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Subdivide A Problem To A Pool Of Workers (No Shared Data)
Take a hard to compute problem and split it up between multiple worker threads. In your solution, try to fully utilize available cores or processors. (I'm looking at you, Python!)
Note: In this question, there should be no need for shared state between worker threads while the problem is being solved. Only after every thread completes computation are the answers recombined into a single output.
Example:
-Input-
(In python syntax)
In other words, a list of random strings.
-Output-
(In python syntax)
In other words, all possible permutations of each input string are computed.
python python 2.7
Submit a new solution for python
There are 13 other solutions in additional languages (clojure, cpp, fantom, fsharp ...)
Note: In this question, there should be no need for shared state between worker threads while the problem is being solved. Only after every thread completes computation are the answers recombined into a single output.
Example:
-Input-
(In python syntax)
["ab", "we", "tfe", "aoj"]
In other words, a list of random strings.
-Output-
(In python syntax)
[ ["ab", "ba", "aa", "bb", "a", "b"], ["we", "ew", "ww", "ee", "w", "e"], ...
In other words, all possible permutations of each input string are computed.
import multiprocessing
import itertools
task_input = ["ab", "we", "tfe", "aoj"]
def all_subperms(s):
return set(reduce(
list.__add__,
([''.join(p) for p in itertools.product(s, repeat=r) if p]
for r in xrange(len(s) + 1))))
p = multiprocessing.Pool(len(task_input))
task_output = p.map(all_subperms, task_input)
print map(list, task_output)
import itertools
task_input = ["ab", "we", "tfe", "aoj"]
def all_subperms(s):
return set(reduce(
list.__add__,
([''.join(p) for p in itertools.product(s, repeat=r) if p]
for r in xrange(len(s) + 1))))
p = multiprocessing.Pool(len(task_input))
task_output = p.map(all_subperms, task_input)
print map(list, task_output)
Submit a new solution for python
There are 13 other solutions in additional languages (clojure, cpp, fantom, fsharp ...)
