Model-based cache-aware dispatching of object-oriented software for multicore systems


Ovatman T. , Buzluca F.

JOURNAL OF SYSTEMS AND SOFTWARE, cilt.86, ss.2754-2770, 2013 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 86 Konu: 11
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.jss.2013.06.025
  • Dergi Adı: JOURNAL OF SYSTEMS AND SOFTWARE
  • Sayfa Sayıları: ss.2754-2770

Özet

In recent years, processor technology has evolved towards multicore processors, which include multiple processing units (cores) in a single package. Those cores, having their own private caches, often share a higher level cache memory dedicated to each processor die. This multi-level cache hierarchy in multicore processors raises the importance of cache utilization problem. Assigning parallel-running software components with common data to processor cores that do not share a common cache increases the number of cache misses. In this paper we present a novel approach that uses model-based information to guide the OS scheduler in assigning appropriate core affinities to software objects at run-time. We build graph models of software and cache hierarchies of processors and devise a graph matcher algorithm that provides mapping between these two graphs. Using this mapping we obtain candidate core sets that each software object can be affiliated with at run-time. These affiliations are determined based on the idea that software components that have the potential to share common data at run-time should run on cores that share a common cache. We also develop an object dispatcher algorithm that keeps track of object affiliations at run-time and dispatches objects by using the information from the compile-time graph matcher. We apply our approach on design pattern implementations and two different application program running on servers using CFS scheduling. Our results show that cache-aware dispatching based on information obtained from software model, decreases number of cache misses significantly and improves CFS' scheduling performance. (C) 2013 Elsevier Inc. All rights reserved.