A Decoupled Execution Paradigm for Data-Intensive High-End Computing
Authors: Y. Chen, C. Chen, X.-H. Sun, W. D. Gropp, R. Thakur
Date: September, 2012
Venue: IEEE International Conference on Cluster Computing 2012 (Cluster'12), Beijing, China,
Type: Conference
Abstract
High-end computing (HEC) applications in critical areas of science and technology tend to be more and more data intensive. I/O has become a vital performance bottleneck of modern HEC practice. Conventional HEC execution paradigms, however, are computing-centric for computation intensive applications. They are designed to utilize memory and CPU performance and have inherent limitations in addressing the critical I/O bottleneck issues of HEC. In this study, we propose a decoupled execution paradigm (DEP) to address the challenging I/O bottleneck issues. DEP is the first paradigm enabling users to identify and handle data- intensive operations separately. It can significantly reduce costly data movement and is better than the existing execution paradigms for data-intensive applications. The initial experimental tests have confirmed its promising potential. Its data-centric architecture could have an impact in future HEC systems, programming models, and algorithms design development. and