3月22日:Yves Robert
发布时间:2018-03-15  阅读次数:2340

报告题目:Checkpointing Workflows for Fail-Stop Errors

人:Yves Robert  Professor

人:王长波教授

报告时间:2018322日(周四)13:30

报告地点:中北校区数学馆201报告厅

 

报告人简介:

    Yves Robert received the PhD degree from Institut National Polytechnique de Grenoble. He is currently a full professor in the Computer Science Laboratory LIP at ENS Lyon. He is the author of 7 books, 130 papers published in international journals, and 195 papers published in international conferences. He is the editor of 11 book proceedings and 13 journal special issues. He is the advisor of 26 PhD theses.

    His main research interests are scheduling techniques and resilient algorithms for large-scale platforms. Yves Robert served on many editorial boards, including IEEE TPDS. He was the program chair of HiPC'2006 in Bangalore, IPDPS'2008 in Miami, ISPDC'2009 in Lisbon, ICPP'2013 in Lyon and HiPC'2013 in Bangalore. He is a Fellow of the IEEE. He has been elected a Senior Member of Institut Universitaire de France in 2007 and renewed in 2012. He has been awarded the 2014 IEEE TCSC Award for Excellence in Scalable Computing. He holds a Visiting Scientist position at the University of Tennessee Knoxville since 2011.

报告摘要:

    We consider the problem of orchestrating the execution of workflow applications structured as Directed Acyclic Graphs (DAGs) on parallel computing platforms that are subject to fail-stop failures. The objective is to minimize expected overall execution time, ormakespan. A solution to this problem consists of a schedule of the Workflow tasks on the available processors and of a decision of which application data to checkpoint to stable storage, so as to mitigate the impact of processor failures.

    To address this challenge, we consider a restricted class of graphs, Minimal Series-Parallel Graphs (GSPGs), which is relevant to many real-world workflow applications. For this class of graphs, we propose a recursive list-scheduling algorithm that exploits the GSPG structure to assign sub-graphs to individual processors, and uses dynamic programming to decide how to checkpoint these sub-graphs. We assess the performance of our algorithm for production workflow configurations, comparing it to an approach in which all application data is check pointed and an approach in which no application data is check pointed. Results demonstrate that our algorithm outperforms both the former approach, because of lower checkpointing overhead, and the latter approach, because of better resilience to failures.

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