AzureBench: Benchmarking the Storage Services of the Azure Cloud Platform

  • Authors:
  • Dinesh Agarwal;Sushil K. Prasad

  • Affiliations:
  • -;-

  • Venue:
  • IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
  • Year:
  • 2012

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Abstract

Cloud computing is becoming mainstream for High Performance Computing (HPC) application development over the last few years. However, even though many vendors have rolled out their commercial cloud infrastructures, the service offerings are usually only best-effort based, without any performance guarantees. Cloud computing effectively saves the eScience developer the hassles of resource provisioning but utilization of these resources will be questionable if it can not meet the performance expectations of deployed applications. Furthermore, in order to make application design choices for a particular cloud offering, an eScience developer needs to understand the performance capabilities of the underlying cloud platform. Among all clouds, the emerging Azure cloud from Microsoft remains a challenge for HPC program development both due to lack of its support for traditional parallel programming support such as MPI and map-reduce and due to its evolving APIs. To aid the HPC developers, we present an open-source benchmark suite, Azure Bench, for Windows Azure cloud platform. We report comprehensive performance analysis of Azure cloud platform's storage services which are its primary artifacts for inter-processor coordination and communication. We also report on how much scalability Azure platform affords using up to 100 processors and point out various bottlenecks in parallel access of storage services. The paper also has pointers to overcome the steep learning curve for HPC application development over Azure. We also provide an open-source generic application framework that can be a starting point for application development for bag-of-task applications over Azure.