/* * Test GPU aware MPI on different platforms using a distributed * 1d stencil on a 2d array. The exchange in second (non-contiguous) * direction forces use of staging buffers, which replicates what * is needed for all but the innermost dimension exchanges in the * GENE fusion code. * * Takes optional command line arg for size of each dimension of the domain * n_global, in 1024 increments. Default is 8 * 1024 (so 256K plus ghost points * in size for doulbles per array), which should fit on any system but may not * be enough to tax larger HPC GPUs and MPI impelmentations. * * There will be four exchange buffers of size 2 * n_global, i.e. 128K each * by default. * * Modified version that uses minimal owning (array2d) and non-owning (span2d) * classes to make indexing handling less error prone, without using all of * gtensor. Note that the owning class is not trivially copyable and not device * copyable, because it must have a non-trivial destructor. * * TODO: Since no temporaries are used, perhaps a helper that allocates and * returns a span is a simpler option to create this minimal example? */ #include #include #include #include #include #include #include #include #include "sycl/sycl.hpp" // #define DEBUG #ifdef DEBUG #define dprintf(...) fprintf(stderr, __VA_ARGS__) #else #define dprintf(...) \ do { \ } while (0) #endif constexpr std::size_t idx2(int n, int row, int col) { return row + col * n; } template class span2d { public: using value_type = T; using pointer = value_type*; using const_pointer = const value_type*; using reference = value_type&; using const_reference = const value_type&; using size_type = std::size_t; span2d(T* data, const int nrows, const int ncols) : data_(data), nrows_(nrows), ncols_(ncols) {} // use default copy and move ctor. Ideall move ctor would better invalidate // the moved from object, but this is supposed to be a small example... span2d(const span2d& other) = default; span2d& operator=(const span2d& other) = default; span2d(span2d&& other) = default; span2d& operator=(span2d&& other) = default; // Note: shallow const reference operator()(int row, int col) const { assert(row < nrows_); assert(col < ncols_); return data_[idx2(nrows_, row, col)]; } // Note: shallow const reference operator[](size_type i) const { assert(i < (nrows_ * ncols_)); return data_[i]; } int nrows() const { return nrows_; } int ncols() const { return ncols_; } size_type size() const { return nrows_ * ncols_; } span2d to_span() { return *this; } // Note: shallow const pointer data() const { return data_; } private: const sycl::usm::alloc alloc_ = Alloc; T* data_; const int nrows_; const int ncols_; }; template auto empty_host(sycl::queue& q, int nrows, int ncols) { T* data = sycl::malloc(nrows * ncols, q, sycl::usm::alloc::host); return span2d(data, nrows, ncols); } template auto empty_device(sycl::queue& q, int nrows, int ncols) { T* data = sycl::malloc(nrows * ncols, q, sycl::usm::alloc::device); return span2d(data, nrows, ncols); } template class array2d : public span2d { public: using base_type = span2d; using value_type = T; using pointer = value_type*; using const_pointer = const value_type*; using reference = value_type&; using const_reference = const value_type&; using size_type = std::size_t; array2d(sycl::queue& q, const int nrows, const int ncols) : base_type(sycl::malloc(nrows * ncols, q, Alloc), nrows, ncols), q_(q) {} // Results in a double free, why? // ~array2d() { sycl::free(this->data(), q_); } // skip these to keep the example simple, pass by reference everywhere array2d(const array2d& other) = delete; array2d& operator=(const array2d& other) = delete; array2d(array2d&& other) = delete; array2d& operator=(array2d&& other) = delete; base_type to_span() { return base_type(this->data(), this->nrows(), this->ncols()); } private: sycl::queue& q_; }; template auto copy(sycl::queue& q, SrcArray& src, DestArray& dest) { static_assert(std::is_same_v, "value types must match"); assert(src.size() == dest.size()); return q.copy(src.data(), dest.data(), dest.size()); } template auto copy_dest_slice(sycl::queue& q, Array& src, Array& dest, int dim, int start, int end) { dprintf("copy dest_slice %d %d %d\n", dim, start, end); auto s_src = src.to_span(); auto s_dest = dest.to_span(); assert(dim == 0 || dim == 1); if (dim == 0) { assert(src.ncols() == dest.ncols()); if (start < 0) { start += dest.nrows(); } if (end < 0) { end += dest.nrows(); } else if (end == 0 && start > end) { end = dest.nrows(); } assert(start < end); auto range = sycl::range<2>(dest.ncols(), end - start); dprintf("d_z < buf range %d - %d (%d, %d)\n", start, end, dest.ncols(), end - start); auto e = q.submit([&](sycl::handler& cgh) { cgh.parallel_for(range, [=](sycl::item<2> item) { int row = item.get_id(1); int col = item.get_id(0); s_dest(start + row, col) = s_src(row, col); }); }); return e; } else { assert(src.nrows() == dest.nrows()); if (start < 0) { start += dest.ncols(); } if (end < 0) { end += dest.ncols(); } else if (end == 0 && start > end) { end = dest.ncols(); } auto range = sycl::range<2>(end - start, dest.nrows()); auto e = q.submit([&](sycl::handler& cgh) { cgh.parallel_for(range, [=](sycl::item<2> item) { int row = item.get_id(1); int col = item.get_id(0); s_dest(row, start + col) = s_src(row, col); }); }); return e; } } template auto copy_src_slice(sycl::queue& q, Array& src, Array& dest, int dim, int start, int end) { dprintf("copy src_slice %d %d %d (%d, %d) -> (%d, %d)\n", dim, start, end, src.nrows(), src.ncols(), dest.nrows(), dest.ncols()); assert(dim == 0 || dim == 1); auto s_src = src.to_span(); auto s_dest = dest.to_span(); if (dim == 0) { assert(src.ncols() == dest.ncols()); if (start < 0) { start += src.nrows(); } if (end < 0) { end += src.nrows(); } else if (end == 0 && start > end) { end = src.nrows(); } auto range = sycl::range<2>(dest.ncols(), end - start); dprintf("buf < d_z range %d - %d (%d, %d)\n", start, end, dest.ncols(), end - start); auto e = q.submit([&](sycl::handler& cgh) { cgh.parallel_for(range, [=](sycl::item<2> item) { int row = item.get_id(1); int col = item.get_id(0); s_dest(row, col) = s_src(start + row, col); }); }); return e; } else { assert(src.nrows() == dest.nrows()); if (start < 0) { start += src.ncols(); } if (end < 0) { end += src.ncols(); } else if (end == 0 && start > end) { end = src.ncols(); } auto range = sycl::range<2>(end - start, dest.nrows()); auto e = q.submit([&](sycl::handler& cgh) { cgh.parallel_for(range, [=](sycl::item<2> item) { int row = item.get_id(1); int col = item.get_id(0); s_dest(row, col) = s_src(row, start + col); }); }); return e; } } inline void check(const char* fname, int line, int mpi_rval) { if (mpi_rval != MPI_SUCCESS) { printf("%s:%d error %d\n", fname, line, mpi_rval); exit(2); } } #define CHECK(x) check(__FILE__, __LINE__, (x)) static constexpr double stencil5[] = {1.0 / 12.0, -2.0 / 3.0, 0.0, 2.0 / 3.0, -1.0 / 12.0}; /* * Calculate 1d stencil of second dimension of 2d array on GPU. Out array must * be contiguous column major nrows x ncols array, while in array must be * (nrows)x(ncols+4) to accomodate 2 ghost points in each direction for the * second dimension. * * Returns sycl event, async with respect to host. */ template auto stencil2d_1d_5(sycl::queue& q, Array& out2d, Array& in2d, double scale) { // Note: swap index order; SYCL is row-major oriented, and this example // is col-major auto range = sycl::range<2>(out2d.ncols(), out2d.nrows()); auto s_in2d = in2d.to_span(); auto s_out2d = out2d.to_span(); auto e = q.submit([&](sycl::handler& cgh) { cgh.parallel_for(range, [=](sycl::item<2> item) { int row = item.get_id(1); int col = item.get_id(0); s_out2d(row, col) = (stencil5[0] * s_in2d(row + 0, col) + stencil5[1] * s_in2d(row + 1, col) + stencil5[2] * s_in2d(row + 2, col) + stencil5[3] * s_in2d(row + 3, col) + stencil5[4] * s_in2d(row + 4, col)) * scale; }); }); return e; } /* * Calculate the norm of the difference of two arrays, as sqrt of sum of * squared distances. */ double diff_norm(sycl::queue& q, std::size_t size, double* d_a, double* d_b) { double result = 0.0; sycl::buffer result_buf{&result, 1}; { sycl::range<1> range(size); auto e = q.submit([&](sycl::handler& cgh) { auto reducer = sycl::reduction(result_buf, cgh, 0.0, std::plus<>{}); cgh.parallel_for(range, reducer, [=](sycl::id<1> idx, auto& r) { double diff = d_a[idx] - d_b[idx]; r.combine(diff * diff); }); }); e.wait(); } return std::sqrt(result_buf.get_host_access()[0]); } sycl::queue get_rank_queue(int n_ranks, int rank) { int n_devices, device_idx, ranks_per_device; sycl::context ctx{}; auto devices = ctx.get_devices(); n_devices = devices.size(); 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_idx = rank / ranks_per_device; } else { ranks_per_device = 1; device_idx = rank; } dprintf("%d: n_devices = %d\n", rank, n_devices); dprintf("%d: device_idx = %d\n", rank, device_idx); return sycl::queue{devices[device_idx], sycl::property::queue::in_order()}; } // exchange in first dimension, staging into contiguous buffers on device template void boundary_exchange_x(MPI_Comm comm, int world_size, int rank, sycl::queue& q, int n_bnd, array2d& d_z, bool stage_host = false) { static array2d sbuf_l{q, n_bnd, d_z.ncols()}; static array2d sbuf_r{q, n_bnd, d_z.ncols()}; static array2d rbuf_l{q, n_bnd, d_z.ncols()}; static array2d rbuf_r{q, n_bnd, d_z.ncols()}; static array2d h_sbuf_l{q, n_bnd, d_z.ncols()}; static array2d h_sbuf_r{q, n_bnd, d_z.ncols()}; static array2d h_rbuf_l{q, n_bnd, d_z.ncols()}; static array2d h_rbuf_r{q, n_bnd, d_z.ncols()}; int buf_size = sbuf_l.size(); MPI_Request req_l[2]; MPI_Request req_r[2]; int rank_l = rank - 1; int rank_r = rank + 1; // start async copy of ghost points into send buffers if (rank_l >= 0) { dprintf("%d: rank_l = %d\n", rank, rank_l); fflush(nullptr); // sbuf_l = d_z.view(_all, _s(n_bnd, 2 * n_bnd)); auto e = copy_src_slice(q, d_z, sbuf_l, 0, n_bnd, 2 * n_bnd); if (stage_host) { e.wait(); copy(q, sbuf_l, h_sbuf_l).wait(); for (int i = 0; i < h_sbuf_l.ncols(); i++) { for (int j = 0; j < h_sbuf_l.nrows(); j++) { dprintf("%d: sbuf_l[%d, %d] = %f\n", rank, j, i, h_sbuf_l(j, i)); fflush(nullptr); } } } } if (rank_r < world_size) { dprintf("%d: rank_r = %d\n", rank, rank_r); fflush(nullptr); // sbuf_r = d_z.view(_all, _s(-2 * n_bnd, -n_bnd)); auto e = copy_src_slice(q, d_z, sbuf_r, 0, -2 * n_bnd, -n_bnd); if (stage_host) { e.wait(); copy(q, sbuf_r, h_sbuf_r).wait(); for (int i = 0; i < h_sbuf_r.ncols(); i++) { for (int j = 0; j < h_sbuf_r.nrows(); j++) { dprintf("%d: sbuf_r[%d, %d] = %f\n", rank, j, i, h_sbuf_r(j, i)); fflush(nullptr); } } } } // initiate async recv if (rank_l >= 0) { double* rbuf_l_data = nullptr; if (stage_host) { rbuf_l_data = h_rbuf_l.data(); } else { rbuf_l_data = rbuf_l.data(); } MPI_Irecv(rbuf_l_data, buf_size, MPI_DOUBLE, rank_l, 123, comm, &req_l[0]); } if (rank_r < world_size) { double* rbuf_r_data = nullptr; if (stage_host) { rbuf_r_data = h_rbuf_r.data(); } else { rbuf_r_data = rbuf_r.data(); } MPI_Irecv(rbuf_r_data, buf_size, MPI_DOUBLE, rank_r, 456, comm, &req_r[0]); } // wait for send buffer fill q.wait(); // initiate async sends if (rank_l >= 0) { double* sbuf_l_data = nullptr; if (stage_host) { sbuf_l_data = h_sbuf_l.data(); } else { sbuf_l_data = sbuf_l.data(); } MPI_Isend(sbuf_l_data, buf_size, MPI_DOUBLE, rank_l, 456, comm, &req_l[1]); } if (rank_r < world_size) { double* sbuf_r_data = nullptr; if (stage_host) { sbuf_r_data = h_sbuf_r.data(); } else { sbuf_r_data = sbuf_r.data(); } MPI_Isend(sbuf_r_data, buf_size, MPI_DOUBLE, rank_r, 123, comm, &req_r[1]); } // wait for send/recv to complete, then copy data back into main data array int mpi_rval; if (rank_l >= 0) { mpi_rval = MPI_Waitall(2, req_l, MPI_STATUSES_IGNORE); if (mpi_rval != MPI_SUCCESS) { printf("%d: send_l error: %d\n", rank, mpi_rval); } if (stage_host) { #ifdef DEBUG for (int i = 0; i < h_rbuf_l.ncols(); i++) { for (int j = 0; j < h_rbuf_l.nrows(); j++) { dprintf("%d: rbuf_l[%d, %d] = %f\n", rank, j, i, h_rbuf_l(j, i)); fflush(nullptr); } } #endif copy(q, h_rbuf_l, rbuf_l).wait(); } // d_z.view(_all, _s(0, n_bnd)) = rbuf_l; copy_dest_slice(q, rbuf_l, d_z, 0, 0, n_bnd); } if (rank_r < world_size) { mpi_rval = MPI_Waitall(2, req_r, MPI_STATUSES_IGNORE); if (mpi_rval != MPI_SUCCESS) { printf("%d: send_r error: %d\n", rank, mpi_rval); } if (stage_host) { #ifdef DEBUG for (int i = 0; i < h_rbuf_r.ncols(); i++) { for (int j = 0; j < h_rbuf_r.nrows(); j++) { dprintf("%d: rbuf_r[%d, %d] = %f\n", rank, j, i, h_rbuf_r(j, i)); fflush(nullptr); } } #endif copy(q, h_rbuf_r, rbuf_r).wait(); } // d_z.view(_all, _s(-n_bnd, _)) = rbuf_r; copy_dest_slice(q, rbuf_r, d_z, 0, -n_bnd, 0); } q.wait(); } int main(int argc, char** argv) { using T = double; static_assert( std::is_trivially_copyable_v>, "span2d device not trivial"); static_assert(std::is_trivially_copyable_v>, "span2d host not trivial"); // Note: domain will be n_global x n_global plus ghost points in one dimension int n_global = 8 * 1024; bool stage_host = false; int n_iter = 100; int n_warmup = 5; if (argc > 1) { n_global = std::atoi(argv[1]) * 1024; } if (argc > 2) { if (argv[2][0] == '1') { stage_host = true; } } if (argc > 3) { n_iter = std::atoi(argv[3]); } #ifdef DEBUG n_global /= 1024; n_iter = 1; n_warmup = 0; #endif 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; sycl::queue q = get_rank_queue(world_size, world_rank); vendor_id = q.get_device().get_info(); if (world_rank == 0) { printf("n procs = %d\n", world_size); printf("rank = %d\n", world_rank); printf("n_global = %d\n", n_global); printf("n_local = %d\n", n_local); printf("n_iter = %d\n", n_iter); printf("n_warmup = %d\n", n_warmup); printf("stage_host = %d\n", stage_host); } int z_size = n_local_with_ghost * n_global; int dzdx_size = n_local * n_global; array2d h_z{q, n_local_with_ghost, n_global}; array2d d_z{q, n_local_with_ghost, n_global}; array2d h_dzdx_actual{q, n_local, n_global}; array2d h_dzdx_numeric{q, n_local, n_global}; array2d d_dzdx_actual{q, n_local, n_global}; array2d d_dzdx_numeric{q, n_local, n_global}; double lx = 8; double dx = lx / n_global; double lx_local = lx / world_size; double scale = n_global / lx; auto fn = [](double x, double y) { return x * x * x + y * y; }; auto fn_dzdx = [](double x, double y) { return 3 * x * x; }; struct timespec start, end; double iter_time = 0.0; double total_time = 0.0; double x_start = world_rank * lx_local; for (int j = 0; j < h_z.ncols(); j++) { double ytmp = j * dx; for (int i = 0; i < n_local; i++) { double xtmp = x_start + i * dx; h_z(i + n_bnd, j) = fn(xtmp, ytmp); h_dzdx_actual(i, j) = fn_dzdx(xtmp, ytmp); } } // fill boundary points on ends if (world_rank == 0) { for (int j = 0; j < h_z.ncols(); j++) { double ytmp = j * dx; for (int i = 0; i < n_bnd; i++) { double xtmp = (i - n_bnd) * dx; h_z(i, j) = fn(xtmp, ytmp); } } } if (world_rank == world_size - 1) { for (int j = 0; j < h_z.ncols(); j++) { double ytmp = j * dx; for (int i = 0; i < n_bnd; i++) { double xtmp = lx + i * dx; h_z(n_bnd + n_local + i, j) = fn(xtmp, ytmp); } } } #ifdef DEBUG for (int r = 0; r < world_size; r++) { if (r != world_rank) { continue; } for (int i = n_bnd; i < 2 * n_bnd; i++) { dprintf("%d: [%d, :]", world_rank, i); for (int j = 0; j < std::min(20, h_z.ncols()); j++) { dprintf(" %f", h_z(i, j)); } dprintf("\n"); } for (int i = h_z.nrows() - 2 * n_bnd; i < h_z.nrows() - n_bnd; i++) { dprintf("%d: [%d, :]", world_rank, i); for (int j = 0; j < std::min(20, h_z.ncols()); j++) { dprintf(" %f", h_z(i, j)); } dprintf("\n"); } MPI_Barrier(MPI_COMM_WORLD); } #endif copy(q, h_z, d_z); for (int i = 0; i < n_warmup + n_iter; i++) { clock_gettime(CLOCK_MONOTONIC, &start); boundary_exchange_x(MPI_COMM_WORLD, world_size, world_rank, q, n_bnd, d_z, stage_host); clock_gettime(CLOCK_MONOTONIC, &end); iter_time = ((end.tv_sec - start.tv_sec) + (end.tv_nsec - start.tv_nsec) * 1.0e-9); if (i >= n_warmup) { total_time += iter_time; } // do some calculation, to try to more closely simulate what happens in GENE auto e = stencil2d_1d_5(q, d_dzdx_numeric, d_z, scale); e.wait(); } printf("%d: exchange time %0.8f ms\n", world_rank, total_time / n_iter * 1000); copy(q, d_dzdx_numeric, h_dzdx_numeric).wait(); /* for (int i = 0; i < 5; i++) { int idx = idx2(n_global, 8, i); printf("%d la %f\n%d ln %f\n", world_rank, h_dzdx_actual[idx], world_rank, h_dzdx_numeric[idx]); } for (int i = 0; i < 5; i++) { int idx = idx2(n_global, 8, n_local - 1 - i); printf("%d ra %f\n%d rn %f\n", world_rank, h_dzdx_actual[idx], world_rank, h_dzdx_numeric[idx]); } */ double err_norm = diff_norm(q, h_dzdx_numeric.size(), h_dzdx_numeric.data(), h_dzdx_actual.data()); printf("%d: [0x%08x] err_norm = %.8f\n", world_rank, vendor_id, err_norm); MPI_Finalize(); return EXIT_SUCCESS; }