Towards High-Performance Computational Algebra with GAP
We present the project of parallelising the computational algebra system GAP. Our design aims to make concurrency facilities available for GAP users, while preserving as much of the existing codebase (about one million lines of code) with as few changes as possible without requiring users (a large percentage of which are domain experts in their fields without necessarily having a background in parallel programming) to have to learn complicated parallel programming techniques. To this end, we preserve the appearance of sequentiality on a per-thread basis by containing each thread within its own data space. Parallelism is made possible through the notion of migrating objects out of one thread’s data space into that of another one, allowing threads to interact.
KeywordsGAP shared memory programming threads data spaces
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