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



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