schwimmbad: A uniform interface to parallel processing pools in Python
Abstract
Many scientific and computing problems require doing some calculation on all elements of some data set. If the calculations can be executed in parallel (i.e. without any communication between calculations), these problems are said to be perfectly parallel. On computers with multiple processing cores, these tasks can be distributed and executed in parallel to greatly improve performance. A common paradigm for handling these distributed computing problems is to use a processing "pool": the "tasks" (the data) are passed in bulk to the pool, and the pool handles distributing the tasks to a number of worker processes when available. schwimmbad provides a uniform interface to parallel processing pools and enables switching easily between local development (e.g., serial processing or with multiprocessing) and deployment on a cluster or supercomputer (via, e.g., MPI or JobLib).
- Publication:
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The Journal of Open Source Software
- Pub Date:
- September 2017
- DOI:
- Bibcode:
- 2017JOSS....2..357P