Migrate Eigen benchmarks to the Google benchmark framework

libeigen/eigen!2132

Closes #3025

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>

benchmarks/sparse_transpose.cpp

@@ -0,0 +1,45 @@
+#include <benchmark/benchmark.h>
+#include <Eigen/Sparse>
+#include <set>
+
+using namespace Eigen;
+
+typedef double Scalar;
+typedef SparseMatrix<Scalar> SpMat;
+
+static void fillMatrix(float density, int rows, int cols, SpMat& dst) {
+  dst.resize(rows, cols);
+  dst.reserve(static_cast<int>(rows * cols * density));
+  for (int j = 0; j < cols; ++j) {
+    for (int i = 0; i < rows; ++i) {
+      if (internal::random<float>(0, 1) < density) {
+        dst.insert(i, j) = internal::random<Scalar>();
+      }
+    }
+  }
+  dst.makeCompressed();
+}
+
+static void BM_SparseTranspose(benchmark::State& state) {
+  int n = state.range(0);
+  float density = state.range(1) / 10000.0f;
+  SpMat sm(n, n), result(n, n);
+  fillMatrix(density, n, n, sm);
+  for (auto _ : state) {
+    result = sm.transpose();
+    benchmark::DoNotOptimize(result.valuePtr());
+  }
+  state.counters["nnz"] = sm.nonZeros();
+  state.counters["density%"] = density * 100;
+}
+
+static void TransposeSizes(::benchmark::Benchmark* b) {
+  // Args: {size, density*10000}
+  for (int n : {1000, 10000}) {
+    for (int d : {100, 50, 10, 4}) {  // 1%, 0.5%, 0.1%, 0.04%
+      b->Args({n, d});
+    }
+  }
+}
+
+BENCHMARK(BM_SparseTranspose)->Apply(TransposeSizes);