HPC System Software for Regular and Irregular Parallel Applications

The upcoming generation of system software for High Performance Computing is expected to provide a richer set of functionalities without compromising application performance. This Ph.D. thesis addresses the problem of designing scalable system software for both regular and irregular applications. The contributions are two-fold. First, we evaluate the drawbacks of current HPC system software for regular applications. We describe a methodology to precisely measure jitter on a general-purpose OS. Considering a lightweight operating system (IBM CNK), we analyze the overhead of adding support for a missing feature such as dynamic memory management. Second, we focus on irregular applications and build a specialized runtime system to enhance this kind of applications on common HPC flop intensive systems. The proposed runtime system provides a global address space abstraction of a distributed memory machine combined with a transparent fork/join execution model and it also includes lightweight multithreading and network message aggregation.