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PanDA and RADICAL-Pilot Integration: Enabling the Pilot Paradigm on HPC Resources

机译:PanDA和RADICAL-Pilot集成:在HPC资源上启用Pilot范式

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PanDA executes millions of ATLAS jobs a month on Grid systems with more than 300,000 cores. Currently, PanDA is compatible only with few high-performance computing (HPC) resources due to different edge services and operational policies; does not implement the pilot paradigm on HPC; and does not dynamically optimize resource allocation among queues. We integrated the PanDA Harvester service and the RADICAL-Pilot (RP) system to overcome these limitations and enable the execution of ATLAS, Molecular Dy-namics and other workloads on HPC resources. This paper offer two main con-tributions: (1) introducing PanDA Harvester and RADICAL-Pilot, two systems independent developed to support high-throughput computing (HTC) on high-performance computing (HPC) infrastructures; (2) describing the integration between these two systems to produce a middleware component with unique functionalities, including the concurrent execution of heterogeneous workloads on the Titan OLCF machine. We integrated Harvester and RP by prototyping a Next Generation Executor (NGE) to expose RP capabilities and manage the execution of PanDA workloads. In this way, we minimized the reengineering of the two systems, allowing their integration while being in production.
机译:PanDA每月在拥有300,000多个核心的网格系统上执行数百万个ATLAS作业。目前,由于不同的边缘服务和操作策略,PanDA仅与很少的高性能计算(HPC)资源兼容。没有在HPC上实施试验范式;并且不会动态优化队列之间的资源分配。我们集成了PanDA Harvester服务和RADICAL-Pilot(RP)系统,以克服这些限制,并能够在HPC资源上执行ATLAS,分子动力学和其他工作负载。本文提供了两个主要的贡献:(1)介绍PanDA Harvester和RADICAL-Pilot,这两个系统是独立开发的,可以在高性能计算(HPC)基础结构上支持高吞吐量计算(HTC); (2)描述了这两个系统之间的集成,以产生具有独特功能的中间件组件,包括在Titan OLCF机器上并发执行异构工作负载。通过为下一代执行器(NGE)制作原型,我们集成了Harvester和RP,以展示RP功能并管理PanDA工作负载的执行。这样,我们最大程度地减少了两个系统的重新设计,使它们在生产时可以集成。

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