Portable Multicore Resource Management for Applications with Performance Constraints

Many modern software applications have performance requirements, like mobile and embedded systems that must keep up with sensor data, or web services that must return results to users within an acceptable latency bound. For such applications, the goal is not to run as fast as possible, but to meet their performance requirements with minimal resource usage, the key resource in most systems being energy. Heuristic solutions have been proposed to minimize energy under a performance constraint, but recent studies show that these approaches are not portable - heuristics that are near-optimal on one system can waste integer factors of energy on others. The POET library and runtime system provides a portable method for resource management that achieves near-optimal energy consumption while meeting soft real-time constraints across a range of devices. Although POET was originally designed and tested on embedded and mobile platforms, in this paper we evaluate it on a manycore server-class system. The larger scale of manycore systems adds some overhead to adjusting resource allocations, but POET still meets timing constraints and achieves near-optimal energy consumption. We demonstrate that POET achieves portable energy efficiency on platforms ranging from low-power ARM big.LITTLE architectures to powerful x86 server-class systems.