An experimental model to analyze OpenMP applications for system utilization

Abstract

Data centers are increasingly focused on optimal use of resources. For technical computing environments, with compute-dominated workloads, we can increase data center efficiencies by increasing multi-core processor utilization. OpenMP programmers need assistance in better understanding efficiencies and scaling for both dedicated and throughput environments. An experimental OpenMP performance analysis model has been developed to give insight into many application scalability bottlenecks. A tool has been developed to implement the model. Compared to other performance analysis tools, this tool takes into account how the operating system scheduler affects OpenMP threaded application performance. Poor parallel scalability can result in reduced system utilization. A case study shows how the tool helped diagnose performance loss caused by OpenMP work distribution schedule strategies. Changing the work distribution schedule substantially improved application performance and system utilization. This tool is specific to Solaris and Studio compilers, although the performance model is applicable to other OpenMP compilers, Linux and UNIX systems. © 2011 Springer-Verlag.