sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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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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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society