Research Article
HAEC-SIM: A Simulation Framework for Highly Adaptive Energy-Efficient Computing Platforms
@ARTICLE{10.4108/eai.24-8-2015.2261105, author={Mario Bielert and Florina Ciorba and Kim Feldhoff and Thomas Ilsche and Wolfgang Nagel}, title={HAEC-SIM: A Simulation Framework for Highly Adaptive Energy-Efficient Computing Platforms}, journal={EAI Endorsed Transactions on Energy Web}, volume={3}, number={8}, publisher={ACM}, journal_a={EW}, year={2015}, month={8}, keywords={haec, parallel simulation, discrete event, trace-based modeling, performance modeling, energy modeling}, doi={10.4108/eai.24-8-2015.2261105} }
- Mario Bielert
Florina Ciorba
Kim Feldhoff
Thomas Ilsche
Wolfgang Nagel
Year: 2015
HAEC-SIM: A Simulation Framework for Highly Adaptive Energy-Efficient Computing Platforms
EW
EAI
DOI: 10.4108/eai.24-8-2015.2261105
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 be- havior of parallel applications on existing systems and form the basis for the simulation. The simulation framework pro- cesses 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 estab- lished tools. The modular design of the framework enables the simulation of different aspects such as temporal perfor- mance 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 al- ternatives of highly adaptive and energy-efficient computing applications and platforms.
Copyright © 2015 M. Bielert et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.