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SCHEDULE: NOV 15-20, 2015
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Adaptive Data Placement for Staging-Based Coupled Scientific Workflows
SESSION: Resource Management
EVENT TYPE: Papers
EVENT TAG(S): System Software, Resource Management
TIME: 11:00AM - 11:30AM
SESSION CHAIR(S): Kim Cupps
AUTHOR(S):Qian Sun, Tong Jin, Melissa Romanus, Hoang Bui, Fan Zhang, Hongfeng Yu, Hemanth Kolla, Scott Klasky, Jacqueline Chen, Manish Parashar
ROOM:19AB
ABSTRACT:
Data staging and in-situ/in-transit data processing are emerging as attractive approaches for supporting extreme scale scientific workflows. These approaches accelerate the data-to-insight process by enabling runtime data sharing between coupled simulations and data analytics components of the workflow. However, the complex and dynamic data exchange patterns exhibited by the workflows coupled with various data access behaviors make efficient data placement within the staging area challenging. In this paper, we present an adaptive data placement approach to address these challenges. Our approach adapts data placement based on application-specific dynamic data access patterns, and applies access pattern-driven and location-aware mechanisms to reduce data access costs and to support efficient data sharing between multiple workflow components. We experimentally demonstrate the effectiveness of our approach on Titan using combustion-analyses workflow. The evaluation results show that our approach can effectively improve data access performance and the overall efficiency of coupled scientific workflows.
Chair/Author Details:
Kim Cupps (Chair) - Lawrence Livermore National Laboratory|
Qian Sun - Rutgers University
Tong Jin - Rutgers University
Melissa Romanus - Rutgers University
Hoang Bui - Rutgers University
Fan Zhang - Rutgers University
Hongfeng Yu - University of Nebraska-Lincoln
Hemanth Kolla - Sandia National Laboratories
Scott Klasky - Oak Ridge National Laboratory
Jacqueline Chen - Sandia National Laboratories
Manish Parashar - Rutgers University
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