Multi-core scalability-impacting compiler optimizations

Abstract

In a multi-core system, while the processor core pipelines and local caches are replicated in each core, other resources, such as shared cache and memory bus, are shared across all cores in a processor. Running multiple copies of memory intensive applications on different cores often leads to poor scaling, because these shared resources can become bottlenecks to throughput performance. Such issues have been traditionally studied under the design and evaluation of processors, platforms, and operating systems. We have identified a set of compiler optimizations that have measurable impact on the scaling of applications on multi-core systems and evaluated them based on the standard rate run of the SPEC CPU2006 benchmark suite, where throughput is measured by running multiple copies of a program in a multi-core and multi-processor system. We have also collected data and analyzed how these compiler optimizations affect the utilization and behaviors of the shared resources. Through our experimental results, we show that conventional compiler optimizations can play an important role in improving the scaling of running memory intensive application threads on multi-core systems.