H
Howard Jay Siegel
Researcher at Colorado State University
Publications - 409
Citations - 12900
Howard Jay Siegel is an academic researcher from Colorado State University. The author has contributed to research in topics: Heuristics & Symmetric multiprocessor system. The author has an hindex of 53, co-authored 408 publications receiving 12512 citations. Previous affiliations of Howard Jay Siegel include New York University & University of Illinois at Chicago.
Papers
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Journal ArticleDOI
A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems
Tracy D. Braun,Howard Jay Siegel,N.B. Beck,Ladislau Bölöni,Muthucumaru Maheswaran,Albert Reuther,James Patrick Robertson,Mitchell D. Theys,Bin Yao,Debra Hensgen,Richard F. Freund +10 more
TL;DR: It is shown that for the cases studied here, the relatively simple Min?min heuristic performs well in comparison to the other techniques, and one even basis for comparison and insights into circumstances where one technique will out-perform another.
Journal ArticleDOI
Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems
TL;DR: Three new heuristics, one for batch mode and two for immediate mode, are introduced as part of this research, revealing that the choice of which dynamic mapping heuristic to use in a given heterogeneous environment depends on parameters such as the structure of the heterogeneity among tasks and machines and the arrival rate of the tasks.
Book
Interconnection networks for large-scale parallel processing: theory and case studies (2nd ed.)
TL;DR: This book presents the theoretical basis and a number of case studies that demonstrate how the construction of an interconnection network to provide interprocessor communications is done.
Journal ArticleDOI
Task Matching and Scheduling in Heterogeneous Computing Environments Using a Genetic-Algorithm-Based Approach
TL;DR: Simulation results for larger-sized problems showed that this genetic-algorithm-based approach outperformed two nonevolutionary heuristics and a random search.
Proceedings ArticleDOI
Scheduling resources in multi-user, heterogeneous, computing environments with SmartNet
Richard F. Freund,Michael Gherrity,S. Ambrosius,M. Campbell,M. Halderman,Debra Hensgen,Elaine G. Keith,T. Kidd,M. Kussow,J.D. Lima,Francesca Mirabile,L. Moore,B. Rust,Howard Jay Siegel +13 more
TL;DR: The SmartNet resource scheduling system is described and compared to two different resource allocation strategies: load balancing and user directed assignment, and results indicate that, for the computer environments simulated, SmartNet outperforms both load balancingand user directed assignments, based on the maximum time users must wait for their tasks to finish.