Performance evaluation of the Red Storm dual‐core upgrade

Brightwell, Ron; Underwood, Keith D.; Vaughan, Courtenay T.; Stevenson, Joel O.

doi:10.1002/cpe.1526

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…Brightwell et al [24], [25] and [26] and Pedretti et al [27] analyze many aspects of network performance but do not evaluate power as part of their experiment. We have found no work that measures energy in-situ at any scale as it relates to network tuning.…”

Section: Related Workmentioning

confidence: 99%

Measuring and tuning energy efficiency on large scale high performance computing platforms.

Laros¹

2011

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Recognition of the importance of power in the field of High Performance Computing, whether it be as an obstacle, expense or design consideration, has never been greater and more pervasive. While research has been conducted on many related aspects, there is a stark absence of work focused on large scale High Performance Computing. Part of the reason is the lack of measurement capability currently available on small or large platforms. Typically, research is conducted using coarse methods of measurement such as inserting a power meter between the power source and the platform, or fine grained measurements using custom instrumented boards (with obvious limitations in scale). To collect the measurements necessary to analyze real scientific computing applications at large scale, an in-situ measurement capability must exist on a large scale capability class platform.In response to this challenge, we exploit the unique power measurement capabilities of the Cray XT architecture to gain an understanding of power use and the effects of tuning. We apply these capabilities at the operating system level by deterministically halting cores when idle. At the application level, we gain an understanding of the power requirements of a range of important DOE/NNSA production scientific computing applications running at large scale (thousands of nodes), while simultaneously collecting current and voltage measurements on the hosting nodes. We examine the effects of both CPU and network bandwidth tuning and demonstrate energy savings opportunities of up to 39% with little or no impact on run-time performance. Capturing scale effects in our 3 experimental results was key. Our results provide strong evidence that next generation large-scale platforms should not only approach CPU frequency scaling differently, but could also benefit from the capability to tune other platform components, such as the network, to achieve energy efficient performance. 5Acknowledgments I would like to acknowledge the following people who have contributed in various ways, all of which significant, to the successful completion of this work: Dr.

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Section: Related Workmentioning

confidence: 99%

Measuring and tuning energy efficiency on large scale high performance computing platforms.

Laros¹

2011

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High‐performance computing: to boldly go where no human has gone before

Limet

Smari

Spalazzi

2015

Concurrency and Computation

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International audienceComputing and computational science are well on their way to enter into the exascale era while High Performance Computing (HPC) is now present in many spheres and domains of modern society. New technologies such as cloud computing, big data, and connected objects open many perspectives and possibilities that were unattainable until now. These are high times for computing and for HPC in particular. The High Performance Computing \& Simulation conference aims to bring together researchers working on various aspects of HPC, their design and use, and their applications. As has been the conference tradition, selected extended papers of HPCS 2012 are presented in this special issue. These should be interesting contributions that supplement the current state-of-the-art research in HPC. To relate these works and highlight their value, in this article, we briefly trace back the history of HPC, sketch the state of the present research and development in the field, and project some of the challenges and future trends anticipated

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Performance evaluation of the Red Storm dual‐core upgrade

Cited by 2 publications

References 11 publications

Measuring and tuning energy efficiency on large scale high performance computing platforms.

Measuring and tuning energy efficiency on large scale high performance computing platforms.

High‐performance computing: to boldly go where no human has gone before

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