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A Hybrid and Secure Mechanism to Execute Parameter Survey Applications on Local and Public Cloud Resources

机译:在本地和公共云资源上执行参数调查应用程序的混合安全机制

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A parameter survey application (PSA) is a typical application running on high-performance computing (HPC) systems. A PSA consists of a lot of independent tasks with different input parameters that are executed in parallel on different CPU cores. Infrastructure-as-a-Service Cloud (IaaS Cloud) is expected to be used as an HPC infrastructure to run PSAs, and some reports have discussed hybrid execution mechanisms to utilize both local resources and IaaS Clouds. However, users still have security problems in running applications with confidential data on an IaaS Cloud. We propose a hybrid and secure execution mechanism to run PSAs utilizing both local computing resources with a batch scheduler and an IaaS Cloud. The proposed mechanism utilizes both local resources and IaaS Clouds to meet the deadline of user applications. We conducted experiments running a natural language processing application, which uses machine learning to detect abusive language on Internet bulletin board systems. The experimental results showed that the proposed mechanism effectively allocated resources and met the deadlines of the user application.
机译:参数调查应用程序(PSA)是在高性能计算(HPC)系统上运行的典型应用程序。 PSA由许多具有不同输入参数的独立任务组成,这些任务在不同CPU内核上并行执行。基础设施即服务云(IaaS Cloud)有望用作运行PSA的HPC基础设施,一些报告讨论了混合执行机制以利用本地资源和IaaS云。但是,用户在IaaS Cloud上运行带有机密数据的应用程序时仍然存在安全问题。我们提出了一种混合且安全的执行机制,以通过批处理调度程序和IaaS云使用本地计算资源来运行PSA。提议的机制同时利用本地资源和IaaS云来满足用户应用程序的截止日期。我们进行了运行自然语言处理应用程序的实验,该应用程序使用机器学习来检测Internet公告板上的辱骂性语言。实验结果表明,该机制有效地分配了资源,并满足了用户申请的截止日期。

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