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Provisioning Legacy Simulation Applications in Product Lifecycle Management via a Cloud Platform

机译：通过云平台提供产品生命周期管理中的遗留仿真应用

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摘要

Provisioning legacy simulation applications for Product Lifecycle Management (PLM) is very challenging. There are two key issues: (i) Hosting applications for simulation job executions. These legacy applications are developed in various platforms, usually monolithic, and may heavily consume system resources in the runtime. (ii) Input/output data storage. During the lifecycle of a project, huge amount of design data is generated by various design tools. When a design is completed, it needs to be validated by numerous simulation applications, which consequently create substantial amount of result data. Therefore, among others, the scalability in both system runtime resources and data storage is one of the biggest challenges. A generic cloud solution, which promises elastic scalability in both computation resources and data storage but lack of coordination between runtime resource allocation and data placement, is insufficient for supporting these legacy applications efficiently. In this paper, we share our experience on implementing a cloud solution that incorporates both scalable application hosting and usage-aware data placement into an integrated mechanism. With such a mechanism, our system can not only scale out according to workload, but also improve performance by increasing the possibility of local data access.
机译：提供产品生命周期管理（PLM）的供应传统仿真应用非常具有挑战性。有两个关键问题：（i）托管模拟作业执行的应用程序。这些遗留应用程序是在各种平台上开发的，通常是单片的，并且可以在运行时大量消耗系统资源。 （ii）输入/输出数据存储。在项目的生命周期期间，各种设计工具产生了大量的设计数据。当设计完成时，需要通过许多仿真应用程序验证，从而创建了大量的结果数据。因此，除了其他方面，系统运行时资源和数据存储的可扩展性是最大的挑战之一。通用云解决方案，它在计算资源和数据存储中承诺弹性可扩展性，但运行时资源分配和数据放置之间缺乏协调，不足以有效地支持这些遗留应用。在本文中，我们分享了我们在实现云解决方案的经验，该解决方案包括可扩展的应用程序托管和使用情况感知数据放置到集成机制中。通过这种机制，我们的系统不仅可以根据工作负载扩展，而且通过提高本地数据访问的可能性，还可以提高性能。

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