Platform-independent analysis of function-level communication in workloads

The emergence of many-core and heterogeneous multicore processors has meant that data communication patterns increasingly determine application performance. Microprocessor designers need tools that can extract and represent these producer-consumer relationships for a workload to aid them in a wide range of tasks including hardware-software co-design, software partitioning, and application performance optimization. This paper presents Sigil, a profiling tool that can extract communication patterns within a workload independent of hardware characteristics. We show how our methodology can extract the true costs of communication within a workload by distinguishing between unique, local, and total communication. We describe the implementation and performance of Sigil as well as the results of several case studies.