Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support

Noronha, R.; Panda, Dhabaleswar K.

doi:10.1109/ipdps.2007.370683

Cited by 14 publications

(5 citation statements)

References 9 publications

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“…In [5], the authors design an OpenMP implementation capable of using large pages and evaluate the impact of using large page support available in most modern processors on the performance and scalability of parallel OpenMP applications. Results show an improvement in performance of up to 25% for some applications.…”

Section: Related Workmentioning

confidence: 99%

Efficiency of Parallel Algorithms on Multi Core Systems Using OpenMP

Kathavate¹,

Visvesvaraya²

2014

International Journal of Advanced Research in Computer and Comm

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Abstract:The improvement in performance gained by the use of a multi core processor depends very much on the software algorithms used and their implementation. In particular, possible gains are limited by the fraction of the software that can be run in parallel simultaneously on multiple cores and this effect is described by Amdahl's law. Most applications, however, are not accelerated so much unless programmers invest a prohibitive amount of effort in refactoring the whole problem. In order to exploit the complete capabilities of multi core systems, applications have to become increasingly parallel in nature. Writing parallel program is not an easy task. OpenMP programming model helps in creating multithreaded applications for the existing sequential programs. This paper analyses the performance improvement of a parallel algorithm on multi core systems. The experimental results shows Significant speed up achieved on multi core systems with the parallel algorithm.

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Section: Related Workmentioning

confidence: 99%

Efficiency of Parallel Algorithms on Multi Core Systems Using OpenMP

Kathavate¹,

Visvesvaraya²

2014

International Journal of Advanced Research in Computer and Comm

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“…Many researches [1,2,3,4,5,6] have been carried out to improve the performance of OpenMP applications on multi-core system. Truong et al [1] seek to improve scalability from implementation aspect.…”

Section: Related Workmentioning

confidence: 99%

“…Their work introduces thread subteams to overcome the thread mapping problem and enhance modularity. Noronha et al [2] study the benefits from using large page support for OpenMP applications. Terboven et al [4] improve data and thread affinity of OpenMP programs on multi-core system by binding thread to thread cores and allocate memory with next touch strategy.…”

Section: Related Workmentioning

confidence: 99%

How OpenMP Applications Get More Benefit from Many-Core Era

Yan

Han

et al. 2010

Beyond Loop Level Parallelism in OpenMP: Accelerators, Tasking and More

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Abstract.With the approaching of the many-core era, it becomes more and more difficult for a single OpenMP application to efficiently utilize all the available processor cores. On the other hand, the available cores become more than necessary for some applications. We believe executing multiple OpenMP applications concurrently will be a common usage model in the future. In this model, how threads are scheduled on the cores are important as cores are asymmetric. We have designed and implemented a prototype scheduler, SWOMPS, to help schedule the threads of all the concurrent applications system-widely. The scheduler makes its decision based on underlying hardware configuration as well as the hints of scheduling preference of each application provided by users. Experiment evaluation shows SWOMPS is quite efficient in improving the performance.With the help of SWOMPS, we compared exclusive running one application and concurrent running multiple applications in term of system throughput and individual application performance. In various experimental comparisons, concurrent execution outperforms in throughput, meanwhile the performance slowdown of individual applications in concurrent execution is reasonable.

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“…Paper [19] evaluated large pages impact on OpenMP programs running on multicore systems. It shows a 25% performance improvement in 4 threads CG.…”

Section: Related Workmentioning

confidence: 99%

Evaluating the Effect of Huge Page on Large Scale Applications

Zhang

Huo

et al. 2009

2009 IEEE International Conference on Networking, Architecture, and Storage

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The ever-increasing memory footprint in large scale applications not only requires efficient computation, but also needs efficient communication. Traditionally huge page is used to reduce CPU's TLB miss, but how huge page impacts communication performance, and how HPC applications in large scale benefit from huge page are still not clear. In this paper, we support huge page in our D5000A platform and micro-benchmark the communication impacts of huge page in detail, also we evaluate the huge page impact on large scale HPC applications. Results show that huge page improves communication bandwidth by 40MB/s in large message sizes, greatly benefits communication performance when multiple connections share the same NIC. Applications such as NPB, Sweep3D, HPL show good performance improvement and good scalability in large scale. With huge page support, HPL achieves 2.76% improvement in 16384 cores.

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Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support

Abstract: Abstract

Cited by 14 publications

References 9 publications

Efficiency of Parallel Algorithms on Multi Core Systems Using OpenMP

Efficiency of Parallel Algorithms on Multi Core Systems Using OpenMP

How OpenMP Applications Get More Benefit from Many-Core Era

Evaluating the Effect of Huge Page on Large Scale Applications

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