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Dynamic Energy Aware Task Scheduling For Periodic Tasks Using Expected Execution Time Feedback, Sachin Pawaskar, Hesham Ali
Dynamic Energy Aware Task Scheduling For Periodic Tasks Using Expected Execution Time Feedback, Sachin Pawaskar, Hesham Ali
Computer Science Faculty Proceedings & Presentations
Scheduling dependent tasks is one of the most challenging problems in parallel and distributed systems. It is known to be computationally intractable in its general form as well as several restricted cases. An interesting application of scheduling is in the area of energy awareness for mobile battery operated devices where minimizing the energy utilized is the most important scheduling policy consideration. A number of heuristics have been developed for this consideration. In this paper, we study the scheduling problem for a particular battery model. In the proposed work, we show how to enhance a well know approach of accounting for …
Abstract Answer Set Solvers, Yuliya Lierler
Abstract Answer Set Solvers, Yuliya Lierler
Computer Science Faculty Proceedings & Presentations
Nieuwenhuis, Oliveras, and Tinelli showed how to describe enhancements of the Davis-Putnam-Logemann-Loveland algorithm using transition systems, instead of pseudocode. We design a similar framework for three algorithms that generate answer sets for logic programs: SMODELS, ASP-SAT with Backtracking, and a newly designed and implemented algorithm SUP. This approach to describing answer set solvers makes it easier to prove their correctness, to compare them, and to design new systems.
On The Tradeoff Between Speedup And Energy Consumption In High Performance Computing – A Bioinformatics Case Study, Sachin Pawaskar, Hesham Ali
On The Tradeoff Between Speedup And Energy Consumption In High Performance Computing – A Bioinformatics Case Study, Sachin Pawaskar, Hesham Ali
Computer Science Faculty Proceedings & Presentations
High Performance Computing has been very useful to researchers in the Bioinformatics, Medical and related fields. The bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Automated techniques such as DNA sequencers, DNA microarrays & others are continually growing the dataset that is stored in large public databases such as GenBank and Protein DataBank. Most methods used for analyzing genetic/protein data have been found to be extremely computationally intensive, providing motivation for the use of powerful computers or systems with high throughput characteristics. In this paper, we provide a …