Files
fedavg_mpi/main.c

156 lines
4.6 KiB
C

#include "library.h"
#include <stdio.h>
#include <stdlib.h>
#include <mpi.h>
#define P_READER 0
#define P_SLAVE 1
#define P_MASTER 2
#define COMM 500
#define ITER 32
#define BS 32
typedef enum{
DATA,
SLAVE,
MASTER
} Role;
void data_reader() {
// Reads some data and converts it to a float array
printf("Start reader\n");
size_t batch_numel = (784 + 10) * BS;
float* batch = malloc(batch_numel * sizeof(float));
while (1) {
mnist_batch(batch, BS);
MPI_Send(batch, batch_numel, MPI_FLOAT, P_SLAVE, 0, MPI_COMM_WORLD);
}
free(batch);
}
void send_network(const Network* c_net, int dest, int tag) {
// Send a network to the expecting destination
// It's best to receive with `recv_network`
size_t n_layers = c_net->n_layers;
MPI_Send(&n_layers, 1, MPI_LONG, dest, tag, MPI_COMM_WORLD);
for (size_t i = 0; i < n_layers; i++) {
long d0 = c_net->layers[i].shape[0];
long d1 = c_net->layers[i].shape[1];
MPI_Send(c_net->layers[i].shape, 2, MPI_LONG, dest, tag,
MPI_COMM_WORLD);
MPI_Send(c_net->layers[i].W, d0 * d1, MPI_FLOAT, dest, tag,
MPI_COMM_WORLD);
MPI_Send(c_net->layers[i].b, d1, MPI_FLOAT, dest, tag,
MPI_COMM_WORLD);
}
}
void recv_network(Network* c_net, int src, int tag) {
// Creates a new network at c_net (all pointers will be lost so beware)
MPI_Recv(&c_net->n_layers, 1, MPI_LONG, src, tag, MPI_COMM_WORLD,
MPI_STATUS_IGNORE);
c_net->layers = malloc(sizeof(Dense) * c_net->n_layers);
for (size_t i = 0; i < c_net->n_layers; i++) {
MPI_Recv(&c_net->layers[i].shape, 2, MPI_LONG, src, tag,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
long d0 = c_net->layers[i].shape[0];
long d1 = c_net->layers[i].shape[1];
c_net->layers[i].ownmem = 1;
c_net->layers[i].W = malloc(sizeof(float) * d0 * d1);
c_net->layers[i].b = malloc(sizeof(float) * d1);
MPI_Recv(c_net->layers[i].W, d0 * d1, MPI_FLOAT, src, tag,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
MPI_Recv(c_net->layers[i].b, d1, MPI_FLOAT, src, tag,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
}
}
void free_network_contents(Network* c_net) {
// Cleans up the net
for (size_t i = 0; i < c_net->n_layers; i++) {
if (c_net->layers[i].ownmem) {
free(c_net->layers[i].b);
free(c_net->layers[i].W);
}
}
free(c_net->layers);
c_net->layers = NULL; // So that you don't get any ideas
}
// Receives weight updates and trains, sends learned weights back to master
void slave_node() {
printf("Start slave\n");
Network net;
create_c_network(&net);
size_t batch_numel = (784 + 10) * BS;
float* batch = malloc(batch_numel * sizeof(float));
for (int i = 0; i < COMM; i++) {
char go;
MPI_Recv(&go, 1, MPI_CHAR, P_MASTER, MPI_ANY_TAG, MPI_COMM_WORLD,
MPI_STATUS_IGNORE);
for (int k = 0; k < ITER; k++) {
MPI_Recv(batch, batch_numel, MPI_FLOAT, P_READER, MPI_ANY_TAG,
MPI_COMM_WORLD, MPI_STATUS_IGNORE);
step_net(&net, batch, BS);
}
printf("Net: %f\n", eval_net(&net));
send_network(&net, P_MASTER, 0);
}
free(batch);
free_network_contents(&net);
}
// Stores most up-to-date model, sends it to slaves for training
void master_node() {
printf("Start master\n");
Network frank;
create_c_network(&frank);
for (int i = 0; i < COMM; i++) {
char go;
MPI_Send(&go, 1, MPI_CHAR, P_SLAVE, 0, MPI_COMM_WORLD);
Network net;
recv_network(&net, P_SLAVE, MPI_ANY_TAG);
frankenstein(&frank, &net, 1);
free_network_contents(&net);
printf("Frank: %f\n", eval_net(&frank));
}
free_network_contents(&frank);
}
Role map_node() {
int node;
MPI_Comm_rank(MPI_COMM_WORLD, &node);
if (node == P_READER) return DATA;
if (node == P_MASTER) return MASTER;
if (node == P_SLAVE) return SLAVE;
exit(1); // this is bad
}
int main (int argc, const char **argv) {
MPI_Init(NULL, NULL);
// Cython Boilerplate
PyImport_AppendInittab("library", PyInit_library);
Py_Initialize();
PyRun_SimpleString("import sys\nsys.path.insert(0,'')");
PyObject* library_module = PyImport_ImportModule("library");
// Actual Code
switch (map_node()) {
case DATA: data_reader(); break;
case SLAVE: slave_node(); break;
case MASTER: master_node(); break;
}
// Finalizing Boilerplate
Py_DECREF(library_module);
Py_Finalize();
MPI_Finalize();
}