234 lines
7.4 KiB
C++
234 lines
7.4 KiB
C++
/*
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Copyright (c) 2018 tevador
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This file is part of RandomX.
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RandomX is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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RandomX is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with RandomX. If not, see<http://www.gnu.org/licenses/>.
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*/
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/* Original code from Argon2 reference source code package used under CC0 Licence
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* https://github.com/P-H-C/phc-winner-argon2
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* Copyright 2015
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* Daniel Dinu, Dmitry Khovratovich, Jean-Philippe Aumasson, and Samuel Neves
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*/
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#include <new>
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#include <algorithm>
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#include <stdexcept>
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#include <cstring>
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#include <limits>
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#include <cstring>
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#include "common.hpp"
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#include "dataset.hpp"
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#include "virtual_memory.hpp"
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#include "superscalar.hpp"
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#include "blake2_generator.hpp"
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#include "reciprocal.h"
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#include "blake2/endian.h"
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#include "argon2.h"
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#include "argon2_core.h"
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#if defined(__SSE2__)
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#include <wmmintrin.h>
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#define PREFETCHNTA(x) _mm_prefetch((const char *)(x), _MM_HINT_NTA)
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#else
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#define PREFETCH(memory)
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#endif
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randomx_dataset::~randomx_dataset() {
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}
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static_assert(RANDOMX_ARGON_MEMORY % (RANDOMX_ARGON_LANES * ARGON2_SYNC_POINTS) == 0, "RANDOMX_ARGON_MEMORY - invalid value");
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void randomx_cache::initialize(const void *seed, size_t seedSize) {
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uint32_t memory_blocks, segment_length;
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argon2_instance_t instance;
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argon2_context context;
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context.out = nullptr;
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context.outlen = 0;
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context.pwd = CONST_CAST(uint8_t *)seed;
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context.pwdlen = (uint32_t)seedSize;
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context.salt = CONST_CAST(uint8_t *)RANDOMX_ARGON_SALT;
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context.saltlen = (uint32_t)randomx::ArgonSaltSize;
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context.secret = NULL;
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context.secretlen = 0;
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context.ad = NULL;
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context.adlen = 0;
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context.t_cost = RANDOMX_ARGON_ITERATIONS;
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context.m_cost = RANDOMX_ARGON_MEMORY;
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context.lanes = RANDOMX_ARGON_LANES;
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context.threads = 1;
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context.allocate_cbk = NULL;
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context.free_cbk = NULL;
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context.flags = ARGON2_DEFAULT_FLAGS;
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context.version = ARGON2_VERSION_NUMBER;
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/* 2. Align memory size */
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/* Minimum memory_blocks = 8L blocks, where L is the number of lanes */
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memory_blocks = context.m_cost;
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segment_length = memory_blocks / (context.lanes * ARGON2_SYNC_POINTS);
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instance.version = context.version;
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instance.memory = NULL;
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instance.passes = context.t_cost;
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instance.memory_blocks = memory_blocks;
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instance.segment_length = segment_length;
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instance.lane_length = segment_length * ARGON2_SYNC_POINTS;
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instance.lanes = context.lanes;
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instance.threads = context.threads;
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instance.type = Argon2_d;
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instance.memory = (block*)memory;
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if (instance.threads > instance.lanes) {
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instance.threads = instance.lanes;
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}
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/* 3. Initialization: Hashing inputs, allocating memory, filling first
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* blocks
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*/
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argon_initialize(&instance, &context);
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fill_memory_blocks(&instance);
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reciprocalCache.clear();
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randomx::Blake2Generator gen(seed, seedSize);
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for (int i = 0; i < RANDOMX_CACHE_ACCESSES; ++i) {
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randomx::generateSuperscalar(programs[i], gen);
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for (unsigned j = 0; j < programs[i].getSize(); ++j) {
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auto& instr = programs[i](j);
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if (instr.opcode == randomx::SuperscalarInstructionType::IMUL_RCP) {
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auto rcp = randomx_reciprocal(instr.getImm32());
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instr.setImm32(reciprocalCache.size());
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reciprocalCache.push_back(rcp);
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}
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}
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}
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}
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namespace randomx {
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template<class Allocator>
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void Dataset<Allocator>::allocate() {
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memory = (uint8_t*)Allocator::allocMemory(RANDOMX_DATASET_SIZE);
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}
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template<class Allocator>
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Dataset<Allocator>::~Dataset() {
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Allocator::freeMemory(memory, RANDOMX_DATASET_SIZE);
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}
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template<class Allocator>
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void Cache<Allocator>::allocate() {
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memory = (uint8_t*)Allocator::allocMemory(RANDOMX_ARGON_MEMORY * ARGON2_BLOCK_SIZE);
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}
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template<class Allocator>
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Cache<Allocator>::~Cache() {
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Allocator::freeMemory(memory, RANDOMX_ARGON_MEMORY * ARGON2_BLOCK_SIZE);
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}
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template<class Allocator>
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DatasetInitFunc Cache<Allocator>::getInitFunc() {
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return &initDataset;
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}
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template<class Allocator>
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DatasetInitFunc CacheWithJit<Allocator>::getInitFunc() {
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return jit.getDatasetInitFunc();
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}
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template<class Allocator>
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void CacheWithJit<Allocator>::initialize(const void *seed, size_t seedSize) {
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randomx_cache::initialize(seed, seedSize);
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jit.generateSuperscalarHash(programs, reciprocalCache);
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jit.generateDatasetInitCode();
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}
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template class Dataset<AlignedAllocator<CacheLineSize>>;
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template class Dataset<LargePageAllocator>;
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template class Cache<AlignedAllocator<CacheLineSize>>;
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template class Cache<LargePageAllocator>;
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template class CacheWithJit<AlignedAllocator<CacheLineSize>>;
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template class CacheWithJit<LargePageAllocator>;
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constexpr uint64_t superscalarMul0 = 6364136223846793005ULL;
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constexpr uint64_t superscalarAdd1 = 9298410992540426748ULL;
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constexpr uint64_t superscalarAdd2 = 12065312585734608966ULL;
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constexpr uint64_t superscalarAdd3 = 9306329213124610396ULL;
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constexpr uint64_t superscalarAdd4 = 5281919268842080866ULL;
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constexpr uint64_t superscalarAdd5 = 10536153434571861004ULL;
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constexpr uint64_t superscalarAdd6 = 3398623926847679864ULL;
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constexpr uint64_t superscalarAdd7 = 9549104520008361294ULL;
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static inline uint8_t* getMixBlock(uint64_t registerValue, uint8_t *memory) {
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constexpr uint32_t mask = (RANDOMX_ARGON_MEMORY * ArgonBlockSize / CacheLineSize - 1);
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return memory + (registerValue & mask) * CacheLineSize;
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}
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void initDatasetBlock(randomx_cache* cache, uint8_t* out, uint64_t blockNumber) {
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int_reg_t rl[8];
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uint8_t* mixBlock;
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uint64_t registerValue = blockNumber;
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rl[0] = (blockNumber + 1) * superscalarMul0;
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rl[1] = rl[0] ^ superscalarAdd1;
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rl[2] = rl[0] ^ superscalarAdd2;
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rl[3] = rl[0] ^ superscalarAdd3;
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rl[4] = rl[0] ^ superscalarAdd4;
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rl[5] = rl[0] ^ superscalarAdd5;
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rl[6] = rl[0] ^ superscalarAdd6;
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rl[7] = rl[0] ^ superscalarAdd7;
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for (unsigned i = 0; i < RANDOMX_CACHE_ACCESSES; ++i) {
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mixBlock = getMixBlock(registerValue, cache->memory);
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SuperscalarProgram& prog = cache->programs[i];
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executeSuperscalar(rl, prog, &cache->reciprocalCache);
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for (unsigned q = 0; q < 8; ++q)
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rl[q] ^= load64(mixBlock + 8 * q);
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registerValue = rl[prog.getAddressRegister()];
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}
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memcpy(out, &rl, CacheLineSize);
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}
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void initDataset(randomx_cache* cache, uint8_t* dataset, uint32_t startBlock, uint32_t endBlock) {
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for (uint32_t blockNumber = startBlock; blockNumber < endBlock; ++blockNumber, dataset += CacheLineSize)
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initDatasetBlock(cache, dataset, blockNumber);
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}
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/*void datasetAlloc(dataset_t& ds, bool largePages) {
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if (std::numeric_limits<size_t>::max() < RANDOMX_DATASET_SIZE)
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throw std::runtime_error("Platform doesn't support enough memory for the dataset");
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if (largePages) {
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ds.dataset.memory = (uint8_t*)allocLargePagesMemory(ds.dataset.size);
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}
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else {
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ds.dataset.memory = (uint8_t*)_mm_malloc(ds.dataset.size, 64);
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if (ds.dataset.memory == nullptr) {
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throw std::runtime_error("Dataset memory allocation failed. >4 GiB of free virtual memory is needed.");
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}
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}
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}
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void datasetInitCache(const void* seed, dataset_t& ds, bool largePages) {
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ds.cache.memory = allocCache(ds.cache.size, largePages);
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argonFill(ds.cache, seed, SeedSize);
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}*/
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}
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