void on_init1_finished()
{
long i;
for(i = 0; i < N/PSIZE * N_LONG_PAGE; i = i + N_LONG_PAGE)
{
if(trigger[i] != 1)
{
abort;
}
}
// mark this watcher committed
trigger[0] = 3;
for(i = 0; i < K; i = i + 1)
{
#ifdef INPUT_PMEM
cx[i] = pmem_in[4*i];
cy[i] = pmem_in[4*i+1];
cz[i] = pmem_in[4*i+2];
cw[i] = pmem_in[4*i+3];
#else
cx[i] = x[i];
cy[i] = y[i];
cz[i] = z[i];
cw[i] = w[i];
#endif
}
// number of iterations
iter = 0;
#ifdef DEBUG
output_char('i');
output_char('t');
output_char('e');
output_char('r');
output_char(':');
output_q(-1);
output_char(':');
output_centroids();
#endif
start_iteration();
commitd;
}
/*
* Send a status update to all connected clients
*/
void broadcast_status() {
struct cl_entry *current;
struct net_status *status;
uint8_t dcount;
uint16_t scount;
uint8_t tcount;
uint8_t permission;
int ret;
/*
* Start iteration over complete client list
* This locks the mutex for the client list
*/
current = start_iteration();
/* Get number of users */
dcount = docent_exists();
tcount = tutor_exists();
scount = get_client_count() - dcount - tcount;
while (current != NULL) {
if (current == get_write_user()) {
permission = 1;
} else {
permission = 0;
}
/* Build the status message */
status = build_status(current->cdata->role, current->cdata->cid,
permission, dcount, tcount, scount);
ret = send(current->cdata->sfd, status, sizeof(struct net_status), 0);
if (ret < 0) {
perror("send");
}
free(status);
/* Select next client in list */
current = iteration_next();
}
log_debug("broadcasting agent: status sent to all connected clients");
/*
* End of iteration
* This unlocks the mutex of the client list
*/
end_iteration();
}
void *monitor_run(void *ptr)
{
struct mt_context *thread_context = (struct mt_context *) ptr;
struct monitor_ctx *monitor_context = (struct monitor_ctx *) thread_context->param;
struct rtgtargets *targets = monitor_context->targets;
struct rtgconf *config = monitor_context->config;
unsigned poll_interval = config->interval;
/* Use the specified next iteration value.
* If it is set to zero, we'll run as soon as possible. */
curms_t next_iteration = monitor_context->next_iteration;
curms_t this_iteration = 0;
struct timespec loopdelay = { 0, 250 * 1000 * 1000 };
nanosleep(&loopdelay, NULL);
while (!thread_stop_requested) {
curms_t now = curms();
/* If there are no threads running and it's time for a new iteration,
* start a new iteration. */
if (active_threads == 0 && now >= next_iteration) {
start_iteration(targets);
this_iteration = now;
next_iteration = next_interval(now, poll_interval);
}
/* Give the threads a chance to start, so we don't
* mistakenly think they're all done already. */
nanosleep(&loopdelay, NULL);
/* If there are no threads running, and we have started a iteration,
* then we are done. End the iteration. */
if (active_threads == 0 && this_iteration) {
end_iteration(next_iteration, this_iteration);
this_iteration = 0;
}
}
/* Save next iteration value, so we can reuse it if necessary. */
monitor_context->next_iteration = next_iteration;
return NULL;
}
/*
* Send a board update message to all connected clients
*
* Excludes the user with write acces if the parameter
* excl_w is set to 1. If the blackbpard should be broadcasted to all
* connected clients, excl_w shoul be 0.
*/
void broadcast_blackboard(char *blackboard, int bsem_id, int excl_w) {
struct cl_entry *current;
struct net_board *board;
int ret;
int length;
/*
* Prepare the blackboard message
*/
lock_sem(bsem_id);
length = strlen(blackboard);
board = build_board(blackboard, length);
unlock_sem(bsem_id);
/*
* Iterate over the complete client list
* This locks the mutex of the client list
*/
current = start_iteration();
while (current != NULL) {
/* Don't broadcast to the user with write access */
if ((current == get_write_user()) && excl_w) {
current = iteration_next();
continue;
}
ret = send(current->cdata->sfd, board, sizeof(struct net_header) + length, 0);
if (ret < 0) {
perror("send");
}
/* Select next client in list */
current = iteration_next();
}
/* Unlock mutex of client list */
end_iteration();
free(board);
log_debug("broadcasting agent: blackboard sent to all connected clients");
}
// Main ------------------------------------------------------------------------------------------
int main(int argc, char **argv) {
const Params p(argc, argv);
CUDASetup setcuda(p.device);
Timer timer;
cudaError_t cudaStatus;
int it_cpu = 0;
int it_gpu = 0;
int err = 0;
#ifdef LOGS
set_iter_interval_print(10);
char test_info[500];
snprintf(test_info, 500, "-i %d -g %d -t %d -f %s -l %d\n",p.n_gpu_threads, p.n_gpu_blocks,p.n_threads, p.file_name,p.switching_limit);
start_log_file("cudaSingleSourceShortestPath", test_info);
//printf("Com LOG\n");
#endif
// Allocate
int n_nodes, n_edges;
// int n_nodes_o;
read_input_size(n_nodes, n_edges, p);
timer.start("Allocation");
Node * h_nodes = (Node *) malloc(sizeof(Node) * n_nodes);
//*************************** Alocando Memoria para o Gold *************************************
Gold * gold = (Gold *) malloc(sizeof(Gold) * n_nodes);
if (p.mode == 1) {
// ********************** Lendo O gold *********************************
read_gold(gold, p);
// **********************************************************************
}
//***********************************************************************************************
Node * d_nodes;
cudaStatus = cudaMalloc((void**) &d_nodes, sizeof(Node) * n_nodes);
Edge * h_edges = (Edge *) malloc(sizeof(Edge) * n_edges);
Edge * d_edges;
cudaStatus = cudaMalloc((void**) &d_edges, sizeof(Edge) * n_edges);
std::atomic_int *h_color = (std::atomic_int *) malloc(
sizeof(std::atomic_int) * n_nodes);
int * d_color;
cudaStatus = cudaMalloc((void**) &d_color, sizeof(int) * n_nodes);
std::atomic_int *h_cost = (std::atomic_int *) malloc(
sizeof(std::atomic_int) * n_nodes);
int * d_cost;
cudaStatus = cudaMalloc((void**) &d_cost, sizeof(int) * n_nodes);
int * h_q1 = (int *) malloc(n_nodes * sizeof(int));
int * d_q1;
cudaStatus = cudaMalloc((void**) &d_q1, sizeof(int) * n_nodes);
int * h_q2 = (int *) malloc(n_nodes * sizeof(int));
int * d_q2;
cudaStatus = cudaMalloc((void**) &d_q2, sizeof(int) * n_nodes);
std::atomic_int h_head[1];
int * d_head;
cudaStatus = cudaMalloc((void**) &d_head, sizeof(int));
std::atomic_int h_tail[1];
int * d_tail;
cudaStatus = cudaMalloc((void**) &d_tail, sizeof(int));
std::atomic_int h_threads_end[1];
int * d_threads_end;
cudaStatus = cudaMalloc((void**) &d_threads_end, sizeof(int));
std::atomic_int h_threads_run[1];
int * d_threads_run;
cudaStatus = cudaMalloc((void**) &d_threads_run, sizeof(int));
int h_num_t[1];
int * d_num_t;
cudaStatus = cudaMalloc((void**) &d_num_t, sizeof(int));
int h_overflow[1];
int * d_overflow;
cudaStatus = cudaMalloc((void**) &d_overflow, sizeof(int));
std::atomic_int h_gray_shade[1];
int * d_gray_shade;
cudaStatus = cudaMalloc((void**) &d_gray_shade, sizeof(int));
std::atomic_int h_iter[1];
int * d_iter;
cudaStatus = cudaMalloc((void**) &d_iter, sizeof(int));
cudaDeviceSynchronize();
CUDA_ERR();
ALLOC_ERR(h_nodes, h_edges, h_color, h_cost, h_q1, h_q2);
timer.stop("Allocation");
// Initialize
timer.start("Initialization");
const int max_gpu_threads = setcuda.max_gpu_threads();
int source;
read_input(source, h_nodes, h_edges, p);
for (int i = 0; i < n_nodes; i++) {
h_cost[i].store(INF);
}
h_cost[source].store(0);
for (int i = 0; i < n_nodes; i++) {
h_color[i].store(WHITE);
}
h_tail[0].store(0);
h_head[0].store(0);
h_threads_end[0].store(0);
h_threads_run[0].store(0);
h_q1[0] = source;
h_iter[0].store(0);
h_overflow[0] = 0;
h_gray_shade[0].store(GRAY0);
timer.stop("Initialization");
//timer.print("Initialization", 1);
// Copy to device
timer.start("Copy To Device");
cudaStatus = cudaMemcpy(d_nodes, h_nodes, sizeof(Node) * n_nodes,
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_edges, h_edges, sizeof(Edge) * n_edges,
cudaMemcpyHostToDevice);
cudaDeviceSynchronize();
CUDA_ERR();
timer.stop("Copy To Device");
for (int rep = 0; rep < p.n_reps; rep++) {
// Reset
for (int i = 0; i < n_nodes; i++) {
h_cost[i].store(INF);
}
h_cost[source].store(0);
for (int i = 0; i < n_nodes; i++) {
h_color[i].store(WHITE);
}
it_cpu = 0;
it_gpu = 0;
h_tail[0].store(0);
h_head[0].store(0);
h_threads_end[0].store(0);
h_threads_run[0].store(0);
h_q1[0] = source;
h_iter[0].store(0);
h_overflow[0] = 0;
h_gray_shade[0].store(GRAY0);
// if(rep >= p.n_warmup)
timer.start("Kernel");
#ifdef LOGS
start_iteration();
#endif
// Run first iteration in master CPU thread
h_num_t[0] = 1;
int pid;
int index_i, index_o;
for (index_i = 0; index_i < h_num_t[0]; index_i++) {
pid = h_q1[index_i];
h_color[pid].store(BLACK);
int cur_cost = h_cost[pid].load();
for (int i = h_nodes[pid].x; i < (h_nodes[pid].y + h_nodes[pid].x);
i++) {
int id = h_edges[i].x;
int cost = h_edges[i].y;
cost += cur_cost;
h_cost[id].store(cost);
h_color[id].store(GRAY0);
index_o = h_tail[0].fetch_add(1);
h_q2[index_o] = id;
}
}
h_num_t[0] = h_tail[0].load();
h_tail[0].store(0);
h_threads_run[0].fetch_add(1);
h_gray_shade[0].store(GRAY1);
h_iter[0].fetch_add(1);
// if(rep >= p.n_warmup)
timer.stop("Kernel");
// Pointers to input and output queues
int * h_qin = h_q2;
int * h_qout = h_q1;
int * d_qin = d_q2;
int * d_qout = d_q1;
const int CPU_EXEC = (p.n_threads > 0) ? 1 : 0;
const int GPU_EXEC =
(p.n_gpu_blocks > 0 && p.n_gpu_threads > 0) ? 1 : 0;
// Run subsequent iterations on CPU or GPU until number of input queue elements is 0
while (*h_num_t != 0) {
if ((*h_num_t < p.switching_limit || GPU_EXEC == 0)
&& CPU_EXEC == 1) { // If the number of input queue elements is lower than switching_limit
it_cpu = it_cpu + 1;
// if(rep >= p.n_warmup)
timer.start("Kernel");
// Continue until switching_limit condition is not satisfied
while ((*h_num_t != 0)
&& (*h_num_t < p.switching_limit || GPU_EXEC == 0)
&& CPU_EXEC == 1) {
// Swap queues
if (h_iter[0] % 2 == 0) {
h_qin = h_q1;
h_qout = h_q2;
} else {
h_qin = h_q2;
h_qout = h_q1;
}
std::thread main_thread(run_cpu_threads, h_nodes, h_edges,
h_cost, h_color, h_qin, h_qout, h_num_t, h_head,
h_tail, h_threads_end, h_threads_run, h_gray_shade,
h_iter, p.n_threads, p.switching_limit, GPU_EXEC);
main_thread.join();
h_num_t[0] = h_tail[0].load(); // Number of elements in output queue
h_tail[0].store(0);
h_head[0].store(0);
if (h_iter[0].load() % 2 == 0)
h_gray_shade[0].store(GRAY0);
else
h_gray_shade[0].store(GRAY1);
}
// if(rep >= p.n_warmup)
timer.stop("Kernel");
} else if ((*h_num_t >= p.switching_limit || CPU_EXEC == 0)
&& GPU_EXEC == 1) { // If the number of input queue elements is higher than or equal to switching_limit
it_gpu = it_gpu + 1;
// if(rep >= p.n_warmup)
timer.start("Copy To Device");
cudaStatus = cudaMemcpy(d_cost, h_cost, sizeof(int) * n_nodes,
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_color, h_color, sizeof(int) * n_nodes,
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_threads_run, h_threads_run,
sizeof(int), cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_threads_end, h_threads_end,
sizeof(int), cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_overflow, h_overflow, sizeof(int),
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_q1, h_q1, sizeof(int) * n_nodes,
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_q2, h_q2, sizeof(int) * n_nodes,
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_iter, h_iter, sizeof(int),
cudaMemcpyHostToDevice);
cudaDeviceSynchronize();
CUDA_ERR();
// if(rep >= p.n_warmup)
timer.stop("Copy To Device");
// Continue until switching_limit condition is not satisfied
while ((*h_num_t != 0)
&& (*h_num_t >= p.switching_limit || CPU_EXEC == 0)
&& GPU_EXEC == 1) {
// Swap queues
if (h_iter[0] % 2 == 0) {
d_qin = d_q1;
d_qout = d_q2;
} else {
d_qin = d_q2;
d_qout = d_q1;
}
// if(rep >= p.n_warmup)
timer.start("Copy To Device");
cudaStatus = cudaMemcpy(d_num_t, h_num_t, sizeof(int),
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_tail, h_tail, sizeof(int),
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_head, h_head, sizeof(int),
cudaMemcpyHostToDevice);
cudaStatus = cudaMemcpy(d_gray_shade, h_gray_shade,
sizeof(int), cudaMemcpyHostToDevice);
cudaDeviceSynchronize();
CUDA_ERR();
// if(rep >= p.n_warmup)
timer.stop("Copy To Device");
// if(rep >= p.n_warmup)
timer.start("Kernel");
assert(
p.n_gpu_threads <= max_gpu_threads
&& "The thread block size is greater than the maximum thread block size that can be used on this device");
cudaStatus = call_SSSP_gpu(p.n_gpu_blocks, p.n_gpu_threads,
d_nodes, d_edges, d_cost, d_color, d_qin, d_qout,
d_num_t, d_head, d_tail, d_threads_end,
d_threads_run, d_overflow, d_gray_shade, d_iter,
p.switching_limit, CPU_EXEC,
sizeof(int) * (W_QUEUE_SIZE + 3));
cudaDeviceSynchronize();
CUDA_ERR();
// if(rep >= p.n_warmup)
timer.stop("Kernel");
// if(rep >= p.n_warmup)
timer.start("Copy Back and Merge");
cudaStatus = cudaMemcpy(h_tail, d_tail, sizeof(int),
cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_iter, d_iter, sizeof(int),
cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
CUDA_ERR();
// if(rep >= p.n_warmup)
timer.stop("Copy Back and Merge");
h_num_t[0] = h_tail[0].load(); // Number of elements in output queue
h_tail[0].store(0);
h_head[0].store(0);
if (h_iter[0].load() % 2 == 0)
h_gray_shade[0].store(GRAY0);
else
h_gray_shade[0].store(GRAY1);
}
// if(rep >= p.n_warmup)
timer.start("Copy Back and Merge");
cudaStatus = cudaMemcpy(h_cost, d_cost, sizeof(int) * n_nodes,
cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_color, d_color, sizeof(int) * n_nodes,
cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_threads_run, d_threads_run,
sizeof(int), cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_threads_end, d_threads_end,
sizeof(int), cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_overflow, d_overflow, sizeof(int),
cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_q1, d_q1, sizeof(int) * n_nodes,
cudaMemcpyDeviceToHost);
cudaStatus = cudaMemcpy(h_q2, d_q2, sizeof(int) * n_nodes,
cudaMemcpyDeviceToHost);
cudaDeviceSynchronize();
CUDA_ERR();
// if(rep >= p.n_warmup)
timer.stop("Copy Back and Merge");
}
}
#ifdef LOGS
end_iteration();
#endif
// printf("IT CPU:%d\t",it_cpu);
//printf("IT GPU:%d\n",it_gpu);
if (p.mode == 1) {
err = newest_verify(h_cost, n_nodes, n_nodes, gold, it_cpu, it_gpu);
} //err=new_verify(h_cost, n_nodes,,it_cpu,it_gpu);
if (err > 0) {
printf("Errors: %d\n", err);
read_input(source, h_nodes, h_edges, p);
read_gold(gold, p);
} else {
printf(".ITERATION %d\n", rep);
}
#ifdef LOGS
log_error_count(err);
#endif
// Ler a entrada novamente
//read_input(source, h_nodes, h_edges, p);
//read_gold(gold,p);
} // end of iteration
#ifdef LOGS
end_log_file();
#endif
// timer.print("Allocation", 1);
//timer.print("Copy To Device", p.n_reps);
// timer.print("Kernel", p.n_reps);
// timer.print("Copy Back and Merge", p.n_reps);
if (p.mode == 0) {
create_output(h_cost, n_nodes, n_edges, std::string(p.comparison_file));
}
// Verify answer
verify(h_cost, n_nodes, p.comparison_file);
// Free memory
timer.start("Deallocation");
free(h_nodes);
free(h_edges);
free(h_color);
free(h_cost);
free(h_q1);
free(h_q2);
cudaStatus = cudaFree(d_nodes);
cudaStatus = cudaFree(d_edges);
cudaStatus = cudaFree(d_cost);
cudaStatus = cudaFree(d_color);
cudaStatus = cudaFree(d_q1);
cudaStatus = cudaFree(d_q2);
cudaStatus = cudaFree(d_num_t);
cudaStatus = cudaFree(d_head);
cudaStatus = cudaFree(d_tail);
cudaStatus = cudaFree(d_threads_end);
cudaStatus = cudaFree(d_threads_run);
cudaStatus = cudaFree(d_overflow);
cudaStatus = cudaFree(d_iter);
cudaStatus = cudaFree(d_gray_shade);
CUDA_ERR();
cudaDeviceSynchronize();
timer.stop("Deallocation");
//timer.print("Deallocation", 1);
// Release timers
timer.release("Allocation");
timer.release("Initialization");
timer.release("Copy To Device");
timer.release("Kernel");
timer.release("Copy Back and Merge");
timer.release("Deallocation");
printf("Test Passed\n");
return 0;
}
