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/*
* Test GPU aware MPI on different platforms using a simple
* distributed 1d stencil as an example. Gtensor is used so
* a single source can be used for all platforms.
*/
#include <cmath>
#include <mpi.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include "gtensor/gtensor.h"
#include "gtensor/reductions.h"
using namespace gt::placeholders;
// little hack to make code parameterizable on managed vs device memory
namespace gt {
namespace ext {
namespace detail {
template <typename T, gt::size_type N, typename S = gt::space::device>
struct gthelper {
using gtensor = gt::gtensor<T, N, S>;
};
#ifdef GTENSOR_HAVE_DEVICE
template <typename T, gt::size_type N>
struct gthelper<T, N, gt::space::managed> {
using gtensor = gt::gtensor_container<gt::space::managed_vector<T>, N>;
};
#endif
} // namespace detail
template <typename T, gt::size_type N, typename S = gt::space::device>
using gtensor2 = typename detail::gthelper<T, N, S>::gtensor;
} // namespace ext
} // namespace gt
static const gt::gtensor<double, 1> stencil5 = {1.0 / 12.0, -2.0 / 3.0, 0.0,
2.0 / 3.0, -1.0 / 12.0};
/*
* Return unevaluated expression that calculates the stencil.
*
* Size of the result will be size of y minus 4 (the number of boundary points).
*/
inline auto stencil1d_5(const gt::gtensor_device<double, 1> &y,
const gt::gtensor<double, 1> &stencil) {
return stencil(0) * y.view(_s(0, -4)) + stencil(1) * y.view(_s(1, -3)) +
stencil(2) * y.view(_s(2, -2)) + stencil(3) * y.view(_s(3, -1)) +
stencil(4) * y.view(_s(4, _));
}
void set_rank_device(int n_ranks, int rank) {
int n_devices, device, ranks_per_device;
n_devices = gt::backend::clib::device_get_count();
if (n_ranks > n_devices) {
if (n_ranks % n_devices != 0) {
printf(
"ERROR: Number of ranks (%d) not a multiple of number of GPUs (%d)\n",
n_ranks, n_devices);
exit(EXIT_FAILURE);
}
ranks_per_device = n_ranks / n_devices;
device = rank / ranks_per_device;
} else {
ranks_per_device = 1;
device = rank;
}
gt::backend::clib::device_set(device);
}
void boundary_exchange(MPI_Comm comm, int world_size, int rank,
gt::gtensor_device<double, 1> &d_y, int n_bnd) {
double *d_y_data = gt::raw_pointer_cast(d_y.data());
double *d_y_data_end = gt::raw_pointer_cast(d_y.data()) + d_y.size();
MPI_Request req_l[2];
MPI_Request req_r[2];
int rank_l = rank - 1;
int rank_r = rank + 1;
if (rank_l >= 0) {
// send/recv left boundary
MPI_Irecv(d_y_data, n_bnd, MPI_DOUBLE, rank_l, 123, comm, &req_l[0]);
MPI_Isend(d_y_data + n_bnd, n_bnd, MPI_DOUBLE, rank_l, 456, comm,
&req_l[1]);
}
if (rank_r < world_size) {
// send/recv right boundary
MPI_Irecv(d_y_data_end - n_bnd, n_bnd, MPI_DOUBLE, rank_r, 456, comm,
&req_r[0]);
MPI_Isend(d_y_data_end - 2 * n_bnd, n_bnd, MPI_DOUBLE, rank_r, 123, comm,
&req_r[1]);
}
int mpi_rval;
if (rank_l >= 0) {
mpi_rval = MPI_Waitall(2, req_l, MPI_STATUSES_IGNORE);
if (mpi_rval != MPI_SUCCESS) {
printf("send_l error: %d\n", mpi_rval);
}
}
if (rank_r < world_size) {
mpi_rval = MPI_Waitall(2, req_r, MPI_STATUSES_IGNORE);
if (mpi_rval != MPI_SUCCESS) {
printf("send_r error: %d\n", mpi_rval);
}
}
}
int main(int argc, char **argv) {
int n_global = 32 * 1024 * 1024;
if (argc > 1) {
n_global = std::atoi(argv[1]) * 1024 * 1024;
}
int n_sten = 5;
int n_bnd = (n_sten - 1) / 2;
int world_size, world_rank, device_id;
uint32_t vendor_id;
MPI_Init(NULL, NULL);
MPI_Comm_size(MPI_COMM_WORLD, &world_size);
MPI_Comm_rank(MPI_COMM_WORLD, &world_rank);
if (n_global % world_size != 0) {
printf("%d nmpi (%d) must be divisor of domain size (%d), exiting\n",
world_rank, world_size, n_global);
exit(1);
}
const int n_local = n_global / world_size;
const int n_local_with_ghost = n_local + 2 * n_bnd;
set_rank_device(world_size, world_rank);
device_id = gt::backend::clib::device_get();
vendor_id = gt::backend::clib::device_get_vendor_id(device_id);
if (world_rank == 0) {
printf("n procs = %d\n", world_size);
printf("n_global = %d\n", n_global);
printf("n_local = %d\n", n_local);
}
auto h_y = gt::empty<double>({n_local_with_ghost});
auto d_y = gt::empty_device<double>({n_local_with_ghost});
auto h_dydx_numeric = gt::empty<double>({n_local});
auto h_dydx_actual = gt::empty<double>({n_local});
auto d_dydx_numeric = gt::empty_device<double>({n_local});
double lx = 8;
double dx = lx / n_global;
double lx_local = lx / world_size;
double scale = n_global / lx;
auto fn_x_cubed = [](double x) { return x * x * x; };
auto fn_x_cubed_deriv = [](double x) { return 3 * x * x; };
struct timespec start, end;
double seconds = 0.0;
double x_start = world_rank * lx_local;
for (int i = 0; i < n_local; i++) {
double xtmp = x_start + i * dx;
h_y(i + n_bnd) = fn_x_cubed(xtmp);
h_dydx_actual(i) = fn_x_cubed_deriv(xtmp);
}
// fill boundary points on ends
if (world_rank == 0) {
for (int i = 0; i < n_bnd; i++) {
double xtmp = (i - n_bnd) * dx;
h_y(i) = fn_x_cubed(xtmp);
}
}
if (world_rank == world_size - 1) {
for (int i = 0; i < n_bnd; i++) {
double xtmp = lx + i * dx;
h_y(n_bnd + n_local + i) = fn_x_cubed(xtmp);
}
}
gt::copy(h_y, d_y);
clock_gettime(CLOCK_MONOTONIC, &start);
boundary_exchange(MPI_COMM_WORLD, world_size, world_rank, d_y, n_bnd);
clock_gettime(CLOCK_MONOTONIC, &end);
seconds = ((end.tv_sec - start.tv_sec) + (end.tv_nsec - start.tv_nsec) * 1.0e-9);
printf("%d/%d exchange time %0.8f\n", world_rank, world_size, seconds);
d_dydx_numeric = stencil1d_5(d_y, stencil5) * scale;
gt::copy(d_dydx_numeric, h_dydx_numeric);
/*
for (int i = 0; i < 5; i++) {
printf("%d la %f\n%d ln %f\n", world_rank, h_dydx_actual(i),
world_rank, h_dydx_numeric(i));
}
for (int i = 0; i < 5; i++) {
int idx = n_local - 1 - i;
printf("%d ra %f\n%d rn %f\n", world_rank, h_dydx_actual(idx),
world_rank, h_dydx_numeric(idx));
}
*/
double err_norm = std::sqrt(gt::sum_squares(h_dydx_numeric - h_dydx_actual));
printf("%d/%d [%d:0x%08x] err_norm = %.8f\n", world_rank, world_size,
device_id, vendor_id, err_norm);
MPI_Finalize();
return EXIT_SUCCESS;
}