def main(args):
print('\nUsage: particle.py [num_chares_x num_chares_y] [max_particles_per_cell_start]')
if len(args) >= 3:
array_dims = (int(args[1]), int(args[2]))
else:
array_dims = (8, 4) # default: 2D chare array of 8 x 4 cells
if len(args) == 4:
max_particles_per_cell_start = int(args[3])
else:
max_particles_per_cell_start = 10000
print('\nCell array size:', array_dims[0], 'x', array_dims[1], 'cells')
# create 2D Cell chare array and start simulation
sim_done = Future()
cells = Array(Cell, array_dims,
args=[array_dims, max_particles_per_cell_start, sim_done],
useAtSync=True)
num_particles_per_cell = cells.getNumParticles(ret=True).get()
print('Total particles created:', sum(num_particles_per_cell))
print('Initial conditions:\n\tmin particles per cell:', min(num_particles_per_cell),
'\n\tmax particles per cell:', max(num_particles_per_cell))
print('\nStarting simulation')
t0 = time.time()
cells.run() # this is a broadcast
# wait for the simulation to finish
sim_done.get()
print('Particle simulation done, elapsed time=', round(time.time() - t0, 3), 'secs')
exit()
class Main(Chare):
def __init__(self, args):
charm.thisProxy.updateGlobals(
{
'mainProxy': self.thisProxy,
'NUM_CHARES': charm.numPes() * CHARES_PER_PE
},
'__main__',
awaitable=True).get()
self.arrayProxy = Array(Test, NUM_CHARES)
self.arrayProxy.run()
self.startTime = time.time()
def collectSum(self, result):
assert_almost_equal(result.sum(), NUM_CHARES * VAL_CHECK, 0.05)
self.arrayProxy.run()
def done(self):
print('Program done in', time.time() - self.startTime)
charm.printStats()
exit()
def main(args):
global blockDimX, blockDimY, num_chare_x, num_chare_y
if len(args) != 3 and len(args) != 5:
print('\nUsage:\t', args[0], 'array_size block_size')
print('\t', args[0],
'array_size_X array_size_Y block_size_X block_size_Y')
exit()
if len(args) == 3:
arrayDimX = arrayDimY = int(args[1])
blockDimX = blockDimY = int(args[2])
elif len(args) == 5:
arrayDimX, arrayDimY = [int(arg) for arg in args[1:3]]
blockDimX, blockDimY = [int(arg) for arg in args[3:5]]
assert (arrayDimX >= blockDimX) and (arrayDimX % blockDimX == 0)
assert (arrayDimY >= blockDimY) and (arrayDimY % blockDimY == 0)
num_chare_x = arrayDimX // blockDimX
num_chare_y = arrayDimY // blockDimY
# set the following global variables on every PE, wait for the call to complete
charm.thisProxy.updateGlobals(
{
'blockDimX': blockDimX,
'blockDimY': blockDimY,
'num_chare_x': num_chare_x,
'num_chare_y': num_chare_y
},
awaitable=True).get()
print('\nRunning Jacobi on', charm.numPes(), 'processors with',
num_chare_x, 'x', num_chare_y, 'chares')
print('Array Dimensions:', arrayDimX, 'x', arrayDimY)
print('Block Dimensions:', blockDimX, 'x', blockDimY)
print('Max iterations:', MAX_ITER)
print('Threshold:', THRESHOLD)
if numbaFound:
# wait until Numba functions are compiled on every PE, so we can get consistent benchmark results
Group(Util).compile(awaitable=True).get()
print('Numba compilation complete')
else:
print(
'!!WARNING!! Numba not found. Will run without Numba but it will be very slow'
)
sim_done = Future()
# create 2D chare array of Jacobi objects (each chare will hold one block)
array = Array(Jacobi, (num_chare_x, num_chare_y), args=[sim_done])
charm.awaitCreation(array)
print('Starting computation')
initTime = time.time()
array.run() # this is a broadcast
total_iterations = sim_done.get() # wait until the computation completes
totalTime = time.time() - initTime
if total_iterations >= MAX_ITER:
print('Finished due to max iterations', total_iterations, 'total time',
round(totalTime, 3), 'seconds')
else:
print('Finished due to convergence, iterations', total_iterations,
'total time', round(totalTime, 3), 'seconds')
exit()
