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#include "../intgemm/aligned.h"
#include "intgemm/intgemm_config.h"
#include "../intgemm/avx512_gemm.h"
#include "../intgemm/sse2_gemm.h"
#include "../intgemm/avx2_gemm.h"
#include "../intgemm/ssse3_gemm.h"
#include "../intgemm/intgemm.h"
#include "../intgemm/stats.h"
#include "../intgemm/callbacks.h"
#include <algorithm>
#include <cassert>
#include <chrono>
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <iomanip>
#include <iostream>
#include <random>
namespace intgemm {
namespace {
struct RandomMatrices {
RandomMatrices(Index A_rows_in, Index width_in, Index B_cols_in) :
A_rows(A_rows_in), width(width_in), B_cols(B_cols_in),
A(A_rows * width), B(width * B_cols) {
std::mt19937 gen;
std::uniform_real_distribution<float> dist(-1.f, 1.f);
gen.seed(45678);
for (auto& it : A) {
it = dist(gen);
}
for (auto& it : B) {
it = dist(gen);
}
}
const Index A_rows, width, B_cols;
AlignedVector<float> A, B;
};
template <class Backend> double Run(const RandomMatrices &m) {
using Integer = typename Backend::Integer;
float quant_mult = 127.0f / 2.0f;
float unquant_mult = 1.0f / (quant_mult * quant_mult);
AlignedVector<Integer> A_prepared(m.A_rows * m.width);
Backend::PrepareA(m.A.begin(), A_prepared.begin(), quant_mult, m.A_rows, m.width);
AlignedVector<Integer> B_prepared(m.width * m.B_cols);
Backend::PrepareB(m.B.begin(), B_prepared.begin(), quant_mult, m.width, m.B_cols);
AlignedVector<float> output(m.A_rows * m.B_cols);
// Burn in
Backend::Multiply(A_prepared.begin(), B_prepared.begin(), m.A_rows, m.width, m.B_cols, callbacks::UnquantizeAndWrite(unquant_mult, output.begin()));
auto start = std::chrono::steady_clock::now();
Backend::Multiply(A_prepared.begin(), B_prepared.begin(), m.A_rows, m.width, m.B_cols, callbacks::UnquantizeAndWrite(unquant_mult, output.begin()));
return std::chrono::duration<double>(std::chrono::steady_clock::now() - start).count();
}
template <class Backend> void RunAll(RandomMatrices *matrices, RandomMatrices *matrices_end, std::vector<std::vector<double>> &stats) {
if (Backend::kUses > kCPU) return;
std::size_t size = matrices_end - matrices;
if (stats.size() < size)
stats.resize(size);
for (std::size_t i = 0; i < size; ++i) {
stats[i].push_back(Run<Backend>(matrices[i]));
}
}
struct BackendStats {
std::vector<std::vector<double>> ssse3_8bit;
std::vector<std::vector<double>> avx2_8bit;
std::vector<std::vector<double>> avx512_8bit;
std::vector<std::vector<double>> avx512vnni_8bit;
std::vector<std::vector<double>> sse2_16bit;
std::vector<std::vector<double>> avx2_16bit;
std::vector<std::vector<double>> avx512_16bit;
};
const float kOutlierThreshold = 0.75;
void Summarize(std::vector<double> &stats) {
// Throw out outliers.
std::vector<double>::iterator keep = stats.begin() + static_cast<std::size_t>(static_cast<float>(stats.size()) * kOutlierThreshold);
std::nth_element(stats.begin(), keep, stats.end());
double avg = 0.0;
for (std::vector<double>::const_iterator i = stats.begin(); i != keep; ++i) {
avg += *i;
}
avg /= (keep - stats.begin());
double stddev = 0.0;
for (std::vector<double>::const_iterator i = stats.begin(); i != keep; ++i) {
double off = (double)*i - avg;
stddev += off * off;
}
stddev = sqrt(stddev / (keep - stats.begin() - 1));
std::cout << std::setw(10) << *std::min_element(stats.begin(), stats.end()) << '\t' << std::setw(8) << avg << '\t' << std::setw(8) << stddev;
}
template <class Backend> void Print(std::vector<std::vector<double>> &stats, std::size_t index) {
if (stats.empty()) return;
std::cout << std::setw(16) << Backend::kName << '\t';
Summarize(stats[index]);
std::cout << '\n';
}
} // namespace intgemm
} // namespace
// Program takes no input
int main(int, char ** argv) {
std::cerr << "Remember to run this on a specific core:\ntaskset --cpu-list 0 " << argv[0] << std::endl;
using namespace intgemm;
RandomMatrices matrices[] = {
{1, 64, 8},
{8, 256, 256},
{8, 2048, 256},
{8, 256, 2048},
{320, 256, 256},
{472, 256, 256},
{248, 256, 256},
{200, 256, 256},
// Additional stuff
{256, 256, 256},
{512, 512, 512},
{1024, 1024, 1024},
/* {4096, 4096, 4096},
{4096, 4096, 2048},
{4096, 4096, 1024},
{4096, 4096, 512},
{4096, 4096, 256},*/
{4096, 4096, 128}
};
RandomMatrices *matrices_end = (RandomMatrices*)matrices + sizeof(matrices) / sizeof(RandomMatrices);
// Only do full sampling for <1024 rows.
RandomMatrices *full_sample;
for (full_sample = matrices_end - 1; full_sample >= matrices && full_sample->A_rows >= 1024; --full_sample) {}
++full_sample;
BackendStats stats;
const int kSamples = 100;
// Realistically, we don't expect different architectures or different precisions to run in the
// same run of an application. Benchmark per architecture and per precision level.
std::cerr << "SSSE3 8bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<ssse3::Kernels8>(matrices, end, stats.ssse3_8bit);
}
std::cerr << "SSE2 16bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<sse2::Kernels16>(matrices, end, stats.sse2_16bit);
}
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX2
std::cerr << "AVX2 8bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<avx2::Kernels8>(matrices, end, stats.avx2_8bit);
}
std::cerr << "AVX2 16bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<avx2::Kernels16>(matrices, end, stats.avx2_16bit);
}
#endif
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX512BW
std::cerr << "AVX512 8bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<avx512bw::Kernels8>(matrices, end, stats.avx512_8bit);
}
std::cerr << "AVX512 16bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<avx512bw::Kernels16>(matrices, end, stats.avx512_16bit);
}
#endif
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX512VNNI
std::cerr << "AVX512VNNI 8bit, 100 samples..." << std::endl;
for (int samples = 0; samples < kSamples; ++samples) {
RandomMatrices *end = (samples < 4) ? matrices_end : full_sample;
RunAll<avx512vnni::Kernels8>(matrices, end, stats.avx512vnni_8bit);
}
#endif
if (stats.sse2_16bit.empty()) {
std::cerr << "No CPU support." << std::endl;
return 1;
}
for (std::size_t i = 0; i < sizeof(matrices) / sizeof(RandomMatrices); ++i) {
std::cout << "Multiply\t" << matrices[i].A_rows << '\t' << matrices[i].width << '\t' << matrices[i].B_cols << '\t' << "Samples=" << (kOutlierThreshold * stats.sse2_16bit[i].size()) << '\n';
Print<ssse3::Kernels8>(stats.ssse3_8bit, i);
Print<avx2::Kernels8>(stats.avx2_8bit, i);
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX512BW
Print<avx512bw::Kernels8>(stats.avx512_8bit, i);
#endif
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX512VNNI
Print<avx512vnni::Kernels8>(stats.avx512vnni_8bit, i);
#endif
Print<sse2::Kernels16>(stats.sse2_16bit, i);
Print<avx2::Kernels16>(stats.avx2_16bit, i);
#ifdef INTGEMM_COMPILER_SUPPORTS_AVX512BW
Print<avx512bw::Kernels16>(stats.avx512_16bit, i);
#endif
}
return 0;
}
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