmd.copy_len_ > 0 && cmd.cmd_prefix_ >= 128) { |
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distance_prefixes->push_back(cmd.dist_prefix_); |
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} |
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} |
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} |
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inline static unsigned int MyRand(unsigned int* seed) { |
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*seed *= 16807U; |
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if (*seed == 0) { |
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*seed = 1; |
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} |
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return *seed; |
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} |
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template<typename HistogramType, typename DataType> |
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void InitialEntropyCodes(const DataType* data, size_t length, |
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int literals_per_histogram, |
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int max_histograms, |
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size_t stride, |
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std::vector<HistogramType>* vec) { |
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int total_histograms = length / literals_per_histogram + 1; |
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if (total_histograms > max_histograms) { |
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total_histograms = max_histograms; |
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} |
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unsigned int seed = 7; |
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int block_length = length / total_histograms; |
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for (int i = 0; i < total_histograms; ++i) { |
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int pos = length * i / total_histograms; |
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if (i != 0) { |
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pos += MyRand(&seed) % block_length; |
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} |
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if (pos + stride >= length) { |
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pos = length - stride - 1; |
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} |
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HistogramType histo; |
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histo.Add(data + pos, stride); |
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vec->push_back(histo); |
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} |
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} |
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template<typename HistogramType, typename DataType> |
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void RandomSample(unsigned int* seed, |
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const DataType* data, |
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size_t length, |
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size_t stride, |
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HistogramType* sample) { |
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size_t pos = 0; |
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if (stride >= length) { |
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pos = 0; |
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stride = length; |
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} else { |
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pos = MyRand(seed) % (length - stride + 1); |
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} |
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sample->Add(data + pos, stride); |
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} |
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template<typename HistogramType, typename DataType> |
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void RefineEntropyCodes(const DataType* data, size_t length, |
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size_t stride, |
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std::vector<HistogramType>* vec) { |
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int iters = |
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kIterMulForRefining * length / stride + kMinItersForRefining; |
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unsigned int seed = 7; |
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iters = ((iters + vec->size() - 1) / vec->size()) * vec->size(); |
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for (int iter = 0; iter < iters; ++iter) { |
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HistogramType sample; |
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RandomSample(&seed, data, length, stride, &sample); |
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int ix = iter % vec->size(); |
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(*vec)[ix].AddHistogram(sample); |
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} |
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} |
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inline static float BitCost(int total, int count) { |
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return count == 0 ? FastLog2(total) + 2 : FastLog2(total) - FastLog2(count); |
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} |
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template<typename DataType, int kSize> |
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void FindBlocks(const DataType* data, const size_t length, |
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const double block_switch_bitcost, |
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const std::vector<Histogram<kSize> > &vec, |
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uint8_t *block_id) { |
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if (vec.size() <= 1) { |
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for (int i = 0; i < length; ++i) { |
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block_id[i] = 0; |
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} |
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return; |
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} |
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int vecsize = vec.size(); |
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double* insert_cost = new double[kSize * vecsize]; |
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memset(insert_cost, 0, sizeof(insert_cost[0]) * kSize * vecsize); |
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for (int i = 0; i < kSize; ++i) { |
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for (int j = 0; j < vecsize; ++j) { |
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insert_cost[i * vecsize + j] = |
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BitCost(vec[j].total_count_, vec[j].data_[i]); |
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} |
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} |
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double *cost = new double[vecsize]; |
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memset(cost, 0, sizeof(cost[0]) * vecsize); |
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bool* switch_signal = new bool[length * vecsize]; |
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memset(switch_signal, 0, sizeof(switch_signal[0]) * length * vecsize); |
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// After each iteration of this loop, cost[k] will contain the difference |
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// between the minimum cost of arriving at the current byte position using |
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// entropy code k, and the minimum cost of arriving at the current byte |
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// position. This difference is capped at the block switch cost, and if it |
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// reaches block switch cost, it means that when we trace back from the last |
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// position, we need to switch here. |
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for (size_t byte_ix = 0; byte_ix < length; ++byte_ix) { |
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int ix = byte_ix * vecsize; |
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int insert_cost_ix = data[byte_ix] * vecsize; |
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double min_cost = 1e99; |
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for (int k = 0; k < vecsize; ++k) { |
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// We are coding the symbol in data[byte_ix] with entropy code k. |
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cost[k] += insert_cost[insert_cost_ix + k]; |
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if (cost[k] < min_cost) { |
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min_cost = cost[k]; |
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block_id[byte_ix] = k; |
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} |
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} |
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double block_switch_cost = block_switch_bitcost; |
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// More blocks for the beginning. |
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if (byte_ix < 2000) { |
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block_switch_cost *= 0.77 + 0.07 * byte_ix / 2000; |
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} |
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for (int k = 0; k < vecsize; ++k) { |
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cost[k] -= min_cost; |
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if (cost[k] >= block_switch_cost) { |
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cost[k] = block_switch_cost; |
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switch_signal[ix + k] = true; |
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} |
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} |
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} |
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// Now trace back from the last position and switch at the marked places. |
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int byte_ix = length - 1; |
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int ix = byte_ix * vecsize; |
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int cur_id = block_id[byte_ix]; |
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while (byte_ix > 0) { |
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--byte_ix; |
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ix -= vecsize; |
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if (switch_signal[ix + cur_id]) { |
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cur_id = block_id[byte_ix]; |
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} |
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block_id[byte_ix] = cur_id; |
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} |
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delete[] insert_cost; |
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delete[] cost; |
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delete[] switch_signal; |
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} |
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int RemapBlockIds(uint8_t* block_ids, const size_t length) { |
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std::map<uint8_t, uint8_t> new_id; |
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int next_id = 0; |
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for (int i = 0; i < length; ++i) { |
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if (new_id.find(block_ids[i]) == new_id.end()) { |
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new_id[block_ids[i]] = next_id; |
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++next_id; |
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} |
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} |
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for (int i = 0; i < length; ++i) { |
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block_ids[i] = new_id[block_ids[i]]; |
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} |
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return next_id; |
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} |
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template<typename HistogramType, typename DataType> |
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void BuildBlockHistograms(const DataType* data, const size_t length, |
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uint8_t* block_ids, |
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std::vector<HistogramType>* histograms) { |
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int num_types = RemapBlockIds(block_ids, length); |
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histograms->clear(); |
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histograms->resize(num_types); |
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for (int i = 0; i < length; ++i) { |
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(*histograms)[block_ids[i]].Add(data[i]); |
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} |
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} |
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template<typename HistogramType, typename DataType> |
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void ClusterBlocks(const DataType* data, const size_t length, |
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uint8_t* block_ids) { |
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std::vector<HistogramType> histograms; |
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std::vector<int> block_index(length); |
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int cur_idx = 0; |
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HistogramType cur_histogram; |
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for (int i = 0; i < length; ++i) { |
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bool block_boundary = (i + 1 == length || block_ids[i] != block_ids[i + 1]); |
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block_index[i] = cur_idx; |
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cur_histogram.Add(data[i]); |
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if (block_boundary) { |
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histograms.push_back(cur_histogram); |
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cur_histogram.Clear(); |
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++cur_idx; |
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} |
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} |
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std::vector<HistogramType> clustered_histograms; |
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std::vector<int> histogram_symbols; |
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// Block ids need to fit in one byte. |
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static const int kMaxNumberOfBlockTypes = 256; |
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ClusterHistograms(histograms, 1, histograms.size(), |
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kMaxNumberOfBlockTypes, |
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&clustered_histograms, |
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&histogram_symbols); |
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for (int i = 0; i < length; ++i) { |
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block_ids[i] = histogram_symbols[block_index[i]]; |
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} |
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} |
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void BuildBlockSplit(const std::vector<uint8_t>& block_ids, BlockSplit* split) { |
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int cur_id = block_ids[0]; |
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int cur_length = 1; |
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split->num_types = -1; |
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for (int i = 1; i < block_ids.size(); ++i) { |
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if (block_ids[i] != cur_id) { |
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split->types.push_back(cur_id); |
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split->lengths.push_back(cur_length); |
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split->num_types = std::max(split->num_types, cur_id); |
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cur_id = block_ids[i]; |
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cur_length = 0; |
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} |
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++cur_length; |
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} |
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split->types.push_back(cur_id); |
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split->lengths.push_back(cur_length); |
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split->num_types = std::max(split->num_types, cur_id); |
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++split->num_types; |
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} |
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template<typename HistogramType, typename DataType> |
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void SplitByteVector(const std::vector<DataType>& data, |
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const int literals_per_histogram, |
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const int max_histograms, |
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const int sampling_stride_length, |
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const double block_switch_cost, |
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BlockSplit* split) { |
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if (data.empty()) { |
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split->num_types = 1; |
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return; |
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} else if (data.size() < kMinLengthForBlockSplitting) { |
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split->num_types = 1; |
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split->types.push_back(0); |
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split->lengths.push_back(data.size()); |
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return; |
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} |
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std::vector<HistogramType> histograms; |
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// Find good entropy codes. |
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InitialEntropyCodes(data.data(), data.size(), |
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literals_per_histogram, |
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max_histograms, |
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sampling_stride_length, |
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&histograms); |
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RefineEntropyCodes(data.data(), data.size(), |
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sampling_stride_length, |
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&histograms); |
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// Find a good path through literals with the good entropy codes. |
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std::vector<uint8_t> block_ids(data.size()); |
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for (int i = 0; i < 10; ++i) { |
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FindBlocks(data.data(), data.size(), |
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block_switch_cost, |
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histograms, |
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&block_ids[0]); |
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BuildBlockHistograms(data.data(), data.size(), &block_ids[0], &histograms); |
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} |
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ClusterBlocks<HistogramType>(data.data(), data.size(), &block_ids[0]); |
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BuildBlockSplit(block_ids, split); |
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} |
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void SplitBlock(const Command* cmds, |
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const size_t num_commands, |
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const uint8_t* data, |
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BlockSplit* literal_split, |
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BlockSplit* insert_and_copy_split, |
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BlockSplit* dist_split) { |
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// Create a continuous array of literals. |
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std::vector<uint8_t> literals; |
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CopyLiteralsToByteArray(cmds, num_commands, data, &literals); |
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// Compute prefix codes for commands. |
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std::vector<uint16_t> insert_and_copy_codes; |
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std::vector<uint8_t> distance_prefixes; |
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CopyCommandsToByteArray(cmds, num_commands, |
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&insert_and_copy_codes, |
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&distance_prefixes); |
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SplitByteVector<HistogramLiteral>( |
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literals, |
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kSymbolsPerLiteralHistogram, kMaxLiteralHistograms, |
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kLiteralStrideLength, kLiteralBlockSwitchCost, |
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literal_split); |
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SplitByteVector<HistogramCommand>( |
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insert_and_copy_codes, |
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kSymbolsPerCommandHistogram, kMaxCommandHistograms, |
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kCommandStrideLength, kCommandBlockSwitchCost, |
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insert_and_copy_split); |
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SplitByteVector<HistogramDistance>( |
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distance_prefixes, |
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kSymbolsPerDistanceHistogram, kMaxCommandHistograms, |
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kCommandStrideLength, kDistanceBlockSwitchCost, |
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dist_split); |
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} |
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void SplitBlockByTotalLength(const Command* all_commands, |
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const size_t num_commands, |
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int input_size, |
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int target_length, |
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std::vector<std::vector<Command> >* blocks) { |
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int num_blocks = input_size / target_length + 1; |
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int length_limit = input_size / num_blocks + 1; |
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int total_length = 0; |
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std::vector<Command> cur_block; |
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for (int i = 0; i < num_commands; ++i) { |
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const Command& cmd = all_commands[i]; |
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int cmd_length = cmd.insert_len_ + cmd.copy_len_; |
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if (total_length > length_limit) { |
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blocks->push_back(cur_block); |
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cur_block.clear(); |
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total_length = 0; |
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} |
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cur_block.push_back(cmd); |
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total_length += cmd_length; |
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} |
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blocks->push_back(cur_block); |
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} |
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} // namespace brotli
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