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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High Performance Data Analytics: Constructing Complex Analytic Workflows in an HPC Enclave

SESSION: Effective Application of HPC

EVENT TYPE: Exhibits, Exhibitor Forums

EVENT TAG(S): Effective Application of HPC

TIME: 11:30AM - 12:00PM

SESSION CHAIR(S): Dane Skow

Presenter(s):William Leinberger

ROOM:12AB

ABSTRACT:

The objectives of High Performance Data Analytic (HPDA) systems are to maintain the productivity of Open Source Big Data frameworks (e.g. Hadoop, Accumulo, Spark) while improving their performance through the use of High Performance Computing (HPC) systems technology. We describe our efforts to define an HPDA Workflow Architecture. This architecture is enabled by three key components. First, a visual workflow tool is required, to provide a parameterizeable and repeatable interface for multi-step analytics. Second, an extensible tool is needed to dynamically deploy a heterogeneous suite of open source frameworks to HPC resources in a just-in-time fashion. Finally, a memory-centric data grid is needed to maximize the performance of data transfers between analytic steps in the workflow. We conclude with a description of a prototype implementation of the workflow architecture, and show how it enables the construction of a complex multi-step graph analytic solution to a real-world Social Network Analysis problem.

Chair/Presenter Details:

Dane Skow (Chair) - University of Wyoming|

William Leinberger - General Dynamics

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