rf_station.t_rf[0, turn], bucket_tolerance=0) # shiftX=rf_station.phi_rf[0, turn]/rf_station.omega_rf[0, turn]) if worker.isMaster: # profile.fwhm() slicesMonitor.track(turn) worker.DLB(turn, beam) beam.gather() end_t = time.time() mpiprint('Total time: ', end_t - start_t) timing.report(total_time=1e3 * (end_t - start_t), out_dir=args['timedir'], out_file='worker-{}.csv'.format(worker.rank)) worker.finalize() if args['monitor'] > 0: slicesMonitor.close() mpiprint('dE mean: ', np.mean(beam.dE)) mpiprint('dE std: ', np.std(beam.dE)) mpiprint('profile sum: ', np.sum(profile.n_macroparticles)) # --- Saving results ---------------------------------------------------- mpiprint('Done!')
os.environ['OMP_NUM_THREADS'] = str(n_threads) np.random.seed(0) A = np.random.randn(size) B = np.random.randn(size) papiprof = PAPIProf(metrics=['IPC', 'L2_MISS_RATE', 'LLC_MISS_RATE']) papiprof.list_events() papiprof.list_metrics() papiprof.list_avail_metrics() with timing.timed_region('tiled_vector_add') as tr: papiprof.start_counters() for s in range(0, size, block): e = min(s + block, size) for i in range(n_turns): result = A[s:e] + B[s:e] papiprof.stop_counters() with timing.timed_region('vector_add') as tr: papiprof.start_counters() # for s in range(0, size, block): # e = min(s+block, size) for i in range(n_turns): result = A + B papiprof.stop_counters() timing.report() papiprof.report_counters() papiprof.report_metrics()