Add new benchmarks for Core, LU, and QR operations

libeigen/eigen!2177

Closes #3035

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

benchmarks/Core/bench_block_ops.cpp

@@ -0,0 +1,89 @@
+// Benchmarks for block extraction and assignment operations.
+//
+// Tests sub-matrix views: block(), topRows(), leftCols(), middleCols().
+// Measures expression template overhead for read and write patterns.
+
+#include <benchmark/benchmark.h>
+#include <Eigen/Core>
+
+using namespace Eigen;
+
+// Read a block and assign to a separate matrix (forces evaluation).
+template <typename Scalar>
+static void BM_BlockRead(benchmark::State& state) {
+  const Index n = state.range(0);
+  const Index block_size = state.range(1);
+  using Mat = Matrix<Scalar, Dynamic, Dynamic>;
+  Mat src = Mat::Random(n, n);
+  Mat dst(block_size, block_size);
+  const Index off = (n - block_size) / 2;
+  for (auto _ : state) {
+    dst = src.block(off, off, block_size, block_size);
+    benchmark::DoNotOptimize(dst.data());
+  }
+  state.SetBytesProcessed(state.iterations() * block_size * block_size * sizeof(Scalar));
+}
+
+// Write into a block of a larger matrix.
+template <typename Scalar>
+static void BM_BlockWrite(benchmark::State& state) {
+  const Index n = state.range(0);
+  const Index block_size = state.range(1);
+  using Mat = Matrix<Scalar, Dynamic, Dynamic>;
+  Mat dst = Mat::Random(n, n);
+  Mat src = Mat::Random(block_size, block_size);
+  const Index off = (n - block_size) / 2;
+  for (auto _ : state) {
+    dst.block(off, off, block_size, block_size) = src;
+    benchmark::DoNotOptimize(dst.data());
+  }
+  state.SetBytesProcessed(state.iterations() * block_size * block_size * sizeof(Scalar));
+}
+
+// topRows extraction.
+template <typename Scalar>
+static void BM_TopRows(benchmark::State& state) {
+  const Index n = state.range(0);
+  const Index k = state.range(1);
+  using Mat = Matrix<Scalar, Dynamic, Dynamic>;
+  Mat src = Mat::Random(n, n);
+  Mat dst(k, n);
+  for (auto _ : state) {
+    dst = src.topRows(k);
+    benchmark::DoNotOptimize(dst.data());
+  }
+  state.SetBytesProcessed(state.iterations() * k * n * sizeof(Scalar));
+}
+
+// leftCols extraction.
+template <typename Scalar>
+static void BM_LeftCols(benchmark::State& state) {
+  const Index n = state.range(0);
+  const Index k = state.range(1);
+  using Mat = Matrix<Scalar, Dynamic, Dynamic>;
+  Mat src = Mat::Random(n, n);
+  Mat dst(n, k);
+  for (auto _ : state) {
+    dst = src.leftCols(k);
+    benchmark::DoNotOptimize(dst.data());
+  }
+  state.SetBytesProcessed(state.iterations() * n * k * sizeof(Scalar));
+}
+
+static void BlockSizes(::benchmark::Benchmark* b) {
+  // (matrix_size, block_size)
+  for (int n : {256, 512, 1024}) {
+    for (int bs : {16, 64, 128}) {
+      if (bs <= n) b->Args({n, bs});
+    }
+  }
+}
+
+BENCHMARK(BM_BlockRead<float>)->Apply(BlockSizes)->Name("BlockRead_float");
+BENCHMARK(BM_BlockRead<double>)->Apply(BlockSizes)->Name("BlockRead_double");
+BENCHMARK(BM_BlockWrite<float>)->Apply(BlockSizes)->Name("BlockWrite_float");
+BENCHMARK(BM_BlockWrite<double>)->Apply(BlockSizes)->Name("BlockWrite_double");
+BENCHMARK(BM_TopRows<float>)->Apply(BlockSizes)->Name("TopRows_float");
+BENCHMARK(BM_TopRows<double>)->Apply(BlockSizes)->Name("TopRows_double");
+BENCHMARK(BM_LeftCols<float>)->Apply(BlockSizes)->Name("LeftCols_float");
+BENCHMARK(BM_LeftCols<double>)->Apply(BlockSizes)->Name("LeftCols_double");