Collaborative Research:Experimental-based Research on Effective Models of Parallel Application Execution Time, Power, and Resilience

The increasing scale and complexity of parallel systems present enormous challenges to parallel applications. One such challenge is the integration and balancing of execution time, power, and resilience for parallel applications. The MuMMI_R project seeks to advance the scientific understanding of the interdependence among power, execution time, and resilience for various application-system configurations. The broader impacts include training of undergraduate and graduate students and the participation in programs such as REUs, CREU, and DREU to increase the participation of students from underrepresented groups in the project.

This project aims to develop effective techniques for quantifying the complicated tradeoffs among execution time, power, and resilience, and to provide a tuning mechanism for user-defined metrics. The project consists of three research thrusts: (1) experimental study of different application-system configurations, (2) developing models for quantifying the interplay between runtime, power, and resilience, and (3) model-based analysis. The resulting framework, MuMMI_R, can provide valuable insights into application-system interactions and aid in the design of efficient parallel applications (with respect to execution time, power requirements, and resilience), runtime systems, and computer architectures. The key outcomes include technical papers, a user-level dynamic power capping library,  and a large amount of experiment data for the community. 

This is a collaborative project between two universities: University of Chicago and Illinois Institute of Technology.

Team Members

Key Publications
Software & Data Contact
  • Valerie Taylor (vtaylor AT anl DOT gov)
  • Zhiling Lan (lan AT iit DOT edu)

  • Acknowlegement:
    This project is supported by the US National Science Foundation (CCF-1618776 and CCF-1801856). Note: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.