// do all the work on 'np' partitions, 'nx' data points each, for 'nt'
// time steps
space do_work(std::size_t np, std::size_t nx, std::size_t nt)
{
// U[t][i] is the state of position i at time t.
std::vector<space> U(2);
for (space& s: U)
s.resize(np);
// Initial conditions: f(0, i) = i
# pragma omp parallel
{
// Visual Studio requires OMP loop variables to be signed :/
# pragma omp for schedule(static)
for (boost::int64_t i = 0; i < (boost::int64_t)np; ++i)
U[0][i] = partition_data(nx, double(i));
// Actual time step loop
for (std::size_t t = 0; t != nt; ++t)
{
space const& current = U[t % 2];
space& next = U[(t + 1) % 2];
// Visual Studio requires OMP loop variables to be signed :/
# pragma omp for schedule(static)
for (boost::int64_t i = 0; i < (boost::int64_t)np; ++i)
next[i] = heat_part(current[idx(i-1, np)], current[i], current[idx(i+1, np)]);
}
}
// Return the solution at time-step 'nt'.
return U[nt % 2];
}
int
main (int argc, const char* argv[])
{
err_t err;
printf ("Loading images and labels...\n");
data_t data;
err = read_all_data (&data, images_file, labels_file);
EXIT_MAIN_ON_ERR(err);
printf ("Setting up network...\n");
network_t network;
uint32_t layers = sizeof(nodes) / sizeof(nodes[0]);
printf ("Node structure: ");
for (uint32_t i = 0; i < layers - 1; ++i) {
printf ("%i x ", nodes[i]);
}
printf ("%i.\n", nodes[layers - 1]);
network.nodes.size = layers;
network.nodes.data = nodes;
network.epochs = EPOCHS;
network.mini_batch_size = MINI_BATCH_SIZE;
network.eta = ETA;
err = network_allocate (&network);
EXIT_MAIN_ON_ERR(err);
printf ("Initialising network...\n");
network_random_init (&network, RANDOM_VARIANCE);
// Split off a chunk of data for testing
data_t test_data;
partition_data(&data, &test_data, VALIDATION_DATA_CHUNK_SIZE);
printf ("Stochastic gradient descent...\n");
network_sgd (&network, &data, &test_data);
network_free (&network);
images_free (&data.images);
labels_free (&data.labels);
return EXIT_SUCCESS;
}
// do all the work on 'np' partitions, 'nx' data points each, for 'nt'
// time steps
space do_work(std::size_t np, std::size_t nx, std::size_t nt)
{
// U[t][i] is the state of position i at time t.
std::vector<space> U(2);
for (space& s: U)
s.resize(np);
// Initial conditions: f(0, i) = i
for (std::size_t i = 0; i != np; ++i)
U[0][i] = partition_data(nx, double(i));
// Actual time step loop
for (std::size_t t = 0; t != nt; ++t)
{
space const& current = U[t % 2];
space& next = U[(t + 1) % 2];
for (std::size_t i = 0; i != np; ++i)
next[i] = heat_part(current[idx(i, -1, np)], current[i], current[idx(i, +1, np)]);
}
// Return the solution at time-step 'nt'.
return U[nt % 2];
}
