Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

conference paper · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · 2011

Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment

Jonathan Apodaca, Dalton Young, Luis Briceno, Jay C. Smith, Sudeep Pasricha, Anthony A. Maciejewski, Howard Jay Siegel, Shirish Bahirat, Bhavesh Khemka, Adrian Ramirez, Young Zou

Cited by 11Abstract and details only

Abstract

In a heterogeneous environment, uncertainty in system parameters may cause performance features to degrade considerably. It then becomes necessary to design a system that is robust. Robustness can be defined as the degree to which a system can function in the presence of inputs different from those assumed. In this research, we focus on the design of robust static resource allocation heuristics suitable for a heterogeneous compute cluster that minimize the energy required to complete a given workload. In this study, we mathematically model and simulate a heterogeneous computing system that is assumed part of a larger warehouse scale computing environment. Task execution times/energy consumption may vary significantly across different data sets in our heterogeneous cluster; therefore, the execution time of each task on each node is modeled as a random variable. A resource allocation is considered robust if the probability that all tasks complete by a system deadline is at least 90%. To minimize the energy consumption of a specific resource allocation, dynamic voltage frequency scaling (DVFS) is employed. However, other factors, such as system overhead (spent on fans, disks, memory, etc.) must also be mathematically modeled when considering minimization of energy consumption. In this research, we propose three different heuristics that employ DVFS to minimize energy consumed by a set of tasks in our heterogeneous computing system. Finally, a lower bound on energy consumption is provided to gauge the performance of our heuristics.

Cite this paper

APA 7

Apodaca, J., Young, D., Briceno, L., Smith, J. C., Pasricha, S., Maciejewski, A. A., Siegel, H. J., Bahirat, S., Khemka, B., Ramirez, A., & Zou, Y. (2011). Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment. IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), 3, 22–31. https://doi.org/10.1109/aiccsa.2011.6126617

MLA 9

Apodaca, Jonathan, et al. “Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment.” IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), vol. 3, 2011, pp. 22–31, https://doi.org/10.1109/aiccsa.2011.6126617.

Chicago

Apodaca, Jonathan, Dalton Young, Luis Briceno, Jay C. Smith, Sudeep Pasricha, Anthony A. Maciejewski, Howard Jay Siegel, et al. 2011. “Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment.” IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) 3: 22–31. https://doi.org/10.1109/aiccsa.2011.6126617.

Harvard

Apodaca, J. et al. (2011) ‘Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment’, IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), 3, pp. 22–31. Available at: https://doi.org/10.1109/aiccsa.2011.6126617.

BibTeX
@article{apodaca2011stochastically,
  title = {{Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment}},
  author = {Apodaca, Jonathan and Young, Dalton and Briceno, Luis and Smith, Jay C. and Pasricha, Sudeep and Maciejewski, Anthony A. and Siegel, Howard Jay and Bahirat, Shirish and Khemka, Bhavesh and Ramirez, Adrian and Zou, Young},
  journal = {IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)},
  volume = {3},
  pages = {22--31},
  year = {2011},
  doi = {10.1109/aiccsa.2011.6126617}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers