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Adding EIGEN_STRONG_INLINE back; using size() instead of dimensions.TotalSize() on Tensor.

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This commit is contained in:
Mehdi Goli 2016-11-10 19:16:31 +00:00
parent 12387abad5
commit 3be3963021
2 changed files with 15 additions and 15 deletions
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20
unsupported/Eigen/CXX11/src/Tensor/TensorDeviceSycl.h
View File

@ -44,14 +44,14 @@ struct SyclDevice {
// destructor
~SyclDevice() { deallocate_all(); }
template <typename T> void deallocate(T *p) const {
template <typename T> EIGEN_STRONG_INLINE void deallocate(T *p) const {
auto it = buffer_map.find(p);
if (it != buffer_map.end()) {
buffer_map.erase(it);
internal::aligned_free(p);
}
}
void deallocate_all() const {
EIGEN_STRONG_INLINE void deallocate_all() const {
std::map<const void *, std::shared_ptr<void>>::iterator it=buffer_map.begin();
while (it!=buffer_map.end()) {
auto p=it->first;
@ -88,23 +88,23 @@ struct SyclDevice {
}
/// allocating memory on the cpu
void *allocate(size_t) const {
EIGEN_STRONG_INLINE void *allocate(size_t) const {
return internal::aligned_malloc(8);
}
// some runtime conditions that can be applied here
bool isDeviceSuitable() const { return true; }
EIGEN_STRONG_INLINE bool isDeviceSuitable() const { return true; }
void memcpy(void *dst, const void *src, size_t n) const {
EIGEN_STRONG_INLINE void memcpy(void *dst, const void *src, size_t n) const {
::memcpy(dst, src, n);
}
template<typename T> void memcpyHostToDevice(T *dst, const T *src, size_t n) const {
template<typename T> EIGEN_STRONG_INLINE void memcpyHostToDevice(T *dst, const T *src, size_t n) const {
auto host_acc= (static_cast<cl::sycl::buffer<T, 1>*>(add_sycl_buffer(dst, n).first->second.get()))-> template get_access<cl::sycl::access::mode::discard_write, cl::sycl::access::target::host_buffer>();
memcpy(host_acc.get_pointer(), src, n);
}
inline void parallel_for_setup(size_t n, size_t &tileSize, size_t &rng, size_t &GRange) const {
EIGEN_STRONG_INLINE void parallel_for_setup(size_t n, size_t &tileSize, size_t &rng, size_t &GRange) const {
tileSize =m_queue.get_device(). template get_info<cl::sycl::info::device::max_work_group_size>()/2;
rng = n;
if (rng==0) rng=1;
@ -116,7 +116,7 @@ struct SyclDevice {
}
}
template<typename T> void memcpyDeviceToHost(T *dst, const T *src, size_t n) const {
template<typename T> EIGEN_STRONG_INLINE void memcpyDeviceToHost(T *dst, const T *src, size_t n) const {
auto it = buffer_map.find(src);
if (it != buffer_map.end()) {
size_t rng, GRange, tileSize;
@ -141,7 +141,7 @@ struct SyclDevice {
}
}
template<typename T> void memset(T *buff, int c, size_t n) const {
template<typename T> EIGEN_STRONG_INLINE void memset(T *buff, int c, size_t n) const {
size_t rng, GRange, tileSize;
parallel_for_setup(n/sizeof(T), tileSize, rng, GRange);
@ -158,7 +158,7 @@ struct SyclDevice {
});
m_queue.throw_asynchronous();
}
int majorDeviceVersion() const {
EIGEN_STRONG_INLINE int majorDeviceVersion() const {
return 1;
}
};

10
unsupported/test/cxx11_tensor_device_sycl.cpp
View File

@ -29,11 +29,11 @@ void test_device_sycl(const Eigen::SyclDevice &sycl_device) {
array<int, 1> tensorRange = {{sizeDim1}};
Tensor<int, 1> in(tensorRange);
Tensor<int, 1> in1(tensorRange);
memset(in1.data(), 1,in1.dimensions().TotalSize()*sizeof(int));
int * gpu_in_data = static_cast<int*>(sycl_device.allocate(in.dimensions().TotalSize()*sizeof(int)));
sycl_device.memset(gpu_in_data, 1,in.dimensions().TotalSize()*sizeof(int) );
sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.dimensions().TotalSize()*sizeof(int) );
for (int i=0; i<in.dimensions().TotalSize(); i++)
memset(in1.data(), 1,in1.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.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(int) );
for (int i=0; i<in.size(); i++)
VERIFY_IS_APPROX(in(i), in1(i));
sycl_device.deallocate(gpu_in_data);
}