Many new large-scale applications have emerged recently and become increasingly important in areas of bioinformatics, social network analysis, etc. Unlike traditional HPC problems, these applications are data-intensive and often require large amount of small messages sent to random nodes. The traditional parallelization approaches for scientific applications are no longer well-suited to them. Active messages have been proven to be an effective way to parallelize such nontraditional HPC applications. However, most existing active messages libraries are low-level and system-specific, which are hard to be directly used in applications. In this talk I will focus on our study on adding active messages support in MPI based on MPI RMA interface to provide programmability and portability, and show how active messages works with multithreading to improve the performance of applications.

Bio:
I am a second-year PhD student from University of Illinois at Urbana-Champaign. My research interest focuses on parallel programming models and runtime systems for high performance computing. In this summer, I work with Dr. Pavan Balaji on exploring the compatibility of active messages with MPI RMA interface.