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-rw-r--r--bench/tensors/tensor_benchmarks.h106
1 files changed, 92 insertions, 14 deletions
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index c2fb3dede..325026113 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -35,6 +35,11 @@ template <typename Device, typename T> class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
@@ -55,7 +60,11 @@ template <typename Device, typename T> class BenchmarkSuite {
}
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ B.device(device_) = A.template cast<T>();
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
@@ -70,7 +79,6 @@ template <typename Device, typename T> class BenchmarkSuite {
sizes[0] = m_;
sizes[1] = m_;
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = C.random();
@@ -93,7 +101,18 @@ template <typename Device, typename T> class BenchmarkSuite {
const Eigen::DSizes<TensorIndex, 2> second_quadrant(0, m_/2);
const Eigen::DSizes<TensorIndex, 2> third_quadrant(m_/2, 0);
const Eigen::DSizes<TensorIndex, 2> fourth_quadrant(m_/2, m_/2);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.slice(first_quadrant, quarter_sizes).device(device_) =
+ A.slice(first_quadrant, quarter_sizes);
+ C.slice(second_quadrant, quarter_sizes).device(device_) =
+ B.slice(second_quadrant, quarter_sizes);
+ C.slice(third_quadrant, quarter_sizes).device(device_) =
+ A.slice(third_quadrant, quarter_sizes);
+ C.slice(fourth_quadrant, quarter_sizes).device(device_) =
+ B.slice(fourth_quadrant, quarter_sizes);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.slice(first_quadrant, quarter_sizes).device(device_) =
@@ -118,7 +137,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = B.chip(iter % k_, 0);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.chip(iter % k_, 0);
@@ -135,7 +158,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = B.chip(iter % n_, 1);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
@@ -158,7 +185,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ B.device(device_) = A.shuffle(shuffle);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
@@ -186,7 +217,11 @@ template <typename Device, typename T> class BenchmarkSuite {
paddings[0] = Eigen::IndexPair<TensorIndex>(0, 0);
paddings[1] = Eigen::IndexPair<TensorIndex>(2, 1);
#endif
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ B.device(device_) = A.pad(paddings);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.pad(paddings);
@@ -216,6 +251,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::IndexList<Eigen::type2index<1>, Eigen::type2index<2> > strides;
#endif
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ B.device(device_) = A.stride(strides);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.stride(strides);
@@ -245,6 +285,11 @@ template <typename Device, typename T> class BenchmarkSuite {
broadcast.set(1, n_);
#endif
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A.broadcast(broadcast);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.broadcast(broadcast);
@@ -261,7 +306,11 @@ template <typename Device, typename T> class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A * A.constant(static_cast<T>(3.14)) + B * B.constant(static_cast<T>(2.7));
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A * A.constant(static_cast<T>(3.14)) + B * B.constant(static_cast<T>(2.7));
@@ -280,6 +329,11 @@ template <typename Device, typename T> class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
+}
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
@@ -297,7 +351,11 @@ template <typename Device, typename T> class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A.exp() + B.log();
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.exp() + B.log();
@@ -325,7 +383,11 @@ template <typename Device, typename T> class BenchmarkSuite {
// optimize the code.
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
#endif
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = B.sum(sum_along_dim);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
@@ -355,7 +417,11 @@ template <typename Device, typename T> class BenchmarkSuite {
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
#endif
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = B.sum(sum_along_dim);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
@@ -375,7 +441,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(
c_, output_size);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = B.sum();
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
@@ -404,7 +474,11 @@ template <typename Device, typename T> class BenchmarkSuite {
typedef typename Tensor<T, 2>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims;
dims[0] = DimPair(1, 0);
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A.contract(B, dims);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.contract(B, dims);
@@ -430,7 +504,11 @@ template <typename Device, typename T> class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-
+#ifdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter < 10; ++iter) {
+ C.device(device_) = A.convolve(B, dims);
+ }
+#endif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
generated by cgit v1.2.3 (git 2.39.1) at 2024-05-15 10:01:46 +0000