International Workshop on SRMPDS

Scheduling and Resource Management for Parallel and Distributed Systems

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The 15th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems will be held at the Kyoto Research Park (KRP), Kyoto, Japan, in conjunction with the ICPP’19 - 2019 International Conference on Parallel Processing.

Resource management and scheduling is a crucial task on large-scale computing systems. It plays an essential role in the optimization of resources usage. The goal of this workshop is to bring together researchers and practitioners working in the areas of resource scheduling and resource management to exchange and share their experiences, new ideas, and latest research results on all aspects of scheduling and resource management in parallel and distributed systems including Grids and Clouds.


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Events will be held on August 5th, Room A, at the Kyoto Research Park (KRP). The local guide is available here.

Start End Event
09:00 09:05 Opening Remarks
09:05 09:50 Keynote Presentation
CobaltV2: What would you do with a blank sheet of paper?
William(Bill) Allcock, Argonne National Laboratory
Abstract & Bio
09:50 10:40 Session I: Scheduling in Clouds
Session Chair: Zichuan Xu, Dalian University of Technology
09:50 10:15 Qiufen Xia, Luyao Bai, Weifa Liang, Zichuan Xu, Lin Yao, Lei Wang. QoS-Aware Proactive Data Replication for Big Data Analytics in Edge Clouds
10:15 10:40 Luan Teylo, Luciana Arantes, Pierre Sens, Lucia Maria de A. Drummond. A Hibernation Aware Dynamic Scheduler for Cloud Environments
10:40 11:00 Coffee break
11:00   Session II: Scheduling in HPC
Session Chair: Lúcia Drummond, , Fluminense Federal University
11:00 11:25 Hamza Djigal, Jun Feng, Jiamin Lu. Task Scheduling for Heterogeneous Computing using a Predict Cost Matrix
11:25 11:50 Mehmet Soysal, Marco Berghoff, Dalibor Klusacek, Achim Streit. On the Quality of Wall Time Estimates for Resource Allocation Prediction
11:50 12:15 Yan Baicheng, Yang Zhang, Xiao Limin, Zhou Yi, Wei Bing, Song Yao. LPMS: A Low-cost Topology-aware Process Mapping Method for Large-scale Parallel Applications on Shared HPC Systems
12:15 12:20 Closing SRMPDS’19 workshop and Announcing SRMPDS’20

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