parallelising the computational algebra system gap
We report on the project of parallelising GAP, a system for computational algebra. Our design aims to make concurrency facilities available for GAP users, while preserving as much of the existing code base (about one million lines of code) with as few changes as possible and without requiring users---a large percentage of whom 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 and via limited use of lockable shared data spaces.
gap data spaces shared memory programming