NUMA-Aware Non-Blocking Calendar Queue

Maryan Rab, Romolo Marotta, Mauro Ianni, Alessandro Pellegrini, and Francesco Quaglia

Published in: Proceedings of the 24th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications
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Modern computing platforms are based on multi-processor/multi-core technology. This allows running applications with a high degree of hardware parallelism. However, medium-to-high end machines pose a problem related to the asymmetric delays threads experience when accessing shared data. Specifically, Non-Uniform-Memory-Access (NUMA) is the dominating technology—thanks to its capability for scaled-up memory bandwidth—which however imposes asymmetric distances between CPU-cores and memory banks, making an access by a thread to data placed on a far NUMA node severely impacting performance. In this article, we tackle this problem in the context of shared event-pool management, a relevant aspect in many fields, like parallel discrete event simulation. Specifically, we present a NUMA-aware calendar queue, which also has the advantage of making concurrent threads coordinate via a non-blocking scalable approach. Our proposal is based on work deferring combined with dynamic re-binding of the calendar queue operations (insertions/extractions) to the best suited among the concurrent threads hosted by the underlying computing platform. This changes the locality of the operations by threads in a way positively reflected onto NUMA tasks at the hardware level. We report the results of an experimental study, demonstrating the capability of our solution to achieve the order of 15% better performance compared to state-of-the-art solutions already suited for multi-core environments.

BibTeX Entry:

author = {Rab, Maryan and Marotta, Romolo and Ianni, Mauro and Pellegrini, Alessandro and Quaglia, Francesco},
booktitle = {Proceedings of the 24th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications},
title = {NUMA-Aware Non-Blocking Calendar Queue},
year = {2020},
month = sep,
publisher = {IEEE},
series = {DS-RT},
location = {Prague, Czech Republic}