Kyle Tarplee's PhD Thesis Publications

Book Chapters:

  • PDF K. M. Tarplee, R. Friese, A. A. Maciejewski, and H. J. Siegel, "Efficient and Scalable Pareto Front Generation for Energy and Makespan in Heterogeneous Computing Systems," Recent Advances in Computational Optimization, Studies in Computational Intelligence Series, Vol. 580, edited by Stefka Fidanova, Springer, pp. 161-180, 2014.

    Serial Journal Articles:

  • PDF K. M. Tarplee, R. Friese, A. A. Maciejewski, H. J. Siegel, and E. K. P. Chong, "Energy and Makespan Tradeoffs in Heterogeneous Computing Systems using Efficient Linear Programming Techniques," IEEE Transactions on Parallel and Distributed Computing, Vol. 27, No. 6, pp. 1633-1646, June 2016.

  • PDF K. M. Tarplee, R. Friese, A. A. Maciejewski, and H. J. Siegel, "Scalable Linear Programming Based Resource Allocation Makespan Minimization in Heterogeneous Computing Systems," Journal of Parallel and Distributed Computing, Vol. 84, pp. 76-86, 2015.

  • PDF K. M. Tarplee, A. A. Maciejewski, and H. J. Siegel, "Robust Performance-Based Resource Provisioning Using a Steady State Model for Multi-Objective Stochastic Programming," IEEE Transactions on Cloud Computing, Vol. 7, No. 4, pp. 1068-1081, Oct-Dec. 2019.

    Conference Proceedings and Presentations:

  • PDF K. Tarplee, R. Friese, A. A. Maciejewski, and H. J. Siegel, "Efficient and Scalable Computation of the Energy and Makespan Pareto Front for Heterogeneous Computing Systems," Sixth Workshop on Computational Optimization (WCO'13), pp. 401-408, Krakow, Poland, Sept. 8-11, 2013. (Received “The 2013 Zdzislaw Pawlak Best Paper Award, by the Award Committee of the 8th Symposium on Advances in Artificial Intelligence and Applications")

  • PDF K. Tarplee, A. A. Maciejewski, and H. J. Siegel, "Energy-Aware Profit Maximizing Scheduling Algorithm for Heterogeneous Computing Systems," ExtremeGreen 2014: Extreme Green & Energy Efficiency in Large Scale Distributed Systems, in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 595-603, Chicago, IL, May 26-29, 2014.