Squashed 'third_party/ceres/' content from commit e51e9b4
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diff --git a/internal/ceres/small_blas_gemv_benchmark.cc b/internal/ceres/small_blas_gemv_benchmark.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2018 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+// * 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.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+// used to endorse or promote products derived from this software without
+// specific prior written permission.
+//
+// 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.
+//
+// Authors: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "Eigen/Dense"
+#include "benchmark/benchmark.h"
+#include "ceres/small_blas.h"
+
+namespace ceres {
+
+// Benchmarking matrix-vector multiply routines and optimizing memory
+// access requires that we make sure that they are not just sitting in
+// the cache. So, as the benchmarking routine iterates, we need to
+// multiply new/different matrice and vectors. Allocating/creating
+// these objects in the benchmarking loop is too heavy duty, so we
+// create them before hand and cycle through them in the
+// benchmark. This class, given the size of the matrix creates such
+// matrix and vector objects for use in the benchmark.
+class MatrixVectorMultiplyData {
+ public:
+ MatrixVectorMultiplyData(int rows, int cols)
+ : num_elements_(1000),
+ rows_(rows),
+ cols_(cols),
+ a_(num_elements_ * rows, 1.001),
+ b_(num_elements_ * rows * cols, 1.5),
+ c_(num_elements_ * cols, 1.00003) {}
+
+ int num_elements() const { return num_elements_; }
+ double* GetA(int i) { return &a_[i * rows_]; }
+ double* GetB(int i) { return &b_[i * rows_ * cols_]; }
+ double* GetC(int i) { return &c_[i * cols_]; }
+
+ private:
+ const int num_elements_;
+ const int rows_;
+ const int cols_;
+ std::vector<double> a_;
+ std::vector<double> b_;
+ std::vector<double> c_;
+};
+
+// Helper function to generate the various matrix sizes for which we
+// run the benchmark.
+static void MatrixSizeArguments(benchmark::internal::Benchmark* benchmark) {
+ std::vector<int> rows = {1, 2, 3, 4, 6, 8};
+ std::vector<int> cols = {1, 2, 3, 4, 8, 12, 15};
+ for (int r : rows) {
+ for (int c : cols) {
+ benchmark->Args({r, c});
+ }
+ }
+}
+
+void BM_MatrixVectorMultiply(benchmark::State& state) {
+ const int rows = state.range(0);
+ const int cols = state.range(1);
+ MatrixVectorMultiplyData data(rows, cols);
+ const int num_elements = data.num_elements();
+ int iter = 0;
+ for (auto _ : state) {
+ // A += B * C;
+ internal::MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
+ data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter));
+ iter = (iter + 1) % num_elements;
+ }
+}
+
+BENCHMARK(BM_MatrixVectorMultiply)->Apply(MatrixSizeArguments);
+
+void BM_MatrixTransposeVectorMultiply(benchmark::State& state) {
+ const int rows = state.range(0);
+ const int cols = state.range(1);
+ MatrixVectorMultiplyData data(cols, rows);
+ const int num_elements = data.num_elements();
+ int iter = 0;
+ for (auto _ : state) {
+ internal::MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
+ data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter));
+ iter = (iter + 1) % num_elements;
+ }
+}
+
+BENCHMARK(BM_MatrixTransposeVectorMultiply)->Apply(MatrixSizeArguments);
+
+} // namespace ceres
+
+BENCHMARK_MAIN();