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Poster: Reservation-Based I/O Performance Guarantee for MPI-IO Applications Using Shared Storage Systems

机译:海报:使用共享存储系统的MPI-IO应用程序基于预订的I / O性能保证

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While optimized collective I/O methods are proposed for MPI-IO implementations, a problem in concurrent use of the shared storage system is raised. In order to prevent performance degradation of parallel I/O due to such I/O conflict, we propose an advance reservation approach, including possible integration with existing batch scheduler on HPC clusters. In this work, we use Dynamic-CoMPI as a MPI-IO implementation and Papio as a shared storage system which implements parallel I/O and performance reservation. Then we have been developing the ADIO layer to connect these systems and to evaluate the benefits of the reservation-based performance isolation. Our prototype implementation, Dynamic-CoMPI/Papio, was evaluated using the MPI-IO Test benchmark and the BISP3D application. In our preliminary evaluation, total execution time increased 3~12% with the Dynamic-CoMPI/PVFS2 and 6~40% with the Dynamic-CoMPI/Lustre, under the situation where additional workload affected on MPI execution, however there was no obvious time increase with Dynamic-CoMPI/Papio.
机译:虽然针对MPI-IO实现提出了优化的集体I / O方法,但是在共享存储系统的并发使用中却出现了问题。为了防止由于此类I / O冲突而导致的并行I / O性能下降,我们提出了一种高级保留方法,包括可能与HPC群集上的现有批处理调度程序集成。在这项工作中,我们将Dynamic-CoMPI用作MPI-IO实现,并将Papio用作实现并行I / O和性能保留的共享存储系统。然后,我们一直在开发ADIO层以连接这些系统,并评估基于预留的性能隔离的好处。我们使用MPI-IO测试基准和BISP3D应用程序对我们的原型实现Dynamic-CoMPI / Papio进行了评估。在我们的初步评估中,在其他工作负载影响MPI执行的情况下,Dynamic-CoMPI / PVFS2的总执行时间增加了3〜12%,而Dynamic-CoMPI / Lustre的总执行时间增加了6〜40%,但是没有明显的时间与Dynamic-CoMPI / Papio一起增加。

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