Eduardo Berrocal
Illinois Institute of Technology
8 Papers
24 Citations
Eduardo Berrocal is an academic researcher from Illinois Institute of Technology. The author has contributed to research in topics: Computer science & Fault tolerance. The author has an hindex of 6, co-authored 8 publications. Previous affiliations of Eduardo Berrocal include Toyota Technological Institute at Chicago.
Chat about Author
Papers
Lynx: a database and knowledge extraction engine for integrative medicine
Dinanath Sulakhe,Sandhya Balasubramanian,Bingqing Xie,Bo Feng,Andrew Taylor,Sheng Wang,Eduardo Berrocal,Utpal J. Dave,Jinbo Xu,Daniela Börnigen,T. Conrad Gilliam,Natalia Maltsev +11 more
TL;DR: Lynx is a web-based database and a knowledge extraction engine, supporting annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest.
39
Exploring void search for fault detection on extreme scale systems
Eduardo Berrocal,Li Yu,Sean Wallace,Michael E. Papka,Zhiling Lan +4 more
- 01 Sep 2014
TL;DR: A new approach for fault detection based on the Void Search (VS) algorithm, used primarily in astrophysics for finding areas of space that have a very low density of galaxies, which can detect almost all faults.
Topology mapping of irregular parallel applications on torus-connected supercomputers
TL;DR: This paper considers the topology mapping problem for torus-connected supercomputers as a discrete optimization problem in the geometric domain of a torus topology, and designs an analytical mapping algorithm, which uses numerical solvers to compute the mapping.
6
On Performance Resilient Scheduling for Scientific Workflows in HPC Systems with Constrained Storage Resources
Yang Wang,Wei Shi,Eduardo Berrocal +2 more
- 16 Jun 2015
TL;DR: The improved algorithm performance-resilience algorithm is called DDS+ to allow it to not only resolve the deadlock but also overcome the performance anomaly, a not yet investigated problem in previous studies.
1
An efficient silent data corruption detection method with error-feedback control and even sampling for HPC applications
Sheng Di,Eduardo Berrocal,Franck Cappello +2 more
- 04 May 2015
TL;DR: This work forms SDC detection as a runtime one-step-ahead prediction method, leveraging multiple linear prediction methods in order to improve the detection results, and proposes a spatial-data-based even-sampling method to minimize the detection overheads.