Update the sizes in small_blas_gem?_benchmark.cc
The sizes are reflective of the matrix sizes
that occur in production.
Change-Id: I8cd85d0640702df09afafced0d28ef416bab946f
diff --git a/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemm_benchmark.json b/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemm_benchmark.json
index 0c67c43..e24572d 100644
--- a/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemm_benchmark.json
+++ b/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemm_benchmark.json
@@ -1,6 +1,6 @@
{
"context": {
- "date": "2018-02-28 19:43:04",
+ "date": "2018-03-23 13:15:00",
"num_cpus": 8,
"mhz_per_cpu": 2200,
"cpu_scaling_enabled": false,
@@ -8,2159 +8,3825 @@
},
"benchmarks": [
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diff --git a/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemv_benchmark.json b/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemv_benchmark.json
index 3e483a2..a8a7795 100644
--- a/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemv_benchmark.json
+++ b/internal/ceres/benchmarks/macbook-pro-2014-small_blas_gemv_benchmark.json
@@ -1,6 +1,6 @@
{
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+ "date": "2018-03-23 13:34:44",
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- "cpu_time": 2.4129585986333215e+01,
+ "iterations": 35709549,
+ "real_time": 1.9691253563928413e+01,
+ "cpu_time": 1.9687591125835635e+01,
"time_unit": "ns"
},
{
- "name": "BM_MatrixTransposeVectorMultiply/4/6",
- "iterations": 20036065,
- "real_time": 3.4106466514085753e+01,
- "cpu_time": 3.3619725230478345e+01,
- "time_unit": "ns"
- },
- {
- "name": "BM_MatrixTransposeVectorMultiply/4/7",
- "iterations": 18768417,
- "real_time": 3.6661212077921938e+01,
- "cpu_time": 3.6314090847405801e+01,
+ "name": "BM_MatrixTransposeVectorMultiply/4/8",
+ "iterations": 20404356,
+ "real_time": 3.3671754796556790e+01,
+ "cpu_time": 3.3668153996136844e+01,
"time_unit": "ns"
},
{
"name": "BM_MatrixTransposeVectorMultiply/4/12",
- "iterations": 11789871,
- "real_time": 6.1986798330774114e+01,
- "cpu_time": 6.1171322400389727e+01,
+ "iterations": 15090728,
+ "real_time": 4.7125273353021399e+01,
+ "cpu_time": 4.7122776316689396e+01,
"time_unit": "ns"
},
{
- "name": "BM_MatrixTransposeVectorMultiply/4/16",
- "iterations": 7869236,
- "real_time": 8.5527959635890710e+01,
- "cpu_time": 8.2749964545479799e+01,
+ "name": "BM_MatrixTransposeVectorMultiply/4/15",
+ "iterations": 11336950,
+ "real_time": 6.2453472226796620e+01,
+ "cpu_time": 6.2451805820789019e+01,
"time_unit": "ns"
},
{
- "name": "BM_MatrixTransposeVectorMultiply/4/20",
- "iterations": 7417847,
- "real_time": 9.9073482499474821e+01,
- "cpu_time": 9.7701125407411183e+01,
+ "name": "BM_MatrixTransposeVectorMultiply/6/1",
+ "iterations": 65892276,
+ "real_time": 1.0683369458878103e+01,
+ "cpu_time": 1.0683331078137206e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/2",
+ "iterations": 45151386,
+ "real_time": 1.5743454386474488e+01,
+ "cpu_time": 1.5741886638873094e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/3",
+ "iterations": 35555194,
+ "real_time": 2.0272604644448467e+01,
+ "cpu_time": 2.0265815453011015e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/4",
+ "iterations": 28844688,
+ "real_time": 2.4899265682219198e+01,
+ "cpu_time": 2.4896646481320971e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/8",
+ "iterations": 16677944,
+ "real_time": 4.2613494320617384e+01,
+ "cpu_time": 4.2610288174610147e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/12",
+ "iterations": 10657572,
+ "real_time": 6.7212158173757643e+01,
+ "cpu_time": 6.7206583263055407e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/6/15",
+ "iterations": 8660580,
+ "real_time": 8.0843434848483710e+01,
+ "cpu_time": 8.0843430809486151e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/1",
+ "iterations": 57066458,
+ "real_time": 1.2319644088657304e+01,
+ "cpu_time": 1.2319338270477425e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/2",
+ "iterations": 38263912,
+ "real_time": 1.8003573181401965e+01,
+ "cpu_time": 1.7997610908158087e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/3",
+ "iterations": 29869088,
+ "real_time": 2.4137524754083010e+01,
+ "cpu_time": 2.4137328866552775e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/4",
+ "iterations": 22616613,
+ "real_time": 3.0444019799836454e+01,
+ "cpu_time": 3.0442931485806785e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/8",
+ "iterations": 12552902,
+ "real_time": 5.4102999925791671e+01,
+ "cpu_time": 5.4099761154830723e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/12",
+ "iterations": 9204229,
+ "real_time": 7.7715734577381653e+01,
+ "cpu_time": 7.7705802408872202e+01,
+ "time_unit": "ns"
+ },
+ {
+ "name": "BM_MatrixTransposeVectorMultiply/8/15",
+ "iterations": 7493764,
+ "real_time": 9.3483444364895007e+01,
+ "cpu_time": 9.3483461715635883e+01,
"time_unit": "ns"
}
]
diff --git a/internal/ceres/small_blas_gemm_benchmark.cc b/internal/ceres/small_blas_gemm_benchmark.cc
index 748858b..0a760a5 100644
--- a/internal/ceres/small_blas_gemm_benchmark.cc
+++ b/internal/ceres/small_blas_gemm_benchmark.cc
@@ -34,6 +34,7 @@
#include "ceres/small_blas.h"
namespace ceres {
+namespace internal {
// Benchmarking matrix-matrix multiply routines and optimizing memory
// access requires that we make sure that they are not just sitting in
@@ -46,20 +47,19 @@
class MatrixMatrixMultiplyData {
public:
MatrixMatrixMultiplyData(
- int a_rows, int a_cols, int b_rows, int b_cols, int c_rows, int c_cols) {
- num_elements_ = 1000;
- a_size_ = a_rows * a_cols;
- b_size_ = b_rows * b_cols;
- c_size_ = c_cols * c_cols;
- a_.resize(num_elements_ * a_size_, 1.00001);
- b_.resize(num_elements_ * b_size_, 1.00002);
- c_.resize(num_elements_ * c_size_, 1.00003);
- }
+ int a_rows, int a_cols, int b_rows, int b_cols, int c_rows, int c_cols)
+ : num_elements_(1000),
+ a_size_(a_rows * a_cols),
+ b_size_(b_rows * b_cols),
+ c_size_(c_rows * c_cols),
+ a_(num_elements_ * a_size_, 1.00001),
+ b_(num_elements_ * b_size_, 0.5),
+ c_(num_elements_ * c_size_, -1.1) {}
int num_elements() const { return num_elements_; }
- double* GetA(int i) { return &a_[i * a_size_]; };
- double* GetB(int i) { return &b_[i * b_size_]; };
- double* GetC(int i) { return &c_[i * c_size_]; };
+ double* GetA(int i) { return &a_[i * a_size_]; }
+ double* GetB(int i) { return &b_[i * b_size_]; }
+ double* GetC(int i) { return &c_[i * c_size_]; }
private:
int num_elements_;
@@ -73,9 +73,9 @@
static void MatrixMatrixMultiplySizeArguments(
benchmark::internal::Benchmark* benchmark) {
- std::vector<int> b_rows = {2, 4, 6, 8};
- std::vector<int> b_cols = {2, 4, 6, 8, 10, 12, 15};
- std::vector<int> c_cols = {2, 4, 6, 8, 10, 12, 15};
+ const std::vector<int> b_rows = {1, 2, 3, 4, 6, 8};
+ const std::vector<int> b_cols = {1, 2, 3, 4, 8, 12, 15};
+ const std::vector<int> c_cols = b_cols;
for (int i : b_rows) {
for (int j : b_cols) {
for (int k : c_cols) {
@@ -86,24 +86,29 @@
}
void BM_MatrixMatrixMultiplyDynamic(benchmark::State& state) {
- const int b_rows = state.range(0);
- const int b_cols = state.range(1);
- const int c_cols = state.range(2);
- MatrixMatrixMultiplyData data(b_rows, c_cols, b_rows, b_cols, b_cols, c_cols);
+ const int i = state.range(0);
+ const int j = state.range(1);
+ const int k = state.range(2);
+ const int b_rows = i;
+ const int b_cols = j;
+ const int c_rows = b_cols;
+ const int c_cols = k;
+ const int a_rows = b_rows;
+ const int a_cols = c_cols;
+
+ MatrixMatrixMultiplyData data(a_rows, a_cols, b_rows, b_cols, c_rows, c_cols);
const int num_elements = data.num_elements();
- int i = 0;
+
+ int iter = 0;
for (auto _ : state) {
- i = (i + 1) % num_elements;
// a += b * c
- internal::MatrixMatrixMultiply<Eigen::Dynamic,
- Eigen::Dynamic,
- Eigen::Dynamic,
- Eigen::Dynamic,
- 1>(data.GetB(i), b_rows, b_cols,
- data.GetC(i), b_cols, c_cols,
- data.GetA(i), 0, 0, b_rows, c_cols);
- i = (i + 1) % num_elements;
+ MatrixMatrixMultiply
+ <Eigen::Dynamic, Eigen::Dynamic,Eigen::Dynamic,Eigen::Dynamic, 1>
+ (data.GetB(iter), b_rows, b_cols,
+ data.GetC(iter), c_rows, c_cols,
+ data.GetA(iter), 0, 0, a_rows, a_cols);
+ iter = (iter + 1) % num_elements;
}
}
@@ -112,9 +117,9 @@
static void MatrixTransposeMatrixMultiplySizeArguments(
benchmark::internal::Benchmark* benchmark) {
- std::vector<int> b_rows = {2, 4, 6, 8};
- std::vector<int> b_cols = {2, 4, 5, 8, 10, 12, 15};
- std::vector<int> c_cols = {2, 4, 6, 8};
+ std::vector<int> b_rows = {1, 2, 3, 4, 6, 8};
+ std::vector<int> b_cols = {1, 2, 3, 4, 8, 12, 15};
+ std::vector<int> c_cols = b_rows;
for (int i : b_rows) {
for (int j : b_cols) {
for (int k : c_cols) {
@@ -125,30 +130,36 @@
}
void BM_MatrixTransposeMatrixMultiplyDynamic(benchmark::State& state) {
- const int b_rows = state.range(0);
- const int b_cols = state.range(1);
- const int c_cols = state.range(2);
- MatrixMatrixMultiplyData data(b_cols, c_cols, b_rows, b_cols, b_cols, c_cols);
+ const int i = state.range(0);
+ const int j = state.range(1);
+ const int k = state.range(2);
+ const int b_rows = i;
+ const int b_cols = j;
+ const int c_rows = b_rows;
+ const int c_cols = k;
+ const int a_rows = b_cols;
+ const int a_cols = c_cols;
+
+ MatrixMatrixMultiplyData data(a_rows, a_cols, b_rows, b_cols, c_rows, c_cols);
const int num_elements = data.num_elements();
- int i = 0;
+
+ int iter = 0;
for (auto _ : state) {
- i = (i + 1) % num_elements;
- // a += b * c
- internal::MatrixTransposeMatrixMultiply<Eigen::Dynamic,
- Eigen::Dynamic,
- Eigen::Dynamic,
- Eigen::Dynamic,
- 1>(data.GetB(i), b_rows, b_cols,
- data.GetC(i), b_cols, c_cols,
- data.GetA(i), 0, 0, b_cols, c_cols);
- i = (i + 1) % num_elements;
+ // a += b' * c
+ MatrixTransposeMatrixMultiply
+ <Eigen::Dynamic,Eigen::Dynamic,Eigen::Dynamic,Eigen::Dynamic, 1>
+ (data.GetB(iter), b_rows, b_cols,
+ data.GetC(iter), c_rows, c_cols,
+ data.GetA(iter), 0, 0, a_rows, a_cols);
+ iter = (iter + 1) % num_elements;
}
}
BENCHMARK(BM_MatrixTransposeMatrixMultiplyDynamic)
->Apply(MatrixTransposeMatrixMultiplySizeArguments);
+} // internal
} // namespace ceres
BENCHMARK_MAIN();
diff --git a/internal/ceres/small_blas_gemv_benchmark.cc b/internal/ceres/small_blas_gemv_benchmark.cc
index 513ff12..4b587bf 100644
--- a/internal/ceres/small_blas_gemv_benchmark.cc
+++ b/internal/ceres/small_blas_gemv_benchmark.cc
@@ -44,25 +44,23 @@
// matrix and vector objects for use in the benchmark.
class MatrixVectorMultiplyData {
public:
- MatrixVectorMultiplyData(int rows, int cols) {
- rows_ = rows;
- cols_ = cols;
-
- num_elements_ = 1000;
- a_.resize(num_elements_ * rows, 1.00001);
- b_.resize(num_elements_ * rows * cols, 1.00002);
- c_.resize(num_elements_ * cols, 1.00003);
- }
+ 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_]; };
+ 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:
- int num_elements_;
- int rows_;
- int cols_;
+ const int num_elements_;
+ const int rows_;
+ const int cols_;
std::vector<double> a_;
std::vector<double> b_;
std::vector<double> c_;
@@ -71,8 +69,8 @@
// 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};
- std::vector<int> cols = {1, 2, 3, 4, 6, 7, 12, 16, 20};
+ 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});
@@ -85,12 +83,12 @@
const int cols = state.range(1);
MatrixVectorMultiplyData data(rows, cols);
const int num_elements = data.num_elements();
- int i = 0;
+ int iter = 0;
for (auto _ : state) {
// A += B * C;
internal::MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- data.GetB(i), rows, cols, data.GetC(i), data.GetA(i));
- i = (i + 1) % num_elements;
+ data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter));
+ iter = (iter + 1) % num_elements;
}
}
@@ -101,11 +99,11 @@
const int cols = state.range(1);
MatrixVectorMultiplyData data(cols, rows);
const int num_elements = data.num_elements();
- int i = 0;
+ int iter = 0;
for (auto _ : state) {
internal::MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- data.GetB(i), rows, cols, data.GetC(i), data.GetA(i));
- i = (i + 1) % num_elements;
+ data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter));
+ iter = (iter + 1) % num_elements;
}
}
