Merge branch 'gemmlowp' into 'master'

add gemmlowp benchmark

See merge request !680

WORKSPACE

@@ -78,11 +78,10 @@ new_http_archive(
 
 http_archive(
     name = "gemmlowp",
-    sha256 = "b87faa7294dfcc5d678f22a59d2c01ca94ea1e2a3b488c38a95a67889ed0a658",
-    strip_prefix = "gemmlowp-38ebac7b059e84692f53e5938f97a9943c120d98",
+    sha256 = "5941b50afb7f43f96a2afaa101e024b5a1c6b0b4e4f110688fefa083bbdd652d",
+    strip_prefix = "gemmlowp-master-3559cf6e2a21a15b5bd8133bb632da6050aa8b8d",
     urls = [
-        "http://cnbj1.fds.api.xiaomi.com/mace/third-party/gemmlowp/38ebac7b059e84692f53e5938f97a9943c120d98.zip",
-        "https://github.com/google/gemmlowp/archive/38ebac7b059e84692f53e5938f97a9943c120d98.zip",
+        "https://cnbj1.fds.api.xiaomi.com/mace/third-party/gemmlowp/gemmlowp-master-3559cf6e2a21a15b5bd8133bb632da6050aa8b8d.zip",
     ],
 )
 

mace/kernels/BUILD

@@ -70,6 +70,7 @@ cc_library(
     deps = [
         "//mace/core",
         "//mace/utils",
+        "@gemmlowp",
     ],
 )
 
@@ -104,7 +105,7 @@ cc_test(
     deps = [
         ":kernels",
         "//mace/ops",
-        "@gtest//:gtest",
+        "@gtest",
         "@gtest//:gtest_main",
     ],
 )
@@ -133,8 +134,9 @@ cc_test(
     linkstatic = 1,
     deps = [
         ":kernels",
-        "//mace/ops",
         "//mace/core:test_benchmark_main",
+        "//mace/ops",
         "//third_party/eigen3",
+        "@gemmlowp",
     ],
 )

mace/kernels/matmul_benchmark.cc

@@ -15,10 +15,74 @@
 #include <Eigen/Dense>
 #include <algorithm>
 #include <string>
+#include <tuple>
 #include <vector>
 
 #include "mace/core/testing/test_benchmark.h"
 #include "mace/kernels/gemm.h"
+#include "public/gemmlowp.h"
+
+namespace gemmlowp {
+
+template<typename tScalar, MapOrder tOrder>
+class Matrix : public MatrixMap<tScalar, tOrder> {
+ public:
+  typedef MatrixMap<tScalar, tOrder> Map;
+  typedef MatrixMap<const tScalar, tOrder> ConstMap;
+  typedef typename Map::Scalar Scalar;
+  static const MapOrder Order = tOrder;
+  using Map::cols_;
+  using Map::data_;
+  using Map::kOrder;
+  using Map::rows_;
+  using Map::stride_;
+
+ public:
+  Matrix() : Map(nullptr, 0, 0, 0) {}
+
+  Matrix(int rows, int cols) : Map(nullptr, 0, 0, 0) { Resize(rows, cols); }
+
+  Matrix(const Matrix &other) : Map(nullptr, 0, 0, 0) { *this = other; }
+
+  Matrix &operator=(const Matrix &other) {
+    Resize(other.rows_, other.cols_);
+    std::memcpy(data_, other.data_, size() * sizeof(Scalar));
+    return *this;
+  }
+
+  friend bool operator==(const Matrix &a, const Matrix &b) {
+    return a.rows_ == b.rows_ && a.cols_ == b.cols_ &&
+        !std::memcmp(a.data_, b.data_, a.size());
+  }
+
+  void Resize(int rows, int cols) {
+    rows_ = rows;
+    cols_ = cols;
+    stride_ = kOrder == gemmlowp::MapOrder::ColMajor ? rows : cols;
+    storage.resize(size());
+    data_ = storage.data();
+  }
+
+  int size() const { return rows_ * cols_; }
+
+  Map &map() { return *static_cast<Map *>(this); }
+
+  ConstMap const_map() const { return ConstMap(data_, rows_, cols_, stride_); }
+
+ protected:
+  std::vector<Scalar> storage;
+};
+
+template<typename MatrixType>
+void MakeZero(MatrixType *m) {
+  for (int c = 0; c < m->cols(); c++) {
+    for (int r = 0; r < m->rows(); r++) {
+      (*m)(r, c) = 128;
+    }
+  }
+}
+
+}  // namespace gemmlowp
 
 namespace mace {
 namespace kernels {
@@ -55,6 +119,76 @@ void MatmulBenchmark_Eigen(int iters, int m, int k, int n) {
   }
 }
 
+void MatmulBenchmark_gemmlowp_uint8(int iters, int rows, int depth, int cols) {
+  mace::testing::StopTiming();
+
+  gemmlowp::Matrix<std::uint8_t, gemmlowp::MapOrder::RowMajor> lhs;
+  gemmlowp::Matrix<std::uint8_t, gemmlowp::MapOrder::ColMajor> rhs;
+  gemmlowp::Matrix<std::uint8_t, gemmlowp::MapOrder::ColMajor> result;
+  lhs.Resize(rows, depth);
+  rhs.Resize(depth, cols);
+  result.Resize(rows, cols);
+  gemmlowp::MakeZero(&lhs);
+  gemmlowp::MakeZero(&rhs);
+  gemmlowp::MakeZero(&result);
+
+  gemmlowp::OutputStageQuantizeDownInt32ByFixedPoint quantize_down_stage;
+  quantize_down_stage.result_offset_after_shift = 128;
+  quantize_down_stage.result_fixedpoint_multiplier = 1234567890;
+  quantize_down_stage.result_shift = 16;
+  gemmlowp::OutputStageSaturatingCastToUint8 saturating_cast_stage;
+  const auto output_pipeline =
+      std::make_tuple(quantize_down_stage, saturating_cast_stage);
+
+  gemmlowp::GemmContext gemm_context;
+  gemm_context.set_max_num_threads(4);
+  using BitDepthParams = gemmlowp::L8R8WithLhsNonzeroBitDepthParams;
+
+  gemmlowp::GemmWithOutputPipeline<std::uint8_t, std::uint8_t, BitDepthParams>(
+      &gemm_context, lhs.const_map(), rhs.const_map(), &result.map(), -128,
+      -128, output_pipeline);
+
+  mace::testing::StartTiming();
+  while (iters--) {
+    gemmlowp::GemmWithOutputPipeline<std::uint8_t, std::uint8_t,
+                                     BitDepthParams>(
+        &gemm_context, lhs.const_map(), rhs.const_map(), &result.map(), -128,
+        -128, output_pipeline);
+  }
+}
+
+void MatmulBenchmark_gemmlowp_int32(int iters, int rows, int depth, int cols) {
+  mace::testing::StopTiming();
+
+  gemmlowp::Matrix<std::uint8_t, gemmlowp::MapOrder::RowMajor> lhs;
+  gemmlowp::Matrix<std::uint8_t, gemmlowp::MapOrder::ColMajor> rhs;
+  gemmlowp::Matrix<std::int32_t, gemmlowp::MapOrder::ColMajor> result;
+  lhs.Resize(rows, depth);
+  rhs.Resize(depth, cols);
+  result.Resize(rows, cols);
+  gemmlowp::MakeZero(&lhs);
+  gemmlowp::MakeZero(&rhs);
+  gemmlowp::MakeZero(&result);
+
+  const auto output_pipeline = std::make_tuple();
+
+  gemmlowp::GemmContext gemm_context;
+  gemm_context.set_max_num_threads(4);
+  using BitDepthParams = gemmlowp::L8R8WithLhsNonzeroBitDepthParams;
+
+  gemmlowp::GemmWithOutputPipeline<std::uint8_t, std::int32_t, BitDepthParams>(
+      &gemm_context, lhs.const_map(), rhs.const_map(), &result.map(), -128,
+      -128, output_pipeline);
+
+  mace::testing::StartTiming();
+  while (iters--) {
+    gemmlowp::GemmWithOutputPipeline<std::uint8_t, std::int32_t,
+                                     BitDepthParams>(
+        &gemm_context, lhs.const_map(), rhs.const_map(), &result.map(), -128,
+        -128, output_pipeline);
+  }
+}
+
 }  // namespace
 
 #define MACE_BM_MATMUL_FUNC(M, K, N, FUNC)                         \
@@ -69,7 +203,9 @@ void MatmulBenchmark_Eigen(int iters, int m, int k, int n) {
 
 #define MACE_BM_MATMUL(M, K, N)                 \
   MACE_BM_MATMUL_FUNC(M, K, N, Mace);           \
-  MACE_BM_MATMUL_FUNC(M, K, N, Eigen);
+  MACE_BM_MATMUL_FUNC(M, K, N, Eigen);          \
+  MACE_BM_MATMUL_FUNC(M, K, N, gemmlowp_uint8); \
+  MACE_BM_MATMUL_FUNC(M, K, N, gemmlowp_int32);
 
 // Embedding size 384
 MACE_BM_MATMUL(7, 384, 384);