HAEC-SIM: A simulation framework for highly adaptive energy-efficient computing platforms

Research output: Contribution to journalConference articleContributedpeer-review

Abstract

This work presents a new trace-based parallel discrete event simulation framework designed for predicting the behavior of a novel computing platform running energy-aware parallel applications. Discrete event traces capture the runtime behavior of parallel applications on existing systems and form the basis for the simulation. The simulation framework processes the events of the input trace by applying simulation models that modify event properties. Thus, the output are again event traces that describe the predicted application behavior on the simulated target platform. Both input and simulated traces can be visualized and analyzed with established tools. The modular design of the framework enables the simulation of different aspects such as temporal performance and energy efficiency by applying distinct simulation models e.g.: (i) A performance model for communication that allows to evaluate the target communication topology and link properties. (ii) An energy model for computations that is based on measurements of current hardware. We showcase the potential of this simulation by simulating the execution of benchmark applications to explore design alternatives of highly adaptive and energy-efficient computing applications and platforms.

Details

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalEAI Endorsed Transactions on Energy Web
Volume16
Issue number8
Publication statusPublished - 2016
Peer-reviewedYes

Conference

TitleEighth EAI International Conference on Simulation Tools and Techniques
Abbreviated titleSIMUTOOLS 2015
Conference number8
Duration24 - 26 August 2015
Website
LocationRoyal Olympic Hotel
CityAthens
CountryGreece

External IDs

ORCID /0000-0002-5437-3887/work/154740495
Scopus 85002250270

Keywords

Sustainable Development Goals

Keywords

  • discrete event, energy modeling, HAEC, parallel simulation, performance modeling, trace-based modeling