The impact of paravirtualized memory hierarchy on linear algebra computational kernels and software

Conference Paper (PDF Available) · January 2008with37 Reads
DOI: 10.1145/1383422.1383440 · Source: DBLP
Conference: Proceedings of the 17th International Symposium on High-Performance Distributed Computing (HPDC-17 2008), 23-27 June 2008, Boston, MA, USA
Abstract
Previous studies have revealed that paravirtualization im- poses minimal performance overhead on High Performance Computing (HPC) workloads, while exposing numerous ben- efits for this field. In this study, we are investigating the memory hierarchy characteristics of paravirtualized systems and their impact on automatically-tuned software systems. We are presenting an accurate characterization of memory attributes using hardware counters and user-process account- ing. For that, we examine the proficiency of ATLAS, a quintessential example of an autotuning software system, in tuning the BLAS library routines for paravirtualized sys- tems. In addition, we examine the effects of paravirtual- ization on the performance boundary. Our results show that the combination of ATLAS and Xen paravirtualiza- tion delivers native execution performance and nearly iden- tical memory hierarchy performance profiles. Our research thus exposes new benefits to memory-intensive applications arising from the ability to slim down the guest OS without influencing the system performance. In addition, our find- ings support a novel and very attractive deployment scenario for computational science and engineering codes on virtual clusters and computational clouds.

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