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Added a test to validate memory transfers between host and sycl device

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This commit is contained in:
Benoit Steiner 2016-11-09 06:23:42 -08:00
parent db3903498d
commit 75c080b176
1 changed files with 56 additions and 15 deletions
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71
unsupported/test/cxx11_tensor_sycl.cpp
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@ -27,7 +27,46 @@ using Eigen::SyclDevice;
using Eigen::Tensor;
using Eigen::TensorMap;
void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
void test_sycl_mem_transfers(const Eigen::SyclDevice &sycl_device) {
int sizeDim1 = 100;
int sizeDim2 = 100;
int sizeDim3 = 100;
array<int, 3> tensorRange = {{sizeDim1, sizeDim2, sizeDim3}};
Tensor<float, 3> in1(tensorRange);
Tensor<float, 3> out1(tensorRange);
Tensor<float, 3> out2(tensorRange);
Tensor<float, 3> out3(tensorRange);
in1 = in1.random();
float* gpu_data1 = static_cast<float*>(sycl_device.allocate(in1.size()*sizeof(float)));
float* gpu_data2 = static_cast<float*>(sycl_device.allocate(out1.size()*sizeof(float)));
//float* gpu_data = static_cast<float*>(sycl_device.allocate(out2.size()*sizeof(float)));
TensorMap<Tensor<float, 3>> gpu1(gpu_data1, tensorRange);
TensorMap<Tensor<float, 3>> gpu2(gpu_data2, tensorRange);
//TensorMap<Tensor<float, 3>> gpu_out2(gpu_out2_data, tensorRange);
sycl_device.memcpyHostToDevice(gpu_data1, in1.data(),(in1.size())*sizeof(float));
sycl_device.memcpyHostToDevice(gpu_data2, in1.data(),(in1.size())*sizeof(float));
gpu1.device(sycl_device) = gpu1 * 3.14f;
gpu2.device(sycl_device) = gpu2 * 2.7f;
sycl_device.memcpyDeviceToHost(out1.data(), gpu_data1,(out1.size())*sizeof(float));
sycl_device.memcpyDeviceToHost(out2.data(), gpu_data1,(out2.size())*sizeof(float));
sycl_device.memcpyDeviceToHost(out3.data(), gpu_data2,(out3.size())*sizeof(float));
// sycl_device.Synchronize();
for (int i = 0; i < in1.size(); ++i) {
VERIFY_IS_APPROX(out1(i), in1(i) * 3.14f);
VERIFY_IS_APPROX(out2(i), in1(i) * 3.14f);
VERIFY_IS_APPROX(out3(i), in1(i) * 2.7f);
}
sycl_device.deallocate(gpu_data1);
sycl_device.deallocate(gpu_data2);
}
void test_sycl_computations(const Eigen::SyclDevice &sycl_device) {
int sizeDim1 = 100;
int sizeDim2 = 100;
@ -41,10 +80,10 @@ void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
in2 = in2.random();
in3 = in3.random();
float * gpu_in1_data = static_cast<float*>(sycl_device.allocate(in1.dimensions().TotalSize()*sizeof(float)));
float * gpu_in2_data = static_cast<float*>(sycl_device.allocate(in2.dimensions().TotalSize()*sizeof(float)));
float * gpu_in3_data = static_cast<float*>(sycl_device.allocate(in3.dimensions().TotalSize()*sizeof(float)));
float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
float * gpu_in1_data = static_cast<float*>(sycl_device.allocate(in1.size()*sizeof(float)));
float * gpu_in2_data = static_cast<float*>(sycl_device.allocate(in2.size()*sizeof(float)));
float * gpu_in3_data = static_cast<float*>(sycl_device.allocate(in3.size()*sizeof(float)));
float * gpu_out_data = static_cast<float*>(sycl_device.allocate(out.size()*sizeof(float)));
TensorMap<Tensor<float, 3>> gpu_in1(gpu_in1_data, tensorRange);
TensorMap<Tensor<float, 3>> gpu_in2(gpu_in2_data, tensorRange);
@ -53,7 +92,7 @@ void test_sycl_cpu(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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(in1.data(), gpu_in1_data ,(in1.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -65,7 +104,7 @@ void test_sycl_cpu(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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data ,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -77,9 +116,9 @@ void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
printf("a=b*1.2f Test Passed\n");
/// c=a*b
sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyHostToDevice(gpu_in2_data, in2.data(),(in2.size())*sizeof(float));
gpu_out.device(sycl_device) = gpu_in1 * gpu_in2;
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -93,7 +132,7 @@ void test_sycl_cpu(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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -107,7 +146,7 @@ void test_sycl_cpu(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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -121,7 +160,7 @@ void test_sycl_cpu(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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(),gpu_out_data,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -134,9 +173,9 @@ void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
printf("a*3.14f + b*2.7f Test Passed\n");
///d= (a>0.5? b:c)
sycl_device.memcpyHostToDevice(gpu_in3_data, in3.data(),(in3.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyHostToDevice(gpu_in3_data, in3.data(),(in3.size())*sizeof(float));
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.dimensions().TotalSize())*sizeof(float));
sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.size())*sizeof(float));
for (int i = 0; i < sizeDim1; ++i) {
for (int j = 0; j < sizeDim2; ++j) {
for (int k = 0; k < sizeDim3; ++k) {
@ -152,8 +191,10 @@ void test_sycl_cpu(const Eigen::SyclDevice &sycl_device) {
sycl_device.deallocate(gpu_in3_data);
sycl_device.deallocate(gpu_out_data);
}
void test_cxx11_tensor_sycl() {
cl::sycl::gpu_selector s;
Eigen::SyclDevice sycl_device(s);
CALL_SUBTEST(test_sycl_cpu(sycl_device));
CALL_SUBTEST(test_sycl_mem_transfers(sycl_device));
CALL_SUBTEST(test_sycl_computations(sycl_device));
}