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Cost-Benefit Analysis of Public Clouds for Offloading In-House HPC Jobs

机译：公共云用于卸载内部HPC作业的成本效益分析

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摘要

The Supercomputing Education and Research Centre (SERC) at the Indian Institute of Science (IISc), located in the South East Asian Region, has been providing state-of-the-art services and support for High Performance Computing (HPC) for the academic users of the institute since 1990. This centre, facilitates OpenMP, MPI, CUDA and OpenCL based HPC jobs for academic research. To augment or support the existing demand for compute intensive, tightly coupled HPC workloads in the institute, it was desirable to explore cloud based HPC services. This study is a comparative cost-benefit analysis of the in-house compute facility at SERC with that of the commercial cloud providers like Amazon, Google Cloud, Microsoft Azure and Sabalcore. The Total Cost of Ownership (TCO) of SahasraT (the in-house supercomputer) is computed and used to identify the cost of running a small job for 24 hours on the in-house facility. This is then compared with the estimated cost of running the same job on comparative cloud instances. Several research papers that provide a detailed evaluation of HPC on the cloud with performance benchmarks and the comparison to in-house HPC facilities, were studied. These references have been used to compare performance of compute instance in the public cloud to the performance of HPC at SahasraT. The results obtained in this study, advocate that current cloud platforms are expensive in both cost and performance as compared to the in-house facility at SERC.
机译：位于东南亚地区的印度科学研究所（IISc）的超级计算教育和研究中心（SERC）一直在为学术界提供最新的服务和对高性能计算（HPC）的支持。自1990年以来一直是该研究所的用户。该中心为基于OpenMP，MPI，CUDA和OpenCL的HPC工作提供便利，以进行学术研究。为了增加或支持研究所中对计算密集，紧密耦合的HPC工作负载的现有需求，需要探索基于云的HPC服务。这项研究是对SERC内部计算设施与商业云提供商（如Amazon，Google Cloud，Microsoft Azure和Sabalcore）进行的成本效益比较分析。计算SahasraT（内部超级计算机）的总拥有成本（TCO），并将其用于识别在内部设施上进行24小时小工作的成本。然后将其与在比较云实例上运行相同作业的估计成本进行比较。研究了几篇提供性能基准并与内部HPC设施进行比较的详细评估云上HPC的研究论文。这些参考已用于将公共云中计算实例的性能与SahasraT上的HPC的性能进行比较。这项研究获得的结果表明，与SERC的内部设施相比，当前的云平台在成本和性能上都是昂贵的。

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