Added a cumsum helper
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7 changed files with 176 additions and 3 deletions
84
benchmarks/BM_cumsum.cpp
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84
benchmarks/BM_cumsum.cpp
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// Copyright (c) 2019, Paul Ferrand
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// All rights reserved.
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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// 1. Redistributions of source code must retain the above copyright notice, this
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// list of conditions and the following disclaimer.
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// 2. Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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// ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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// WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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// ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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// (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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// ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#include <benchmark/benchmark.h>
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#include <random>
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#include <numeric>
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#include <vector>
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#include <cmath>
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#include <iostream>
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#include "../sfizz/SIMDHelpers.h"
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class CumsumArray : public benchmark::Fixture {
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public:
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void SetUp(const ::benchmark::State& state) {
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std::random_device rd { };
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std::mt19937 gen { rd() };
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std::uniform_real_distribution<float> dist { 0, 1 };
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input = std::vector<float>(state.range(0));
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output = std::vector<float>(state.range(0));
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std::generate(input.begin(), input.end(), [&]() { return dist(gen); });
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}
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void TearDown(const ::benchmark::State& state [[maybe_unused]]) {
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}
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std::vector<float> input;
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std::vector<float> output;
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};
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BENCHMARK_DEFINE_F(CumsumArray, Scalar)(benchmark::State& state) {
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for (auto _ : state)
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{
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cumsum<float, false>(input, absl::MakeSpan(output));
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}
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}
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BENCHMARK_DEFINE_F(CumsumArray, SIMD)(benchmark::State& state) {
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for (auto _ : state)
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{
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cumsum<float, true>(input, absl::MakeSpan(output));
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}
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}
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BENCHMARK_DEFINE_F(CumsumArray, Scalar_Unaligned)(benchmark::State& state) {
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for (auto _ : state)
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{
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cumsum<float, false>(absl::MakeSpan(input).subspan(1), absl::MakeSpan(output).subspan(1));
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}
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}
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BENCHMARK_DEFINE_F(CumsumArray, SIMD_Unaligned)(benchmark::State& state) {
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for (auto _ : state)
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{
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cumsum<float, true>(absl::MakeSpan(input).subspan(1), absl::MakeSpan(output).subspan(1));
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}
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}
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BENCHMARK_REGISTER_F(CumsumArray, Scalar)->RangeMultiplier(4)->Range(1 << 2, 1 << 12);
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BENCHMARK_REGISTER_F(CumsumArray, SIMD)->RangeMultiplier(4)->Range(1 << 2, 1 << 12);
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BENCHMARK_REGISTER_F(CumsumArray, Scalar_Unaligned)->RangeMultiplier(4)->Range(1 << 2, 1 << 12);
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BENCHMARK_REGISTER_F(CumsumArray, SIMD_Unaligned)->RangeMultiplier(4)->Range(1 << 2, 1 << 12);
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BENCHMARK_MAIN();
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@ -75,6 +75,9 @@ target_link_libraries(bm_mean benchmark absl::span absl::algorithm)
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add_executable(bm_meanSquared BM_meanSquared.cpp ${SFIZZ_SIMD_SOURCES})
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target_link_libraries(bm_meanSquared benchmark absl::span absl::algorithm)
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add_executable(bm_cumsum BM_cumsum.cpp ${SFIZZ_SIMD_SOURCES})
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target_link_libraries(bm_cumsum benchmark absl::span absl::algorithm)
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add_custom_target(sfizz_benchmarks)
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add_dependencies(sfizz_benchmarks
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bm_opf_high_vs_low
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@ -83,6 +86,7 @@ add_dependencies(sfizz_benchmarks
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bm_mean
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bm_meanSquared
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bm_fill
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bm_cumsum
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bm_mathfuns
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bm_gain
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bm_looping
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@ -61,6 +61,7 @@ namespace SIMDConfig {
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constexpr bool multiplyAdd { false };
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constexpr bool copy { false };
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constexpr bool pan { true };
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constexpr bool cumsum { true };
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constexpr bool mean { false };
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constexpr bool meanSquared { false };
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}
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@ -142,4 +142,10 @@ template <>
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float meanSquared<float, true>(absl::Span<const float> vector) noexcept
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{
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return meanSquared<float, false>(vector);
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}
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template <>
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void cumsum<float, true>(absl::Span<const float> input, absl::Span<float> output) noexcept
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{
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cumsum<float, false>(input, output);
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}
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@ -448,4 +448,30 @@ T meanSquared(absl::Span<const T> vector) noexcept
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}
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template <>
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float meanSquared<float, true>(absl::Span<const float> vector) noexcept;
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float meanSquared<float, true>(absl::Span<const float> vector) noexcept;
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template <class T>
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inline void snippetCumsum(const T*& input, T*& output)
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{
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*output = *(output - 1) + *input++;
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output++;
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}
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template <class T, bool SIMD = SIMDConfig::cumsum>
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void cumsum(absl::Span<const float> input, absl::Span<float> output) noexcept
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{
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ASSERT(output.size() >= input.size());
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if (input.size() == 0)
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return;
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auto out = output.data();
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auto in = input.data();
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const auto sentinel = in + std::min(input.size(), output.size());
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*out++ = *in++;
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while (in < sentinel)
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snippetCumsum(in, out);
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}
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template <>
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void cumsum<float, true>(absl::Span<const float> input, absl::Span<float> output) noexcept;
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@ -613,7 +613,7 @@ float mean<float, true>(absl::Span<const float> vector) noexcept
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auto* sentinel = vector.end();
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const auto* lastAligned = prevAligned(sentinel);
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while (unaligned(value))
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while (unaligned(value) && value < lastAligned)
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result += *value++;
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auto mmSums = _mm_setzero_ps();
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@ -645,7 +645,7 @@ float meanSquared<float, true>(absl::Span<const float> vector) noexcept
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auto* sentinel = vector.end();
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const auto* lastAligned = prevAligned(sentinel);
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while (unaligned(value)) {
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while (unaligned(value) && value < lastAligned) {
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result += (*value) * (*value);
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value++;
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}
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@ -669,4 +669,36 @@ float meanSquared<float, true>(absl::Span<const float> vector) noexcept
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}
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return result / static_cast<float>(vector.size());
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}
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template <>
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void cumsum<float, true>(absl::Span<const float> input, absl::Span<float> output) noexcept
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{
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ASSERT(output.size() >= input.size());
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if (input.size() == 0)
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return;
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auto out = output.data();
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auto in = input.data();
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const auto sentinel = in + std::min(input.size(), output.size());
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const auto lastAligned = prevAligned(sentinel);
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*out++ = *in++;
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while (unaligned(in, out) && in < lastAligned)
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snippetCumsum(in, out);
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auto mmOutput = _mm_set_ps1(*(out - 1));
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while (in < lastAligned) {
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auto mmOffset = _mm_load_ps(in);
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mmOffset = _mm_add_ps(mmOffset, _mm_castsi128_ps(_mm_slli_si128(_mm_castps_si128(mmOffset), 4)));
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mmOffset = _mm_add_ps(mmOffset, _mm_shuffle_ps(_mm_setzero_ps(), mmOffset, 0x40));
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mmOutput = _mm_add_ps(mmOutput, mmOffset);
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_mm_store_ps(out, mmOutput);
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mmOutput = _mm_shuffle_ps(mmOutput, mmOutput, _MM_SHUFFLE(3, 3, 3, 3));
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in += TypeAlignment;
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out += TypeAlignment;
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}
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while (in < sentinel)
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snippetCumsum(in, out);
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}
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@ -711,4 +711,24 @@ TEST_CASE("[Helpers] Mean Squared (SIMD vs scalar)")
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std::vector<float> input(medBufferSize);
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absl::c_iota(input, 0.0);
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REQUIRE(meanSquared<float, false>(input) == meanSquared<float, true>(input));
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}
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TEST_CASE("[Helpers] Cumulative sum ")
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{
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std::array<float, 6> input { 1.1f, 1.2f, 1.3f, 1.4f, 1.5f, 1.6f }; // 1.1 2.3 3.6 5.0 6.5 8.1
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std::array<float, 6> output;
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std::array<float, 6> expected { 1.1f, 2.3f, 3.6f, 5.0f, 6.5f, 8.1f };
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cumsum<float, false>(input, absl::MakeSpan(output));
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REQUIRE(approxEqual<float>(output, expected));
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}
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TEST_CASE("[Helpers] Cumulative sum (SIMD vs Scalar)")
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{
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std::vector<float> input(bigBufferSize);
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std::vector<float> outputScalar(bigBufferSize);
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std::vector<float> outputSIMD(bigBufferSize);
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linearRamp<float>(absl::MakeSpan(input), 0.0, 0.1);
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cumsum<float, false>(input, absl::MakeSpan(outputScalar));
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cumsum<float, true>(input, absl::MakeSpan(outputSIMD));
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REQUIRE(approxEqual<float>(outputScalar, outputSIMD));
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}
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