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624 lines
20 KiB
C++
624 lines
20 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2015 Benoit Jacob <benoitjacob@google.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include <iostream>
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#include <cstdint>
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#include <cstdlib>
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#include <vector>
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#include <fstream>
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#include <memory>
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bool eigen_use_specific_block_size;
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int eigen_block_size_k, eigen_block_size_m, eigen_block_size_n;
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#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZES eigen_use_specific_block_size
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#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_K eigen_block_size_k
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#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_M eigen_block_size_m
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#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_N eigen_block_size_n
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#include <Eigen/Core>
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#include <bench/BenchTimer.h>
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using namespace Eigen;
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using namespace std;
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static BenchTimer timer;
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// how many times we repeat each measurement.
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// measurements are randomly shuffled - we're not doing
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// all N identical measurements in a row.
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const int measurement_repetitions = 3;
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// Timings below this value are too short to be accurate,
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// we'll repeat measurements with more iterations until
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// we get a timing above that threshold.
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const float g_min_accurate_time = 1e-2f;
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// See --min-working-set-size command line parameter.
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size_t g_min_working_set_size = 0;
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// range of sizes that we will benchmark (in all 3 K,M,N dimensions)
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const size_t maxsize = 2048;
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const size_t minsize = 16;
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typedef MatrixXf MatrixType;
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typedef MatrixType::Scalar Scalar;
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typedef internal::packet_traits<Scalar>::type Packet;
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static_assert((maxsize & (maxsize - 1)) == 0, "maxsize must be a power of two");
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static_assert((minsize & (minsize - 1)) == 0, "minsize must be a power of two");
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static_assert(maxsize > minsize, "maxsize must be larger than minsize");
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static_assert(maxsize < (minsize << 16), "maxsize must be less than (minsize<<16)");
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// just a helper to store a triple of K,M,N sizes for matrix product
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struct size_triple_t
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{
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size_t k, m, n;
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size_triple_t() : k(0), m(0), n(0) {}
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size_triple_t(size_t _k, size_t _m, size_t _n) : k(_k), m(_m), n(_n) {}
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size_triple_t(const size_triple_t& o) : k(o.k), m(o.m), n(o.n) {}
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size_triple_t(uint16_t compact)
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{
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k = 1 << ((compact & 0xf00) >> 8);
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m = 1 << ((compact & 0x0f0) >> 4);
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n = 1 << ((compact & 0x00f) >> 0);
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}
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};
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uint8_t log2_pot(size_t x) {
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size_t l = 0;
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while (x >>= 1) l++;
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return l;
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}
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// Convert between size tripes and a compact form fitting in 12 bits
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// where each size, which must be a POT, is encoded as its log2, on 4 bits
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// so the largest representable size is 2^15 == 32k ... big enough.
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uint16_t compact_size_triple(size_t k, size_t m, size_t n)
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{
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return (log2_pot(k) << 8) | (log2_pot(m) << 4) | log2_pot(n);
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}
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uint16_t compact_size_triple(const size_triple_t& t)
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{
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return compact_size_triple(t.k, t.m, t.n);
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}
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// A single benchmark. Initially only contains benchmark params.
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// Then call run(), which stores the result in the gflops field.
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struct benchmark_t
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{
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uint16_t compact_product_size;
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uint16_t compact_block_size;
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bool use_default_block_size;
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float gflops;
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size_t min_working_set_size;
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float min_accurate_time;
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benchmark_t(size_t pk, size_t pm, size_t pn,
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size_t bk, size_t bm, size_t bn)
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: compact_product_size(compact_size_triple(pk, pm, pn))
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, compact_block_size(compact_size_triple(bk, bm, bn))
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, use_default_block_size(false)
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, gflops(0)
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, min_working_set_size(g_min_working_set_size)
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, min_accurate_time(g_min_accurate_time)
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{}
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benchmark_t(size_t pk, size_t pm, size_t pn)
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: compact_product_size(compact_size_triple(pk, pm, pn))
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, compact_block_size(0)
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, use_default_block_size(true)
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, gflops(0)
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, min_working_set_size(g_min_working_set_size)
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, min_accurate_time(g_min_accurate_time)
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{}
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void run();
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};
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ostream& operator<<(ostream& s, const benchmark_t& b)
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{
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s << hex << b.compact_product_size << dec;
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if (b.use_default_block_size) {
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size_triple_t t(b.compact_product_size);
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Index k = t.k, m = t.m, n = t.n;
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internal::computeProductBlockingSizes<Scalar, Scalar>(k, m, n);
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s << " default(" << k << ", " << m << ", " << n << ")";
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} else {
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s << " " << hex << b.compact_block_size << dec;
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}
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s << " " << b.gflops;
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return s;
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}
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// We sort first by increasing benchmark parameters,
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// then by decreasing performance.
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bool operator<(const benchmark_t& b1, const benchmark_t& b2)
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{
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return b1.compact_product_size < b2.compact_product_size ||
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(b1.compact_product_size == b2.compact_product_size && (
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(b1.compact_block_size < b2.compact_block_size || (
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b1.compact_block_size == b2.compact_block_size &&
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b1.gflops > b2.gflops))));
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}
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void benchmark_t::run()
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{
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size_triple_t productsizes(compact_product_size);
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if (use_default_block_size) {
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eigen_use_specific_block_size = false;
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} else {
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// feed eigen with our custom blocking params
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eigen_use_specific_block_size = true;
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size_triple_t blocksizes(compact_block_size);
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eigen_block_size_k = blocksizes.k;
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eigen_block_size_m = blocksizes.m;
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eigen_block_size_n = blocksizes.n;
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}
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// set up the matrix pool
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const size_t combined_three_matrices_sizes =
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sizeof(Scalar) *
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(productsizes.k * productsizes.m +
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productsizes.k * productsizes.n +
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productsizes.m * productsizes.n);
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// 64 M is large enough that nobody has a cache bigger than that,
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// while still being small enough that everybody has this much RAM,
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// so conveniently we don't need to special-case platforms here.
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const size_t unlikely_large_cache_size = 64 << 20;
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const size_t working_set_size =
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min_working_set_size ? min_working_set_size : unlikely_large_cache_size;
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const size_t matrix_pool_size =
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1 + working_set_size / combined_three_matrices_sizes;
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MatrixType *lhs = new MatrixType[matrix_pool_size];
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MatrixType *rhs = new MatrixType[matrix_pool_size];
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MatrixType *dst = new MatrixType[matrix_pool_size];
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for (size_t i = 0; i < matrix_pool_size; i++) {
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lhs[i] = MatrixType::Zero(productsizes.m, productsizes.k);
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rhs[i] = MatrixType::Zero(productsizes.k, productsizes.n);
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dst[i] = MatrixType::Zero(productsizes.m, productsizes.n);
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}
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// main benchmark loop
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int iters_at_a_time = 1;
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float time_per_iter = 0.0f;
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size_t matrix_index = 0;
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while (true) {
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double starttime = timer.getCpuTime();
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for (int i = 0; i < iters_at_a_time; i++) {
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dst[matrix_index] = lhs[matrix_index] * rhs[matrix_index];
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matrix_index++;
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if (matrix_index == matrix_pool_size) {
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matrix_index = 0;
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}
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}
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double endtime = timer.getCpuTime();
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const float timing = float(endtime - starttime);
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if (timing >= min_accurate_time) {
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time_per_iter = timing / iters_at_a_time;
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break;
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}
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iters_at_a_time *= 2;
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}
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delete[] lhs;
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delete[] rhs;
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delete[] dst;
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gflops = 2e-9 * productsizes.k * productsizes.m * productsizes.n / time_per_iter;
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}
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void print_cpuinfo()
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{
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#ifdef __linux__
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cout << "contents of /proc/cpuinfo:" << endl;
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string line;
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ifstream cpuinfo("/proc/cpuinfo");
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if (cpuinfo.is_open()) {
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while (getline(cpuinfo, line)) {
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cout << line << endl;
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}
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cpuinfo.close();
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}
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cout << endl;
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#elif defined __APPLE__
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cout << "output of sysctl hw:" << endl;
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system("sysctl hw");
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cout << endl;
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#endif
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}
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template <typename T>
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string type_name()
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{
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return "unknown";
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}
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template<>
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string type_name<float>()
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{
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return "float";
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}
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template<>
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string type_name<double>()
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{
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return "double";
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}
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struct action_t
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{
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virtual const char* invokation_name() const { abort(); return nullptr; }
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virtual void run() const { abort(); }
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virtual ~action_t() {}
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};
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void show_usage_and_exit(int /*argc*/, char* argv[],
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const vector<unique_ptr<action_t>>& available_actions)
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{
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cerr << "usage: " << argv[0] << " <action> [options...]" << endl << endl;
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cerr << "available actions:" << endl << endl;
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for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
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cerr << " " << (*it)->invokation_name() << endl;
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}
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cerr << endl;
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cerr << "options:" << endl << endl;
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cerr << " --min-working-set-size=N:" << endl;
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cerr << " Set the minimum working set size to N bytes." << endl;
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cerr << " This is rounded up as needed to a multiple of matrix size." << endl;
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cerr << " A larger working set lowers the chance of a warm cache." << endl;
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cerr << " The default value 0 means use a large enough working" << endl;
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cerr << " set to likely outsize caches." << endl;
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cerr << " A value of 1 (that is, 1 byte) would mean don't do anything to" << endl;
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cerr << " avoid warm caches." << endl;
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exit(1);
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}
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float measure_clock_speed()
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{
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cerr << "Measuring clock speed... \r" << flush;
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vector<float> all_gflops;
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for (int i = 0; i < 8; i++) {
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// a good measure of clock speed is obtained by benchmarking small matrices that
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// fit in L1 cache and use warm caches (min_working_set_size = 1).
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benchmark_t b(128, 128, 128);
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b.min_working_set_size = 1;
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b.min_accurate_time = 0.1f; // long-running for better accuracy
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b.run();
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all_gflops.push_back(b.gflops);
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}
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sort(all_gflops.begin(), all_gflops.end());
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float stable_estimate = all_gflops[2] + all_gflops[3] + all_gflops[4] + all_gflops[5];
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// multiply by an arbitrary constant to discourage trying doing anything with the
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// returned values besides just comparing them with each other.
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float result = stable_estimate * 123.456f;
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return result;
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}
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struct human_duration_t
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{
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int seconds;
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human_duration_t(int s) : seconds(s) {}
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};
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ostream& operator<<(ostream& s, const human_duration_t& d)
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{
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int remainder = d.seconds;
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if (remainder > 3600) {
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int hours = remainder / 3600;
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s << hours << " h ";
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remainder -= hours * 3600;
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}
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if (remainder > 60) {
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int minutes = remainder / 60;
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s << minutes << " min ";
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remainder -= minutes * 60;
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}
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if (d.seconds < 600) {
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s << remainder << " s";
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}
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return s;
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}
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void try_run_some_benchmarks(
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vector<benchmark_t>& benchmarks,
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double time_start,
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size_t& first_benchmark_to_run,
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float& max_clock_speed)
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{
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if (first_benchmark_to_run == benchmarks.size()) {
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return;
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}
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double time_last_progress_update = 0;
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double time_last_clock_speed_measurement = 0;
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double time_now = 0;
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size_t benchmark_index = first_benchmark_to_run;
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while (true) {
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float ratio_done = float(benchmark_index) / benchmarks.size();
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time_now = timer.getRealTime();
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// We check clock speed every minute and at the end.
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if (benchmark_index == benchmarks.size() ||
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time_now > time_last_clock_speed_measurement + 60.0f)
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{
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time_last_clock_speed_measurement = time_now;
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// Ensure that clock speed is as expected
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float current_clock_speed = measure_clock_speed();
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// we only allow 1% higher clock speeds, because we want to know the
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// clock speed with good accuracy, and this should only cause restarts
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// at the beginning of the benchmarks run.
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const float tolerance_higher_clock_speed = 1.01f;
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if (current_clock_speed > tolerance_higher_clock_speed * max_clock_speed) {
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// Clock speed is now higher than we previously measured.
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// Either our initial measurement was inaccurate, which won't happen
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// too many times as we are keeping the best clock speed value and
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// and allowing some tolerance; or something really weird happened,
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// which invalidates all benchmark results collected so far.
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// Either way, we better restart all over again now.
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if (benchmark_index) {
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cerr << "Restarting at " << 100.0f * ratio_done
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<< " % because clock speed increased. " << endl;
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}
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max_clock_speed = current_clock_speed;
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first_benchmark_to_run = 0;
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return;
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}
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// we are a bit more tolerant to lower clock speeds because we don't want
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// to cause sleeps and reruns all the time.
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const float tolerance_lower_clock_speed = 0.98f;
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bool rerun_last_tests = false;
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if (current_clock_speed < tolerance_lower_clock_speed * max_clock_speed) {
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cerr << "Measurements completed so far: "
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<< 100.0f * ratio_done
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<< " % " << endl;
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cerr << "Clock speed seems to be only "
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<< current_clock_speed/max_clock_speed
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<< " times what it used to be." << endl;
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unsigned int seconds_to_sleep_if_lower_clock_speed = 1;
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while (current_clock_speed < tolerance_lower_clock_speed * max_clock_speed) {
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if (seconds_to_sleep_if_lower_clock_speed > 300) {
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cerr << "Sleeping longer probably won't make a difference. Giving up." << endl;
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cerr << "Things to try:" << endl;
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cerr << " 1. Check if the device is in some energy-saving state." << endl;
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cerr << " On Android, it may help to enable 'Stay Awake' in the dev settings." << endl;
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cerr << " 2. Check if the device is overheating." << endl;
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cerr << " On some devices, system temperature is reported in" << endl;
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cerr << " /sys/class/thermal/thermal_zone*/temp" << endl;
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cerr << " 3. Some system daemon might be playing with clock speeds." << endl;
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cerr << " In particular, on Qualcomm devices, disable mpdecision " << endl;
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cerr << " by renaming /system/bin/mpdecision and rebooting." << endl;
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cerr << " 4. CPU frequency scaling might conceivably be the problem." << endl;
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cerr << " In particular, Intel Turbo Boost. Try disabling that." << endl;
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exit(1);
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}
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rerun_last_tests = true;
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cerr << "Sleeping "
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<< seconds_to_sleep_if_lower_clock_speed
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<< " s..." << endl;
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sleep(seconds_to_sleep_if_lower_clock_speed);
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current_clock_speed = measure_clock_speed();
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seconds_to_sleep_if_lower_clock_speed *= 2;
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}
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}
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if (rerun_last_tests) {
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cerr << "Redoing the last "
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<< 100.0f * float(benchmark_index - first_benchmark_to_run) / benchmarks.size()
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<< " % because clock speed had been low. " << endl;
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return;
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}
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// nothing wrong with the clock speed so far, so there won't be a need to rerun
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// benchmarks run so far in case we later encounter a lower clock speed.
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first_benchmark_to_run = benchmark_index;
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}
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if (benchmark_index == benchmarks.size()) {
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// We're done!
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first_benchmark_to_run = benchmarks.size();
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// Erase progress info
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cerr << " " << endl;
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return;
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}
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// Display progress info on stderr
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if (time_now > time_last_progress_update + 1.0f) {
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time_last_progress_update = time_now;
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cerr << "Measurements... " << 100.0f * ratio_done
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<< " %, ETA "
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<< human_duration_t(float(time_now - time_start) * (1.0f - ratio_done) / ratio_done)
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<< " \r" << flush;
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}
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// This is where we actually run a benchmark!
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benchmarks[benchmark_index].run();
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benchmark_index++;
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}
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}
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void run_benchmarks(vector<benchmark_t>& benchmarks)
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{
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// Randomly shuffling benchmarks allows us to get accurate enough progress info,
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// as now the cheap/expensive benchmarks are randomly mixed so they average out.
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// It also means that if data is corrupted for some time span, the odds are that
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// not all repetitions of a given benchmark will be corrupted.
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random_shuffle(benchmarks.begin(), benchmarks.end());
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|
float max_clock_speed = 0.0f;
|
|
for (int i = 0; i < 4; i++) {
|
|
max_clock_speed = max(max_clock_speed, measure_clock_speed());
|
|
}
|
|
|
|
double time_start = timer.getRealTime();
|
|
size_t first_benchmark_to_run = 0;
|
|
while (first_benchmark_to_run < benchmarks.size()) {
|
|
try_run_some_benchmarks(benchmarks,
|
|
time_start,
|
|
first_benchmark_to_run,
|
|
max_clock_speed);
|
|
}
|
|
|
|
// Sort timings by increasing benchmark parameters, and decreasing gflops.
|
|
// The latter is very important. It means that we can ignore all but the first
|
|
// benchmark with given parameters.
|
|
sort(benchmarks.begin(), benchmarks.end());
|
|
|
|
// Collect best (i.e. now first) results for each parameter values.
|
|
vector<benchmark_t> best_benchmarks;
|
|
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
|
|
if (best_benchmarks.empty() ||
|
|
best_benchmarks.back().compact_product_size != it->compact_product_size ||
|
|
best_benchmarks.back().compact_block_size != it->compact_block_size)
|
|
{
|
|
best_benchmarks.push_back(*it);
|
|
}
|
|
}
|
|
|
|
// keep and return only the best benchmarks
|
|
benchmarks = best_benchmarks;
|
|
}
|
|
|
|
struct measure_all_pot_sizes_action_t : action_t
|
|
{
|
|
virtual const char* invokation_name() const { return "all-pot-sizes"; }
|
|
virtual void run() const
|
|
{
|
|
vector<benchmark_t> benchmarks;
|
|
for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
|
|
for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
|
|
for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
|
|
for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
|
|
for (size_t kblock = minsize; kblock <= ksize; kblock *= 2) {
|
|
for (size_t mblock = minsize; mblock <= msize; mblock *= 2) {
|
|
for (size_t nblock = minsize; nblock <= nsize; nblock *= 2) {
|
|
benchmarks.emplace_back(ksize, msize, nsize, kblock, mblock, nblock);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
run_benchmarks(benchmarks);
|
|
|
|
cout << "BEGIN MEASUREMENTS ALL POT SIZES" << endl;
|
|
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
|
|
cout << *it << endl;
|
|
}
|
|
}
|
|
};
|
|
|
|
struct measure_default_sizes_action_t : action_t
|
|
{
|
|
virtual const char* invokation_name() const { return "default-sizes"; }
|
|
virtual void run() const
|
|
{
|
|
vector<benchmark_t> benchmarks;
|
|
for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
|
|
for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
|
|
for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
|
|
for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
|
|
benchmarks.emplace_back(ksize, msize, nsize);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
run_benchmarks(benchmarks);
|
|
|
|
cout << "BEGIN MEASUREMENTS DEFAULT SIZES" << endl;
|
|
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
|
|
cout << *it << endl;
|
|
}
|
|
}
|
|
};
|
|
|
|
int main(int argc, char* argv[])
|
|
{
|
|
double time_start = timer.getRealTime();
|
|
cout.precision(4);
|
|
cerr.precision(4);
|
|
|
|
vector<unique_ptr<action_t>> available_actions;
|
|
available_actions.emplace_back(new measure_all_pot_sizes_action_t);
|
|
available_actions.emplace_back(new measure_default_sizes_action_t);
|
|
|
|
auto action = available_actions.end();
|
|
|
|
if (argc <= 1) {
|
|
show_usage_and_exit(argc, argv, available_actions);
|
|
}
|
|
for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
|
|
if (!strcmp(argv[1], (*it)->invokation_name())) {
|
|
action = it;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (action == available_actions.end()) {
|
|
show_usage_and_exit(argc, argv, available_actions);
|
|
}
|
|
|
|
for (int i = 2; i < argc; i++) {
|
|
if (argv[i] == strstr(argv[i], "--min-working-set-size=")) {
|
|
const char* equals_sign = strchr(argv[i], '=');
|
|
g_min_working_set_size = strtoul(equals_sign+1, nullptr, 10);
|
|
} else {
|
|
cerr << "unrecognized option: " << argv[i] << endl << endl;
|
|
show_usage_and_exit(argc, argv, available_actions);
|
|
}
|
|
}
|
|
|
|
print_cpuinfo();
|
|
|
|
cout << "benchmark parameters:" << endl;
|
|
cout << "pointer size: " << 8*sizeof(void*) << " bits" << endl;
|
|
cout << "scalar type: " << type_name<Scalar>() << endl;
|
|
cout << "packet size: " << internal::packet_traits<MatrixType::Scalar>::size << endl;
|
|
cout << "minsize = " << minsize << endl;
|
|
cout << "maxsize = " << maxsize << endl;
|
|
cout << "measurement_repetitions = " << measurement_repetitions << endl;
|
|
cout << "g_min_accurate_time = " << g_min_accurate_time << endl;
|
|
cout << "g_min_working_set_size = " << g_min_working_set_size;
|
|
if (g_min_working_set_size == 0) {
|
|
cout << " (try to outsize caches)";
|
|
}
|
|
cout << endl << endl;
|
|
|
|
(*action)->run();
|
|
|
|
double time_end = timer.getRealTime();
|
|
cerr << "Finished in " << human_duration_t(time_end - time_start) << endl;
|
|
}
|