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In practice, standard scheduling of parallel computing jobs almost alwaysleaves significant portions of the available hardware unused, even with manyjobs still waiting in the queue. The simple reason is that the resourcerequests of these waiting jobs are fixed and do not match the available, unusedresources. However, with alternative but existing and well-establishedtechniques it is possible to achieve a fully automated, adaptive parallelismthat does not need pre-set, fixed resources. Here, we demonstrate that such anadaptively parallel program can indeed fill in all such scheduling gaps, evenin real-life situations on large supercomputers.

Adaptive parallelism with RMI: Idle high-performance computing resources can be completely avoided