207 lines
No EOL
7.8 KiB
C++
207 lines
No EOL
7.8 KiB
C++
// Copyright (c) 2019, Paul Ferrand
|
|
// All rights reserved.
|
|
|
|
// Redistribution and use in source and binary forms, with or without
|
|
// modification, are permitted provided that the following conditions are met:
|
|
|
|
// 1. Redistributions of source code must retain the above copyright notice, this
|
|
// list of conditions and the following disclaimer.
|
|
// 2. Redistributions in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
|
|
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
|
// ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
|
// WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
|
// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
|
|
// ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
|
// (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
|
// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
|
// ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
|
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
|
|
#include <benchmark/benchmark.h>
|
|
#include <random>
|
|
#include "SIMDHelpers.h"
|
|
#include "Buffer.h"
|
|
|
|
|
|
static void Dummy(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
benchmark::DoNotOptimize(value);
|
|
}
|
|
}
|
|
|
|
static void LinearScalar(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, false>(absl::MakeSpan(output), 0.0f, value);
|
|
}
|
|
}
|
|
|
|
static void LinearSIMD(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, true>(absl::MakeSpan(output), 0.0f, value);
|
|
}
|
|
}
|
|
static void LinearScalarUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, false>(absl::MakeSpan(output).subspan(1), 0.0f, value);
|
|
}
|
|
}
|
|
|
|
static void LinearSIMDUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, true>(absl::MakeSpan(output).subspan(1), 0.0f, value);
|
|
}
|
|
}
|
|
|
|
static void MulScalar(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::multiplicativeRamp<float, false>(absl::MakeSpan(output), 1.0f, value);
|
|
}
|
|
}
|
|
|
|
static void MulSIMD(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::multiplicativeRamp<float, true>(absl::MakeSpan(output), 1.0f, value);
|
|
}
|
|
}
|
|
static void MulScalarUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::multiplicativeRamp<float, false>(absl::MakeSpan(output).subspan(1), 1.0f, value);
|
|
}
|
|
}
|
|
|
|
static void MulSIMDUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::multiplicativeRamp<float, true>(absl::MakeSpan(output).subspan(1), 1.0f, value);
|
|
}
|
|
}
|
|
|
|
static void LogDomainScalar(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, false>(absl::MakeSpan(output), 1.0f, value);
|
|
sfz::applyGain<float, false>(std::log(2.0f), absl::MakeSpan(output));
|
|
sfz::exp<float, false>(output, absl::MakeSpan(output));
|
|
}
|
|
}
|
|
|
|
static void LogDomainSIMD(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
sfz::linearRamp<float, true>(absl::MakeSpan(output), 1.0f, value);
|
|
sfz::applyGain<float, true>(std::log(2.0f), absl::MakeSpan(output));
|
|
sfz::exp<float, true>(output, absl::MakeSpan(output));
|
|
}
|
|
}
|
|
static void LogDomainScalarUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
auto outputSpan = absl::MakeSpan(output).subspan(1);
|
|
sfz::linearRamp<float, false>(outputSpan, 1.0f, value);
|
|
sfz::applyGain<float, false>(std::log(2.0f), outputSpan);
|
|
sfz::exp<float, false>(outputSpan, outputSpan);
|
|
}
|
|
}
|
|
|
|
static void LogDomainSIMDUnaligned(benchmark::State& state) {
|
|
sfz::Buffer<float> output(state.range(0));
|
|
std::random_device rd { };
|
|
std::mt19937 gen { rd() };
|
|
std::uniform_real_distribution<float> dist { 1, 2 };
|
|
for (auto _ : state)
|
|
{
|
|
auto value = dist(gen);
|
|
auto outputSpan = absl::MakeSpan(output).subspan(1);
|
|
sfz::linearRamp<float, true>(outputSpan, 1.0f, value);
|
|
sfz::applyGain<float, true>(std::log(2.0f), outputSpan);
|
|
sfz::exp<float, true>(outputSpan, outputSpan);
|
|
}
|
|
}
|
|
|
|
// Register the function as a benchmark
|
|
BENCHMARK(Dummy)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LinearScalar)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LinearSIMD)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LinearScalarUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LinearSIMDUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(MulScalar)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(MulSIMD)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(MulScalarUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(MulSIMDUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LogDomainScalar)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LogDomainSIMD)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LogDomainScalarUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK(LogDomainSIMDUnaligned)->RangeMultiplier(4)->Range((1 << 2), (1 << 12));
|
|
BENCHMARK_MAIN(); |