J
Jeanine Cook
Researcher at Sandia National Laboratories
Publications - 53
Citations - 722
Jeanine Cook is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Proxy (statistics) & Cache. The author has an hindex of 11, co-authored 53 publications receiving 653 citations. Previous affiliations of Jeanine Cook include New Mexico State University & Los Alamos National Laboratory.
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Journal ArticleDOI
The structural simulation toolkit
Arun Rodrigues,Karl Scott Hemmert,Brian W. Barrett,C. Kersey,Ron A. Oldfield,M. Weston,R. Risen,Jeanine Cook,Paul Rosenfeld,Elliott Cooper-Balis,Bruce Jacob +10 more
TL;DR: The Structural Simulation Toolkit (SST) as discussed by the authors is an open, modular, parallel, multi-criteria, multiscale simulation framework for HPC systems that includes a number of processor, memory, and network models.
Proceedings ArticleDOI
Abstract machine models and proxy architectures for exascale computing
J. A. Ang,Richard F. Barrett,R.E. Benner,Daniel Burke,Che Ting Chan,Jeanine Cook,Dave Donofrio,Simon D. Hammond,Karl Scott Hemmert,Suzanne M. Kelly,H. Le,Vitus J. Leung,David Resnick,Arun Rodrigues,John Shalf,Dylan Stark,Didem Unat,Nicholas J. Wright +17 more
TL;DR: A set of abstract machine models are presented and applied to one of these models to demonstrate how a proxy architecture can enable a more concrete exploration of how well application codes map onto future architectures.
Proceedings ArticleDOI
The Performance Implication of Task Size for Applications on the HPX Runtime System
TL;DR: This paper characterize task scheduling overheads and show metrics to determine optimal task size, the first step toward the goal of dynamically adapting task size to optimize parallel performance.
Proceedings ArticleDOI
Improved estimation for software multiplexing of performance counters
W. Mathur,Jeanine Cook +1 more
TL;DR: This work quantifies the estimation error of the event-counts in the multiplexed mode, which indicates that as many as 42% of sampled intervals are estimated with error greater than 10%, and proposes new estimation algorithms that result in an accuracy improvement of up to 40%.
Journal ArticleDOI
Using Performance-Power Modeling to Improve Energy Efficiency of HPC Applications
TL;DR: A proposed modeling framework can be used with an earthquake simulation and an aerospace application and reduces energy consumption by up to 48.65 percent and 30.67 percent, respectively.