c++ - tutorial - ¿Puedo informar el progreso de las tareas de openmp?

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Question

Imagine una tarea OMP clásica:

• Sumando un gran vector de dobles en el rango [0.0, 1.0)

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using namespace std;
int main() {
vector<double> v;
// generate some data
generate_n(back_inserter(v), 1ul << 18,
bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));
long double sum = 0;
{
#pragma omp parallel for reduction(+:sum)
for(size_t i = 0; i < v.size(); i++)
{
sum += v[i];
}
}
std::cout << "Done: sum = " << sum << "/n";
}

Tengo problemas para tener una idea de cómo informar el progreso. Después de todo, OMP está manejando toda la coordinación entre los hilos del equipo para mí, y no tengo un estado global.

Podría utilizar un std::thread normal y observar alguna variable compartida desde allí, pero ¿no hay una forma más "omp-ish" de lograr esto?

Answer 1

En procesadores sin soporte atómico nativo (e incluso con ellos) utilizando #pragma omp atomic , como sugieren las otras respuestas aquí, puede ralentizar el programa.

La idea de un indicador de progreso es darle al usuario una idea de cuándo terminará algo. Si está en el objetivo más / menos una pequeña fracción del tiempo total de ejecución, el usuario no se molestará demasiado. Es decir, el usuario preferiría que las cosas terminen antes a expensas de saber con mayor exactitud cuándo terminarán las cosas.

Por este motivo, generalmente hago un seguimiento del progreso en solo un hilo y lo uso para estimar el progreso total. Esto está bien para situaciones en las que cada hilo tiene una carga de trabajo similar. Como está utilizando #pragma omp parallel for , probablemente trabaje sobre una serie de elementos similares sin interdependencias, por lo que mi suposición probablemente sea válida para su caso de uso.

He envuelto esta lógica en una clase ProgressBar , que generalmente incluyo en un archivo de encabezado, junto con su clase auxiliar Timer . La clase usa señales de control ANSI para que las cosas se vean bien.

La salida se ve así:

[====== ] (12% - 22.0s - 4 threads)

También es fácil que el compilador elimine todos los gastos generales de la -DNOPROGRESS progreso al declarar el -DNOPROGRESS compilación -DNOPROGRESS .

Código y un ejemplo de uso a continuación:

#include <iostream>
#include <chrono>
#include <thread>
#include <iomanip>
#include <stdexcept>
#ifdef _OPENMP
///Multi-threading - yay!
#include <omp.h>
#else
///Macros used to disguise the fact that we do not have multithreading enabled.
#define omp_get_thread_num() 0
#define omp_get_num_threads() 1
#endif
///@brief Used to time how intervals in code.
///
///Such as how long it takes a given function to run, or how long I/O has taken.
class Timer{
private:
typedef std::chrono::high_resolution_clock clock;
typedef std::chrono::duration<double, std::ratio<1> > second;
std::chrono::time_point<clock> start_time; ///< Last time the timer was started
double accumulated_time; ///< Accumulated running time since creation
bool running; ///< True when the timer is running
public:
Timer(){
accumulated_time = 0;
running = false;
}
///Start the timer. Throws an exception if timer was already running.
void start(){
if(running)
throw std::runtime_error("Timer was already started!");
running=true;
start_time = clock::now();
}
///Stop the timer. Throws an exception if timer was already stopped.
///Calling this adds to the timer''s accumulated time.
///@return The accumulated time in seconds.
double stop(){
if(!running)
throw std::runtime_error("Timer was already stopped!");
accumulated_time += lap();
running = false;
return accumulated_time;
}
///Returns the timer''s accumulated time. Throws an exception if the timer is
///running.
double accumulated(){
if(running)
throw std::runtime_error("Timer is still running!");
return accumulated_time;
}
///Returns the time between when the timer was started and the current
///moment. Throws an exception if the timer is not running.
double lap(){
if(!running)
throw std::runtime_error("Timer was not started!");
return std::chrono::duration_cast<second> (clock::now() - start_time).count();
}
///Stops the timer and resets its accumulated time. No exceptions are thrown
///ever.
void reset(){
accumulated_time = 0;
running = false;
}
};
///@brief Manages a console-based progress bar to keep the user entertained.
///
///Defining the global `NOPROGRESS` will
///disable all progress operations, potentially speeding up a program. The look
///of the progress bar is shown in ProgressBar.hpp.
class ProgressBar{
private:
uint32_t total_work; ///< Total work to be accomplished
uint32_t next_update; ///< Next point to update the visible progress bar
uint32_t call_diff; ///< Interval between updates in work units
uint32_t work_done;
uint16_t old_percent; ///< Old percentage value (aka: should we update the progress bar) TODO: Maybe that we do not need this
Timer timer; ///< Used for generating ETA
///Clear current line on console so a new progress bar can be written
void clearConsoleLine() const {
std::cerr<<"/r/033[2K"<<std::flush;
}
public:
///@brief Start/reset the progress bar.
///@param total_work The amount of work to be completed, usually specified in cells.
void start(uint32_t total_work){
timer = Timer();
timer.start();
this->total_work = total_work;
next_update = 0;
call_diff = total_work/200;
old_percent = 0;
work_done = 0;
clearConsoleLine();
}
///@brief Update the visible progress bar, but only if enough work has been done.
///
///Define the global `NOPROGRESS` flag to prevent this from having an
///effect. Doing so may speed up the program''s execution.
void update(uint32_t work_done0){
//Provide simple way of optimizing out progress updates
#ifdef NOPROGRESS
return;
#endif
//Quick return if this isn''t the main thread
if(omp_get_thread_num()!=0)
return;
//Update the amount of work done
work_done = work_done0;
//Quick return if insufficient progress has occurred
if(work_done<next_update)
return;
//Update the next time at which we''ll do the expensive update stuff
next_update += call_diff;
//Use a uint16_t because using a uint8_t will cause the result to print as a
//character instead of a number
uint16_t percent = (uint8_t)(work_done*omp_get_num_threads()*100/total_work);
//Handle overflows
if(percent>100)
percent=100;
//In the case that there has been no update (which should never be the case,
//actually), skip the expensive screen print
if(percent==old_percent)
return;
//Update old_percent accordingly
old_percent=percent;
//Print an update string which looks like this:
// [================================================ ] (96% - 1.0s - 4 threads)
std::cerr<<"/r/033[2K["
<<std::string(percent/2, ''='')<<std::string(50-percent/2, '' '')
<<"] ("
<<percent<<"% - "
<<std::fixed<<std::setprecision(1)<<timer.lap()/percent*(100-percent)
<<"s - "
<<omp_get_num_threads()<< " threads)"<<std::flush;
}
///Increment by one the work done and update the progress bar
ProgressBar& operator++(){
//Quick return if this isn''t the main thread
if(omp_get_thread_num()!=0)
return *this;
work_done++;
update(work_done);
return *this;
}
///Stop the progress bar. Throws an exception if it wasn''t started.
///@return The number of seconds the progress bar was running.
double stop(){
clearConsoleLine();
timer.stop();
return timer.accumulated();
}
///@return Return the time the progress bar ran for.
double time_it_took(){
return timer.accumulated();
}
uint32_t cellsProcessed() const {
return work_done;
}
};
int main(){
ProgressBar pg;
pg.start(100);
//You should use ''default(none)'' by default: be specific about what you''re
//sharing
#pragma omp parallel for default(none) schedule(static) shared(pg)
for(int i=0;i<100;i++){
pg.update(i);
std::this_thread::sleep_for(std::chrono::seconds(1));
}
}

Answer 2

Mi código a continuación es similar al sehe , pero hay algunas diferencias, lo que me permitió lidiar con los puntos omitidos para informar debido a las igualdades exactas, que implican la división por módulo. Además, el contador global recopila ejecuciones de bucle reales para todos los hilos, pero puede ser impreciso, lo que es aceptable para este problema en particular. Yo uso solo el hilo maestro para reportar.

const size_t size = ...
const size_t step_size = size / 100;
const size_t nThreads = ...
const size_t local_count_max = step_size / nThreads;
size_t count = 0;
#pragma omp parallel num_threads(nThreads)
{
size_t reported_count = 0;
size_t local_count = 0;
#pragma omp for
for (size_t i = 0; i < size; ++i)
{
<... do some useful work ...>
// -------------------------- update local and global progress counters
if (local_count >= local_count_max)
{
#pragma omp atomic
count += local_count_max;
local_count = 0;
}
else
{
++local_count;
}
// ------------------------------ report progress (in master thread only)
#pragma omp master
if (count - reported_count >= step_size)
{
<... report the progress ...>
reported_count = count;
}
}
}

Answer 3

Simplemente permita que cada hilo en el equipo rastree el progreso local y actualice un contador global atómicamente. Todavía podría hacer que otro hilo lo observe o, como en mi ejemplo a continuación, podría simplemente hacer la salida del terminal dentro de una sección crítica de OMP.

La clave aquí es sintonizar un tamaño de paso que no conduzca a actualizaciones altamente frecuentes, porque entonces el bloqueo de la región crítica (y en menor medida la carga atómica / almacena) degradaría el rendimiento.

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#include <omp.h>
#include <vector>
#include <random>
#include <algorithm>
#include <iterator>
#include <functional>
#include <iostream>
#include <iomanip>
using namespace std;
int main() {
vector<double> v;
// generate some data
generate_n(back_inserter(v), 1ul << 18, bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));
auto step_size = 100ul;
auto total_steps = v.size() / step_size + 1;
size_t steps_completed = 0;
long double sum = 0;
#pragma omp parallel
{
size_t local_count = 0;
#pragma omp for reduction(+:sum)
for(size_t i = 0; i < v.size(); i++)
{
sum += v[i];
if (local_count++ % step_size == step_size-1)
{
#pragma omp atomic
++steps_completed;
if (steps_completed % 100 == 1)
{
#pragma omp critical
std::cout << "Progress: " << steps_completed << " of " << total_steps << " (" << std::fixed << std::setprecision(1) << (100.0*steps_completed/total_steps) << "%)/n";
}
}
}
}
std::cout << "Done: sum = " << sum << "/n";
}

Finalmente, imprima el resultado. Salida:

Progress: 1 of 2622 (0.0%)
Progress: 191 of 2622 (7.3%)
Progress: 214 of 2622 (8.2%)
Progress: 301 of 2622 (11.5%)
Progress: 401 of 2622 (15.3%)
Progress: 501 of 2622 (19.1%)
Progress: 601 of 2622 (22.9%)
Progress: 701 of 2622 (26.7%)
Progress: 804 of 2622 (30.7%)
Progress: 901 of 2622 (34.4%)
Progress: 1003 of 2622 (38.3%)
Progress: 1101 of 2622 (42.0%)
Progress: 1201 of 2622 (45.8%)
Progress: 1301 of 2622 (49.6%)
Progress: 1402 of 2622 (53.5%)
Progress: 1501 of 2622 (57.2%)
Progress: 1601 of 2622 (61.1%)
Progress: 1701 of 2622 (64.9%)
Progress: 1801 of 2622 (68.7%)
Progress: 1901 of 2622 (72.5%)
Progress: 2001 of 2622 (76.3%)
Progress: 2101 of 2622 (80.1%)
Progress: 2203 of 2622 (84.0%)
Progress: 2301 of 2622 (87.8%)
Progress: 2402 of 2622 (91.6%)
Progress: 2501 of 2622 (95.4%)
Progress: 2601 of 2622 (99.2%)
Done: sum = 130943.8