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

机译:熊猫和激进的飞行员集成:在HPC资源中启用试点范例

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摘要

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每月在具有超过300,000个核心的网格系统上每月执行数百万个地图集。目前,由于边缘服务和操作策略,熊猫兼容少数高性能计算(HPC)资源;不在HPC上实施飞行员范式;并且不会动态优化队列之间的资源分配。我们集成了熊猫收割机服务和激进的飞行员(RP)系统,以克服这些限制,并使HPC资源的Atlas,分子Dy-Namics和其他工作负载能够执行。本文提供了两个主要的锥形─(1)介绍熊猫收割机和激进的飞行员,两个系统独立于高性能计算(HPC)基础设施,支持高通量计算(HTC); (2)描述这两个系统之间的集成,以产生具有唯一功能的中间件组件,包括在Titan OLCF机器上的异构工作负载的并发执行。我们通过原型设计了一个下一代执行器(NGE)来填写Harvester和RP来公开RP功能并管理熊猫工作负载的执行。通过这种方式,我们最小化了两个系统的再造,允许他们在生产中的集成。

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