llama.cpp/ggml-mpi.c

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#include "ggml-mpi.h"
#include "ggml.h"
#include <mpi.h>
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#include <stdio.h>
#include <stdlib.h>
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#define UNUSED GGML_UNUSED
struct ggml_mpi_tensor_info {
int rank;
};
// ggml_compute_forward_send
static void ggml_mpi_compute_forward_send(
struct ggml_tensor * src,
const struct ggml_tensor * orig) {
UNUSED(orig);
GGML_ASSERT(src->type == GGML_TYPE_F32);
int my_rank;
MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);
int dst_rank = ((struct ggml_mpi_tensor_info *)src->extra)->rank;
// fprintf(stderr, "(%d) Sending to (%d)\n", my_rank, (int)dst->extra);
int retval = MPI_Send(src->data, ggml_nelements(src), MPI_FLOAT, dst_rank, 0, MPI_COMM_WORLD);
// fprintf(stderr, "(%d) Sent to (%d)\n", my_rank, (int)dst->extra);
GGML_ASSERT(retval == MPI_SUCCESS);
}
// ggml_compute_forward_recv
static void ggml_mpi_compute_forward_recv(
struct ggml_tensor * dst,
const struct ggml_tensor * orig,
const struct ggml_tensor * parent) {
UNUSED(parent);
UNUSED(orig);
GGML_ASSERT(dst->type == GGML_TYPE_F32);
MPI_Status status;
int my_rank;
MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);
int src_rank = ((struct ggml_mpi_tensor_info *)dst->extra)->rank;
// fprintf(stderr, "(%d) Receiving from (%d)\n", my_rank, src_extra);
int retval = MPI_Recv(dst->data, ggml_nelements(dst), MPI_FLOAT, src_rank, MPI_ANY_TAG, MPI_COMM_WORLD, &status);
// fprintf(stderr, "(%d) Received from (%d)\n", my_rank, src_extra);
GGML_ASSERT(retval == MPI_SUCCESS);
}
struct ggml_tensor * ggml_mpi_send_tensor(
struct ggml_context * ctx,
struct ggml_tensor * src,
int dst_rank) {
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struct ggml_tensor * result = ggml_map_custom1_inplace_f32(ctx, src, ggml_mpi_compute_forward_send);
// TODO how/when to free this struct?
struct ggml_mpi_tensor_info *info = calloc(1, sizeof(struct ggml_mpi_tensor_info));
info->rank = dst_rank;
result->extra = info;
return result;
}
struct ggml_tensor * ggml_mpi_recv_tensor(
struct ggml_context * ctx,
struct ggml_tensor * parent,
struct ggml_tensor * dst,
int src_rank) {
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struct ggml_tensor * result = ggml_map_custom2_inplace_f32(ctx, dst, parent, ggml_mpi_compute_forward_recv);
// TODO how/when to free this struct?
struct ggml_mpi_tensor_info *info = calloc(1, sizeof(struct ggml_mpi_tensor_info));
info->rank = src_rank;
result->extra = info;
return result;
}
struct ggml_mpi_context {
int mpi_rank;
int mpi_size;
};
void ggml_mpi_backend_init(void) {
MPI_Init(NULL, NULL);
}
void ggml_mpi_backend_free(void) {
MPI_Finalize();
}
struct ggml_mpi_context * ggml_mpi_init(void) {
struct ggml_mpi_context * ctx = calloc(1, sizeof(struct ggml_mpi_context));
MPI_Comm_rank(MPI_COMM_WORLD, &ctx->mpi_rank);
MPI_Comm_size(MPI_COMM_WORLD, &ctx->mpi_size);
return ctx;
}
void ggml_mpi_free(struct ggml_mpi_context * ctx) {
free(ctx);
}
int ggml_mpi_rank(struct ggml_mpi_context * ctx) {
return ctx->mpi_rank;
}
struct ggml_tensor * ggml_mpi_eval_init(
struct ggml_mpi_context * ctx_mpi,
struct ggml_context * ctx,
int n_embd,
int * n_tokens,
int * n_past,
int * n_threads) {
struct ggml_tensor * res = NULL;
// synchronize the worker node parameters with the root node
MPI_Barrier(MPI_COMM_WORLD);
MPI_Bcast(n_tokens, 1, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Bcast(n_past, 1, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Bcast(n_threads, 1, MPI_INT, 0, MPI_COMM_WORLD);
if (ctx_mpi->mpi_rank > 0) {
res = ggml_mpi_recv_tensor(ctx, NULL,
ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, *n_tokens), ctx_mpi->mpi_rank - 1);
ggml_set_name(res, "mpi_recv");
}
return res;
}