diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..df453b4 --- /dev/null +++ b/Makefile @@ -0,0 +1,18 @@ +# Copyright 2024 Parallel Software and Systems Group, University of Maryland. +# See the top-level LICENSE file for details. +# +# SPDX-License-Identifier: MIT + +CC = cc +INC = -I/global/common/software/nersc9/nccl/2.19.4/include +CFLAGS = -std=c++11 -O2 -target-accel=nvidia80 --cuda-gpu-arch=sm_80 -DUSE_CUDA -DUSE_NCCL +LDFLAGS = -L/global/common/software/nersc9/nccl/2.19.4/lib -lnccl + + +all: allgather.x + +allgather.x: allgather.cu + ${CC} ${CFLAGS} ${INC} ${LDFLAGS} -o allgather.x allgather.cu + +clean: + rm -f allgather.x diff --git a/README b/README new file mode 100644 index 0000000..eba2046 --- /dev/null +++ b/README @@ -0,0 +1,9 @@ +Before compiling do these: + +module load PrgEnv-cray cudatoolkit craype-accel-nvidia80 +export CRAY_ACCEL_TARGET=nvidia80 + +When running do these: + +module load cudatoolkit +export MPICH_GPU_SUPPORT_ENABLED=1 diff --git a/allgather.cu b/allgather.cu new file mode 100644 index 0000000..1d2346a --- /dev/null +++ b/allgather.cu @@ -0,0 +1,204 @@ +/* \file allgather.c + * Copyright 2024 Parallel Software and Systems Group, University of Maryland. + * See the top-level LICENSE file for details. + * + * SPDX-License-Identifier: MIT + */ + +#include +#include +#include + +#ifdef USE_CUDA + #include + #include +#endif + +#ifdef USE_NCCL + #include "nccl.h" +#elif defined(USE_RCCL) + #include "rccl.h" +#endif + +#define NUM_WARMUP_ITERATIONS 5 + +#define MPI_CHECK(cmd) do { \ + int e = cmd; \ + if( e != MPI_SUCCESS ) { \ + printf("Failed: MPI error %s:%d '%d'\n", \ + __FILE__,__LINE__, e); \ + exit(EXIT_FAILURE); \ + } \ +} while(0) + +#define CUDA_CHECK(cmd) do { \ + cudaError_t e = cmd; \ + if(e != cudaSuccess) { \ + printf("CUDA error %s:%d: %s\n", \ + __FILE__, __LINE__, cudaGetErrorString(e)); \ + exit(EXIT_FAILURE); \ + } \ +} while(0) + +#define NCCL_CHECK(cmd) do { \ + ncclResult_t e = cmd; \ + if (e != ncclSuccess) { \ + printf("NCCL error %s:%d %s\n", \ + __FILE__, __LINE__, ncclGetErrorString(e)); \ + exit(EXIT_FAILURE); \ + } \ +} while(0) + +void initializeData(nv_bfloat16 *data, int size) { + for (int i = 0; i < (size / sizeof(nv_bfloat16)); ++i) { + data[i] = __float2bfloat16((float)i); + } +} + +int main(int argc, char *argv[]) { + if (argc != 5) { + fprintf(stderr, "Usage: %s \n", argv[0]); + return EXIT_FAILURE; + } + + int num_gpus = atoi(argv[1]); + int min_msg_size = atoi(argv[2]); + int max_msg_size = atoi(argv[3]); + int iterations = atoi(argv[4]); + + if (num_gpus < 2 || min_msg_size <= 0 || max_msg_size <= 0 || min_msg_size > max_msg_size || iterations <= 0) { + fprintf(stderr, "Invalid input parameters.\n"); + return EXIT_FAILURE; + } + + int my_rank, num_pes; + int num_gpus_per_node; + int msg_count; + + MPI_Init(&argc, &argv); + MPI_Comm_rank(MPI_COMM_WORLD, &my_rank); + MPI_Comm_size(MPI_COMM_WORLD, &num_pes); + + if (num_pes != num_gpus) { + fprintf(stderr, "Number of processes must match number of GPUs.\n"); + MPI_Finalize(); + return EXIT_FAILURE; + } + + // Initialize GPU context + cudaGetDeviceCount(&num_gpus_per_node); + cudaSetDevice((my_rank % num_gpus_per_node)); + + int local_data_size = max_msg_size; // Size of local data to be reduced + int global_data_size = local_data_size * num_gpus; // Size of global data + + nv_bfloat16 *local_data = (nv_bfloat16*)malloc(local_data_size); + nv_bfloat16 *global_data = (nv_bfloat16*)malloc(global_data_size); + + // Initialize local data + initializeData(local_data, local_data_size); + + // Allocate memory on GPU + nv_bfloat16 *d_local_data, *d_global_data; + CUDA_CHECK(cudaMalloc(&d_local_data, local_data_size)); + CUDA_CHECK(cudaMalloc(&d_global_data, global_data_size)); + + // Copy local data to GPU + CUDA_CHECK(cudaMemcpy(d_local_data, local_data, local_data_size, cudaMemcpyHostToDevice)); + + #ifdef USE_MPI + // create 2-byte datatype (send raw, un-interpreted bytes) + MPI_Datatype mpi_type_bfloat16; + MPI_Type_contiguous(2, MPI_BYTE, &mpi_type_bfloat16); + MPI_Type_commit(&mpi_type_bfloat16); + + #elif USE_NCCL + ncclUniqueId nccl_comm_id; + ncclComm_t nccl_comm; + + if (my_rank == 0) { + /* Generates an Id to be used in ncclCommInitRank. */ + ncclGetUniqueId(&nccl_comm_id); + } + + /* distribute nccl_comm_id to all ranks */ + MPI_CHECK(MPI_Bcast((void *)&nccl_comm_id, sizeof(nccl_comm_id), MPI_BYTE, + 0, MPI_COMM_WORLD)); + + /* Create a new NCCL communicator */ + NCCL_CHECK(ncclCommInitRank(&nccl_comm, num_pes, nccl_comm_id, my_rank)); + + #elif defined(USE_RCCL) + // TODO: fix later + rcclComm_t rccl_comm; + rcclCommInitRank(&comm, num_gpus, 0, rccl_root); + #endif + + // Perform MPI_Iallgather, NCCL allgather, or RCCL allgather + double total_time, start_time; + MPI_Request request; + MPI_Status status; + + // Print benchmark results + if (my_rank == 0) { + printf("Number of GPUs: %d\n", num_gpus); + printf("Message size range: %d - %d\n", min_msg_size, max_msg_size); + printf("Number of iterations: %d\n", iterations); + } + fflush(NULL); + + for (int msg_size = min_msg_size; msg_size <= max_msg_size; msg_size *= 2) { + msg_count = msg_size / sizeof(nv_bfloat16); + + // warmup iterations + for (int i = 0; i < NUM_WARMUP_ITERATIONS; ++i) { + #ifdef USE_MPI + MPI_CHECK(MPI_Iallgather(d_local_data, msg_count, mpi_type_bfloat16, + d_global_data, msg_count, mpi_type_bfloat16, MPI_COMM_WORLD, &request)); + + MPI_CHECK(MPI_Wait(&request, &status)); + #elif defined(USE_NCCL) + NCCL_CHECK(ncclAllGather((const void*)d_local_data, (void*)d_global_data, msg_count, ncclBfloat16, nccl_comm, NULL)); + #elif defined(USE_RCCL) + // TODO: fix later + rcclAllReduce((const void*)d_local_data, (void*)d_global_data, global_data_size, rcclInt, rcclSum, comm, NULL); + #endif + } + + MPI_Barrier(MPI_COMM_WORLD); + start_time = MPI_Wtime(); + for (int i = 0; i < iterations; ++i) { + #ifdef USE_MPI + MPI_CHECK(MPI_Iallgather(d_local_data, msg_count, mpi_type_bfloat16, + d_global_data, msg_count, mpi_type_bfloat16, MPI_COMM_WORLD, &request)); + + MPI_CHECK(MPI_Wait(&request, &status)); + #elif defined(USE_NCCL) + NCCL_CHECK(ncclAllGather((const void*)d_local_data, (void*)d_global_data, msg_count, ncclBfloat16, nccl_comm, NULL)); + #elif defined(USE_RCCL) + // TODO: fix later + rcclAllReduce((const void*)d_local_data, (void*)d_global_data, global_data_size, rcclInt, rcclSum, comm, NULL); + #endif + } + MPI_Barrier(MPI_COMM_WORLD); + total_time = MPI_Wtime() - start_time; + if (my_rank == 0) + printf("%d %.6f seconds\n", msg_size, (total_time / iterations)); + } + + // Cleanup + free(local_data); + free(global_data); + CUDA_CHECK(cudaFree(d_local_data)); + CUDA_CHECK(cudaFree(d_global_data)); + + #ifdef USE_NCCL + ncclCommDestroy(nccl_comm); + #elif defined(USE_RCCL) + rcclCommDestroy(rccl_comm); + #endif + + MPI_Finalize(); + return EXIT_SUCCESS; +} +