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Towards auction-based HPC computing in the cloud

Computer Technology and Application 2012年第7期3卷 499-509页

作者： Moussa Taifi Justin Y. Shi Abdallah Khreishah Computer and Information Sciences Department Temple University Philadelphia PA 19122 USA

cloud computing is expanding widely in the world of IT infrastructure. This is due partly to the cost-saving effect of economies of scale. Fair market conditions can in theory provide a healthy environment to reflect the most reasonable costs of computations. While fixed cloud pricing provides an attractive low entry barrier for compute-intensive applications, both the consumer and supplier of computing resources can see high efficiency for their investments by participating in auction-based exchanges. There are huge incentives for the cloud provider to offer auctioned resources. However, from the consumer perspective, using these resources is a sparsely discussed challenge. This paper reports a methodology and framework designed to address the challenges of using HPC （High Performance computing） applications on auction-based cloud clusters. The authors focus on HPC applications and describe a method for determining bid-aware checkpointing intervals. They extend a theoretical model for determining checkpoint intervals using statistical analysis of pricing histories. Also the latest developments in the SpotHPC framework are introduced which aim at facilitating the managed execution of real MPI applications on auction-based cloud environments. The authors use their model to simulate a set of algorithms with different computing and communication densities. The results show the complex interactions between optimal bidding strategies and parallel applications performance.

关键词： auction-based cloud computing fault tolerance cloud HPC （high performance computing）

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Banking on Decoupling: Budget-driven Sustainability for HPC Applications on EC2 Spot Instances

Banking on Decoupling: Budget-driven Sustainability for HPC ...

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31st IEEE International Symposium on Reliable Distributed Systems (SRDS)

作者： Taifi, Moussa Temple Univ Comp & Informat Sci Dept Philadelphia PA 19122 USA

ISBN: (纸本)9780769547848;9781467323970

cloud providers are auctioning their excess capacity using dynamically priced virtual instances. These spot instances provide significant savings compared to on-demand or fixed price instances. The users willing to use these resources are asked to provide a maximum bid price per hour, and the cloud provider runs the instances as long as the market price is below the user's bid price. By using such resources, the users are exposed explicitly to failures and need to adapt their applications to provide some level of fault tolerance. In this paper we expose the effect of bidding in the case of virtual HPC clusters composed of spot instances. We describe the interesting effect of uniform versus non-uniform bidding, in terms of failure rate and failure model. We propose an initial attempt to deal with the problem of predicting the runtime of a parallel application under various bidding strategies and various system parameters. We describe the relationship between bidding strategies and programming models. We build a preliminary optimization model that uses real price traces from Amazon Web Services as inputs, as well as instrumented values related to the processing and network capacities of clusters instances on the EC2 services. Our results show preliminary insights into the relationship between non-uniform bidding and application scaling strategies.

关键词： Spot Instances cloud-based Fault Tolerance cloud virtual clusters auction-based cloud computing Decoupling Parallel Programming Models Cost-aware Optimization models

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