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SPLASH 2017
Sun 22 - Fri 27 October 2017 Vancouver, Canada

The C++ Actor Framework (CAF) was designed for using multiple, exchangeable schedulers with a default choice of random work stealing (RWS) for load-balancing. RWS is excellently scalable, and by choosing a random victim scheduling is kept simple with minimal information required. On the downside, it ignores data locality and misses opportunities to improve the application performance.

In this paper, we contribute a locality-guided scheduling that exploits knowledge about the host system to adapt runtime deployment and thereby improves the performance of actor based applications. We implement and thoroughly analyze a CAF scheduler which considers the trade-off between \emph{communication locality} and \emph{execution locality}. The former describes the locality of communicating actors, while the latter the locality between a worker, which executes an actor, and the location of its data. Extensive performance evaluations show a performance gain for data intensive application of up to 25% on a 64 core NUMA machine.

Mon 23 Oct

agere-2017
13:30 - 15:00: AGERE 2017 - Session 2: Runtime Environments and Debugging at Prince of Wales
Chair(s): Joeri De KosterVrije Universiteit Brussel, Belgium
agere-2017150875820000013:30 - 14:00
Talk
File Attached
agere-2017150876000000014:00 - 14:30
Talk
Carmen Torres Lopez, Stefan MarrUniversity of Kent, Elisa Gonzalez BoixVrije Universiteit Brussel, Hanspeter MössenböckJKU Linz, Austria, Christophe ScholliersUniversiteit Gent, Belgium
agere-2017150876180000014:30 - 15:00
Talk
Kazuhiro ShibanaiTokyo Institute of Technology, Takuo WatanabeTokyo Institute of Technology
Link to publication DOI