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Restyle statistics kernels #116

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Oct 5, 2020
Merged

Restyle statistics kernels #116

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53 changes: 28 additions & 25 deletions dpnp/backend/custom_kernels_statistics.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -118,20 +118,22 @@ void custom_cov_c(void* array1_in, void* result1, size_t nrows, size_t ncols)
// fill lower elements
cl::sycl::event event;
cl::sycl::range<1> gws(nrows * nrows);
event = DPNP_QUEUE.submit([&](cl::sycl::handler& cgh) {
cgh.parallel_for<class custom_cov_c_kernel<_DataType> >(
gws,
[=](cl::sycl::id<1> global_id)
{
const size_t idx = global_id[0];
const size_t row_idx = idx / nrows;
const size_t col_idx = idx - row_idx * nrows;
if (col_idx < row_idx)
{
result[idx] = result[col_idx * nrows + row_idx];
}
}); // parallel_for
}); // queue.submit
auto kernel_parallel_for_func = [=](cl::sycl::id<1> global_id) {
const size_t idx = global_id[0];
const size_t row_idx = idx / nrows;
const size_t col_idx = idx - row_idx * nrows;
if (col_idx < row_idx)
{
result[idx] = result[col_idx * nrows + row_idx];
}
};

auto kernel_func = [&](cl::sycl::handler& cgh) {
cgh.parallel_for<class custom_cov_c_kernel<_DataType> >(gws, kernel_parallel_for_func);
};

event = DPNP_QUEUE.submit(kernel_func);

event.wait();

dpnp_memory_free_c(mean);
Expand Down Expand Up @@ -350,18 +352,19 @@ void custom_var_c(
_ResultType* squared_deviations = reinterpret_cast<_ResultType*>(dpnp_memory_alloc_c(size * sizeof(_ResultType)));

cl::sycl::range<1> gws(size);
event = DPNP_QUEUE.submit([&](cl::sycl::handler& cgh) {
cgh.parallel_for<class custom_var_c_kernel<_DataType, _ResultType> >(
gws,
[=](cl::sycl::id<1> global_id)
auto kernel_parallel_for_func = [=](cl::sycl::id<1> global_id) {
size_t i = global_id[0]; /*for (size_t i = 0; i < size; ++i)*/
{
size_t i = global_id[0]; /*for (size_t i = 0; i < size; ++i)*/
{
_ResultType deviation = static_cast<_ResultType>(array1[i]) - mean_val;
squared_deviations[i] = deviation * deviation;
}
}); /* parallel_for */
}); /* queue.submit */
_ResultType deviation = static_cast<_ResultType>(array1[i]) - mean_val;
squared_deviations[i] = deviation * deviation;
}
};

auto kernel_func = [&](cl::sycl::handler& cgh) {
cgh.parallel_for<class custom_var_c_kernel<_DataType, _ResultType> >(gws, kernel_parallel_for_func);
};

event = DPNP_QUEUE.submit(kernel_func);

event.wait();

Expand Down