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Improving the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems with Eley

  • Orcun Yildiz
  • , Amelie Chi Zhou
  • , Shadi Ibrahim*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)

Abstract

Burst Buffer is an effective solution for reducing the data transfer time and the I/O interference in HPC systems. Extending Burst Buffers (BBs) to handle Big Data applications is challenging because BBs must account for the large data inputs of Big Data applications and the Quality-of-Service (QoS) of HPC applications—whichare considered as first-class citizens in HPC systems. Existing BBs focus on only intermediate data of Big Data applications and incur a high performance degradation of both Big Data and HPC applications. We present Eley, a burst buffer solution that helps to accelerate the performance of Big Data applications while guaranteeing the QoS of HPC applications. To achieve this goal, Eley embraces interference-aware prefetching technique that makes reading data input faster while introducing low interference for HPC applications. Evaluations using a wide range of Big Data and HPC applications demonstrate that Eley improves the performance of Big Data applications by up to 30% compared to existing BBs while maintaining the QoS of HPC applications.
Original languageEnglish
Pages (from-to)308-318
Number of pages11
JournalFuture Generation Computer Systems
Volume86
DOIs
Publication statusPublished - Sept 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

User-Defined Keywords

  • HPC
  • MapReduce
  • Big data
  • Parallel file systems
  • Burst buffers
  • Interference
  • Prefetch

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