10 Years Later: Cloud Computing is Closing the Performance Gap [article]

Giulia Guidi, Marquita Ellis, Aydin Buluc, Katherine Yelick, David Culler
<span title="2020-11-02">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Large scale modeling and simulation problems, from nanoscale materials to universe-scale cosmology, have in the past used the massive computing resources of High-Performance Computing (HPC) systems. Over the last decade, cloud computing has gained popularity for business applications and increasingly for computationally intensive machine learning problems. Despite the prolific literature, the question remains open whether cloud computing can provide HPC-competitive performance for a wide range
more &raquo; ... f scientific applications. The answer to this question is crucial in guiding the design of future systems and providing access to high-performance resources to a broadened community. Here we present a multi-level approach to identifying the performance gap between HPC and cloud computing and to isolate several variables that contribute to this gap by dividing our experiments into (i) hardware and system microbenchmarks and (ii) user applications. Our results show that today's high-end cloud computing can deliver HPC-like performance - at least at modest scales - not only for computationally intensive applications, but also for memory- and communication-intensive applications, thanks to the high-speed memory systems and interconnects and dedicated batch scheduling now available on some cloud platforms.
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