Use oneapi::dpl::begin and oneapi::dpl::end Functions

oneapi::dpl::begin and oneapi::dpl::end are special helper functions that allow you to pass SYCL buffers to parallel algorithms. These functions accept a SYCL buffer and return an object of an unspecified type that provides the following API:

• It satisfies CopyConstructible and CopyAssignable C++ named requirements and comparable with operator== and operator!=.

• It gives the following valid expressions: a + n, a - n, and a - b, where a and b are objects of the type, and n is an integer value. The effect of those operations is the same as for the type that satisfies the LegacyRandomAccessIterator, a C++ named requirement.

• It provides the get_buffer method, which returns the buffer passed to the begin and end functions.

The begin and end functions can take SYCL 2020 deduction tags and sycl::no_init as arguments to explicitly mention which access mode should be applied to the buffer accessor when submitting a SYCL kernel to a device. For example:

auto first1 = begin(buf, sycl::read_only);
auto first2 = begin(buf, sycl::write_only, sycl::no_init);
auto first3 = begin(buf, sycl::no_init);

The example above allows you to control the access mode for the particular buffer passing to a parallel algorithm.

To use the functions, add #include <oneapi/dpl/iterator> to your code. For example:

#include <oneapi/dpl/execution>
#include <oneapi/dpl/algorithm>
#include <oneapi/dpl/iterator>
#include <sycl/sycl.hpp>
int main(){
  sycl::buffer<int> buf { 1000 };
  auto buf_begin = oneapi::dpl::begin(buf);
  auto buf_end   = oneapi::dpl::end(buf);
  std::fill(oneapi::dpl::execution::dpcpp_default, buf_begin, buf_end, 42);
  return 0;
}

Use Unified Shared Memory

The following examples demonstrate two ways to use the parallel algorithms with USM:

• USM pointers

• USM allocators

If you have a USM-allocated buffer, pass the pointers to the start and past the end of the buffer to a parallel algorithm. Make sure that the execution policy and the buffer were created for the same queue. For example:

#include <oneapi/dpl/execution>
#include <oneapi/dpl/algorithm>
#include <sycl/sycl.hpp>
int main(){
  sycl::queue q;
  const int n = 1000;
  int* d_head = sycl::malloc_shared<int>(n, q);

  std::fill(oneapi::dpl::execution::make_device_policy(q), d_head, d_head + n, 42);

  sycl::free(d_head, q);
  return 0;
}

Alternatively, use std::vector with a USM allocator. For example:

#include <oneapi/dpl/execution>
#include <oneapi/dpl/algorithm>
#include <sycl/sycl.hpp>
int main(){
  const int n = 1000;
  auto policy = oneapi::dpl::execution::dpcpp_default;
  sycl::usm_allocator<int, sycl::usm::alloc::shared> alloc(policy.queue());
  std::vector<int, decltype(alloc)> vec(n, alloc);

  std::fill(policy, vec.begin(), vec.end(), 42);

  return 0;
}

When using device USM, such as allocated by malloc_device, manually copy data to this memory before calling oneDPL algorithms, and copy it back once the algorithms have finished execution.

Use Host-Side std::vector

Intel® oneAPI DPC++ Library parallel algorithms can be called with ordinary (host-side) iterators, as seen in the example below. In this case, a temporary SYCL buffer is created, and the data is copied to this buffer. After processing on a device is complete, the modified data is copied from the temporary buffer back to the host container. For example:

#include <oneapi/dpl/execution>
#include <oneapi/dpl/algorithm>
#include <vector>
int main(){
  std::vector<int> vec( 1000 );
  std::fill(oneapi::dpl::execution::dpcpp_default, vec.begin(), vec.end(), 42);
  // each element of vec equals to 42
  return 0;
}

Working with SYCL buffers is recommended to reduce data copying between the host and device.