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

The actor model is present in many systems that demand substan-tial computing resources which are often provided by multicore and multiprocessor platforms such as non-uniform memory access ar-chitectures (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 pro-posal to improve the performance of these systems. Using knowl-edge 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 adap-tation to the Kalray MPPA-256 manycore processor