thesis

7.2 Features 191
this task, two stages are required. First, the task itself must be written : it is a Python
class which actually performs the computation. Every computing unit stores
and executes its own instance. Then, the task launcher executes on the client and
launches the task on the CPUs on the local machine or on several machines across
the network.
import numpy, playdoh
class PiMonteCarlo(playdoh.ParallelTask):
def initialize(self, n):
self.n = n # number of points on this node
def start(self):
# Draws n points uniformly in [0,1]^2
samples = numpy.random.rand(2, self.n)
# Number of points inside the quarter unit circle
self.count = numpy.sum(samples[0, :] ** 2 + samples[1, :] ** 2