sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 16-21, 2014

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Quantitatively Modeling Application Resiliency with the Data Vulnerability Factor

SESSION: Resilience

EVENT TYPE: Papers, Best Student Paper Finalists

TIME: 3:30PM - 4:00PM

SESSION CHAIR: Ananta Tiwari

AUTHOR(S):Li Yu, Dong Li, Sparsh Mittal, Jeffery S. Vetter

ROOM:393-94-95

ABSTRACT:

Strategies to improve the visible resilience of applications require the ability to distinguish vulnerability difference across application components and selectively apply protection. Hence, quantitatively modeling application vulnerability, as a method to capture vulnerability variance within the application, is critical to evaluate and improve system resilience. The tradition methods cannot effectively quantify vulnerability, because they lack a holist view to examine system resilience, and come with prohibitive evaluation costs. In this paper, we introduce a data-driven methodology to analyze application vulnerability based on a novel resilience metric, the data vulnerability factor (DVF). DVF integrates both application and specific hardware into the resilience analysis. To calculate DVF, we extend a performance modeling language to provide a fast modeling solution. Furthermore, we measure six representative computational kernels; we demonstrate the values of DVF by quantifying the impact of algorithm optimization on vulnerability and by quantifying the effectiveness of a hardware protection mechanism.

Chair/Author Details:

Ananta Tiwari (Chair) - PMaC Lab, SDSC

Li Yu - Illinois Institute of Technology

Dong Li - Oak Ridge National Laboratory

Sparsh Mittal - Oak Ridge National Laboratory

Jeffery S. Vetter - Oak Ridge National Laboratory

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society