Improving the Performance of Actor Model Runtime Environments on Multicore and Manycore Platforms


The actor model is present in many systems that demand substantial computing resources which are often provided by multicore and multiprocessor platforms such as non-uniform memory access architectures (NUMA) and manycore processors. Yet, no mainstream actor model runtime environment (RE) currently in use takes into account the hierarchical memory characteristics of these platforms. These REs essentially assume a flat-memory space therefore not performing as well as they could. In this paper we present our proposal to improve the performance of these systems. Using knowledge about the general characteristics of actor-based applications and the underlying platform, we propose techniques spanning from memory management to scheduling and load-balancing. Based on previous work, we present our design guidelines for the RE adaptation to the Kalray MPPA-256 manycore processor.

Proceedings of the 3rd International Workshop on Programming based on Actors, Agents, and Decentralized Control (AGERE) held in the Annual Conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH), Indianapolis, Indiana, Oct 2013.