POAP: Plumbing for Optimization with Asynchronous Parallelism
POAP provides an event-driven framework for building and combining asynchronous optimization strategies. A typical optimization code written with POAP might look like:
from poap.strategy import FixedSampleStrategy
from poap.strategy import CheckWorkStrategy
from poap.controller import ThreadController
from poap.controller import BasicWorkerThread
# samples = list of sample points ...
controller = ThreadController()
sampler = FixedSampleStrategy(samples)
controller.strategy = CheckWorkerStrategy(controller, sampler)
for i in range(NUM_WORKERS):
t = BasicWorkerThread(controller, objective)
controller.launch_worker(t)
result = controller.run()
print 'Best result: {0} at {1}'.format(result.value, result.params)The basic ingredients are a controller capable of asking workers to run function evaluations and a strategy for choosing where to sample. The strategies send the controller proposed actions, which the controller then accepts or rejects; the controller, in turn, informs the strategies of relevant events through callback functions.
Most users will probably want to provide their own strategies, controllers, or both.
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Release files for POAP 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| POAP-0.1.5.tar.gz | 14.6 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| POAP-0.1.5-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 33.8 kB
Release files / POAP-0.1.5.tar.gz
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