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()
