Visible to Intel only — GUID: GUID-A4D68FB6-AA64-4BC7-B688-6142BBC1EF5B
Sample Application
The sample code below shows how to use oneCCL API to perform allreduce communication for SYCL USM memory.
#include <iostream>
#include <mpi.h>
#include "oneapi/ccl.hpp"
void mpi_finalize() {
int is_finalized = 0;
MPI_Finalized(&is_finalized);
if (!is_finalized) {
MPI_Finalize();
}
}
int main(int argc, char* argv[]) {
constexpr size_t count = 10 * 1024 * 1024;
int size = 0;
int rank = 0;
ccl::init();
MPI_Init(nullptr, nullptr);
MPI_Comm_size(MPI_COMM_WORLD, &size);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
atexit(mpi_finalize);
sycl::default_selector device_selector;
sycl::queue q(device_selector);
std::cout << "Running on " << q.get_device().get_info<sycl::info::device::name>() << "\n";
/* create kvs */
ccl::shared_ptr_class<ccl::kvs> kvs;
ccl::kvs::address_type main_addr;
if (rank == 0) {
kvs = ccl::create_main_kvs();
main_addr = kvs->get_address();
MPI_Bcast((void*)main_addr.data(), main_addr.size(), MPI_BYTE, 0, MPI_COMM_WORLD);
}
else {
MPI_Bcast((void*)main_addr.data(), main_addr.size(), MPI_BYTE, 0, MPI_COMM_WORLD);
kvs = ccl::create_kvs(main_addr);
}
/* create communicator */
auto dev = ccl::create_device(q.get_device());
auto ctx = ccl::create_context(q.get_context());
auto comm = ccl::create_communicator(size, rank, dev, ctx, kvs);
/* create stream */
auto stream = ccl::create_stream(q);
/* create buffers */
auto send_buf = sycl::malloc_device<int>(count, q);
auto recv_buf = sycl::malloc_device<int>(count, q);
/* open buffers and modify them on the device side */
auto e = q.submit([&](auto& h) {
h.parallel_for(count, [=](auto id) {
send_buf[id] = rank + id + 1;
recv_buf[id] = -1;
});
});
int check_sum = 0;
for (int i = 1; i <= size; ++i) {
check_sum += i;
}
/* do not wait completion of kernel and provide it as dependency for operation */
std::vector<ccl::event> deps;
deps.push_back(ccl::create_event(e));
/* invoke allreduce */
auto attr = ccl::create_operation_attr<ccl::allreduce_attr>();
ccl::allreduce(send_buf, recv_buf, count, ccl::reduction::sum, comm, stream, attr, deps).wait();
/* open recv_buf and check its correctness on the device side */
sycl::buffer<int> check_buf(count);
q.submit([&](auto& h) {
sycl::accessor check_buf_acc(check_buf, h, sycl::write_only);
h.parallel_for(count, [=](auto id) {
if (recv_buf[id] != static_cast<int>(check_sum + size * id)) {
check_buf_acc[id] = -1;
}
});
});
q.wait_and_throw();
/* print out the result of the test on the host side */
{
sycl::host_accessor check_buf_acc(check_buf, sycl::read_only);
size_t i;
for (i = 0; i < count; i++) {
if (check_buf_acc[i] == -1) {
std::cout << "FAILED\n";
break;
}
}
if (i == count) {
std::cout << "PASSED\n";
}
}
sycl::free(send_buf, q);
sycl::free(recv_buf, q);
}
Build details
Run the sample
Intel® MPI Library is required for running the sample. Make sure that MPI environment is set up.
To run the sample, use the following command:
mpiexec <parameters> ./sample
where <parameters> represents optional mpiexec parameters such as node count, processes per node, hosts, and so on.