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Created a test to check that the sycl runtime can successfully report errors (like ivision by 0).

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Small cleanup
This commit is contained in:
Benoit Steiner 2016-11-17 20:27:54 -08:00
parent 004344cf54
commit 4349fc640e
2 changed files with 30 additions and 9 deletions
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3
unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
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@ -158,10 +158,9 @@ struct SyclDevice {
}); });
}); });
m_queue.throw_asynchronous(); m_queue.throw_asynchronous();
} else{ } else {
eigen_assert("no source or destination device memory found."); eigen_assert("no source or destination device memory found.");
} }
//::memcpy(dst, src, n);
} }
/// The memcpyHostToDevice is used to copy the device only pointer to a host pointer. Using the device /// The memcpyHostToDevice is used to copy the device only pointer to a host pointer. Using the device

36
unsupported/test/cxx11_tensor_device_sycl.cpp
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@ -21,24 +21,46 @@
#include <unsupported/Eigen/CXX11/Tensor> #include <unsupported/Eigen/CXX11/Tensor>
#include<stdint.h> #include<stdint.h>
void test_device_sycl(const Eigen::SyclDevice &sycl_device) { void test_device_memory(const Eigen::SyclDevice &sycl_device) {
std::cout <<"Helo from ComputeCpp: the requested device exists and the device name is : " std::cout << "Running on: "
<< sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>() <<std::endl;; << sycl_device.m_queue.get_device(). template get_info<cl::sycl::info::device::name>()
<< std::endl;
int sizeDim1 = 100; int sizeDim1 = 100;
array<int, 1> tensorRange = {{sizeDim1}}; array<int, 1> tensorRange = {{sizeDim1}};
Tensor<int, 1> in(tensorRange); Tensor<int, 1> in(tensorRange);
Tensor<int, 1> in1(tensorRange); Tensor<int, 1> in1(tensorRange);
memset(in1.data(), 1,in1.size()*sizeof(int)); memset(in1.data(), 1,in1.size()*sizeof(int));
int * gpu_in_data = static_cast<int*>(sycl_device.allocate(in.size()*sizeof(int))); int* gpu_in_data = static_cast<int*>(sycl_device.allocate(in.size()*sizeof(int)));
sycl_device.memset(gpu_in_data, 1,in.size()*sizeof(int) ); sycl_device.memset(gpu_in_data, 1, in.size()*sizeof(int) );
sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(int) ); sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(int) );
for (int i=0; i<in.size(); i++) for (int i=0; i<in.size(); i++) {
VERIFY_IS_APPROX(in(i), in1(i)); VERIFY_IS_APPROX(in(i), in1(i));
}
sycl_device.deallocate(gpu_in_data); sycl_device.deallocate(gpu_in_data);
} }
void test_device_exceptions(const Eigen::SyclDevice &sycl_device) {
bool threw_exception = false;
array<int, 1> tensorDims = {{100}};
int* gpu_data = static_cast<int*>(sycl_device.allocate(100*sizeof(int)));
TensorMap<Tensor<int, 1>> in(gpu_data, tensorDims);
TensorMap<Tensor<int, 1>> out(gpu_data, tensorDims);
try {
out.device(sycl_device) = in / in.constant(0);
} catch(...) {
threw_exception = true;
}
VERIFY(threw_exception);
sycl_device.deallocate(gpu_data);
}
void test_cxx11_tensor_device_sycl() { void test_cxx11_tensor_device_sycl() {
cl::sycl::gpu_selector s; cl::sycl::gpu_selector s;
Eigen::SyclDevice sycl_device(s); Eigen::SyclDevice sycl_device(s);
CALL_SUBTEST(test_device_sycl(sycl_device)); CALL_SUBTEST(test_device_memory(sycl_device));
// This deadlocks
// CALL_SUBTEST(test_device_exceptions(sycl_device));
} }