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Added an OpenCL regression test

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This commit is contained in:
Benoit Steiner 2016-12-19 18:56:26 -08:00
parent 0e0d92d34b
commit 548ed30a1c
1 changed files with 44 additions and 0 deletions
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44
unsupported/test/cxx11_tensor_sycl.cpp
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@ -26,6 +26,7 @@ using Eigen::array;
using Eigen::SyclDevice;
using Eigen::Tensor;
using Eigen::TensorMap;
template <typename DataType, int DataLayout>
void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) {
int sizeDim1 = 100;
@ -52,6 +53,7 @@ void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) {
sycl_device.memcpyDeviceToHost(out1.data(), gpu_data1,(out1.size())*sizeof(DataType));
sycl_device.memcpyDeviceToHost(out2.data(), gpu_data1,(out2.size())*sizeof(DataType));
sycl_device.memcpyDeviceToHost(out3.data(), gpu_data2,(out3.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < in1.size(); ++i) {
VERIFY_IS_APPROX(out1(i), in1(i) * 3.14f);
@ -62,6 +64,35 @@ void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) {
sycl_device.deallocate(gpu_data1);
sycl_device.deallocate(gpu_data2);
}
template <typename DataType, int DataLayout>
void test_sycl_mem_sync(const Eigen::SyclDevice &sycl_device) {
int size = 20;
array<int, 1> tensorRange = {{size}};
Tensor<DataType, 1, DataLayout> in1(tensorRange);
Tensor<DataType, 1, DataLayout> in2(tensorRange);
Tensor<DataType, 1, DataLayout> out(tensorRange);
in1 = in1.random();
in2 = in1;
DataType* gpu_data = static_cast<DataType*>(sycl_device.allocate(in1.size()*sizeof(DataType)));
TensorMap<Tensor<DataType, 1, DataLayout>> gpu1(gpu_data, tensorRange);
sycl_device.memcpyHostToDevice(gpu_data, in1.data(),(in1.size())*sizeof(DataType));
sycl_device.synchronize();
in1.setZero();
sycl_device.memcpyDeviceToHost(out.data(), gpu_data, out.size()*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < in1.size(); ++i) {
VERIFY_IS_APPROX(out(i), in2(i));
}
sycl_device.deallocate(gpu_data);
}
template <typename DataType, int DataLayout>
void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
@ -90,6 +121,8 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
/// a=1.2f
gpu_in1.device(sycl_device) = gpu_in1.constant(1.2f);
sycl_device.memcpyDeviceToHost(in1.data(), gpu_in1_data ,(in1.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -102,6 +135,8 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
/// a=b*1.2f
gpu_out.device(sycl_device) = gpu_in1 * 1.2f;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data ,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -116,6 +151,8 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.size())*sizeof(DataType));
gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -130,6 +167,7 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
/// c=a+b
gpu_out.device(sycl_device) = gpu_in1 + gpu_in2;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -144,6 +182,7 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
/// c=a*a
gpu_out.device(sycl_device) = gpu_in1 * gpu_in1;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -158,6 +197,7 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
//a*3.14f + b*2.7f
gpu_out.device(sycl_device) = gpu_in1 * gpu_in1.constant(3.14f) + gpu_in2 * gpu_in2.constant(2.7f);
sycl_device.memcpyDeviceToHost(out.data(),gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -173,6 +213,7 @@ void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
sycl_device.memcpyHostToDevice(gpu_in3_data, in3.data(),(in3.size())*sizeof(DataType));
gpu_out.device(sycl_device) =(gpu_in1 > gpu_in1.constant(0.5f)).select(gpu_in2, gpu_in3);
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(DataType));
sycl_device.synchronize();
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -193,9 +234,12 @@ template<typename DataType, typename dev_Selector> void sycl_computing_test_per_
auto sycl_device = Eigen::SyclDevice(&queueInterface);
test_sycl_mem_transfers<DataType, RowMajor>(sycl_device);
test_sycl_computations<DataType, RowMajor>(sycl_device);
test_sycl_mem_sync<DataType, RowMajor>(sycl_device);
test_sycl_mem_transfers<DataType, ColMajor>(sycl_device);
test_sycl_computations<DataType, ColMajor>(sycl_device);
test_sycl_mem_sync<DataType, ColMajor>(sycl_device);
}
void test_cxx11_tensor_sycl() {
for (const auto& device :Eigen::get_sycl_supported_devices()) {
CALL_SUBTEST(sycl_computing_test_per_device<float>(device));