TY - JOUR
T1 - Dynamic resource management in energy constrained heterogeneous computing systems using voltage scaling
AU - Kim, Jong Kook
AU - Siegel, Howard Jay
AU - Maciejewski, Anthony A.
AU - Eigenmann, Rudolf
N1 - Funding Information:
The authors thank Sameer Shivle, Prasanna Sugavanam, and T.N. Vijaykumar for their valuable comments. A preliminary version of portions of this material was presented at the 19th International Parallel and Distributed Processing Symposium. This research was supported by the US National Science Foundation under Grant CNS-0615170, the Colorado State University George T. Abell Endowment, and the Korea University Grant. Submitted to the IEEE TPDS Special Section on Power-Aware Parallel and Distributed Systems in October 2007.
Funding Information:
Rudolf Eigenmann received the PhD degree in electrical engineering/computer science from ETH Zurich, Switzerland, in 1988. He is a professor in the School of Electrical and Compu-ter Engineering, Purdue University. He is also the interim director of the Computing Research Institute and associate director of Purdue’s Cyber Center. His research interests include optimizing compilers, programming methodologies and tools, performance evaluation for high-performance computers, and Internet sharing technology. From 1988 to 1995, he worked as a research scientist at the Center for Supercomputing Research and Development, University of Illinois, Urbana Champaign, where he also served as the leader of the Center’s Cedar Fortran compiler group. He has published his work in more than 100 papers in international conference and workshop proceedings and journals. He serves on the editorial boards of the International Journal of Parallel Programming, the IEEE Transaction on Parallel and Distributed Systems Journal, and the IEEE Computing in Science and Engineering Magazine. He has served as the chairman of computer engineering at Purdue’s School of ECE and as the chairman of the High-Performance Group, Standard Performance Evaluation Corp. (SPEC). He has also been the general chair and program chair of such conferences as the ACM Symposium Principles and Practice of Parallel Programming, the International Conference on Parallel Processing, the Workshop on Languages and Compilers for High-Performance Computing, and the Workshop on High-Level Interfaces for Parallel Systems. He is the recipient of a 1997 US National Science Foundation CAREER Award. For more information, please visit http://www.ece.purdue.edu/~eigenman. He is a senior member of the IEEE.
PY - 2008
Y1 - 2008
N2 - An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.
AB - An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.
KW - Ad hoc
KW - Distributed heterogeneous computing
KW - Dynamic resource allocation/management
KW - Dynamic voltage scaling
KW - Energy-aware computing
KW - Task priorities and deadlines
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U2 - 10.1109/TPDS.2008.113
DO - 10.1109/TPDS.2008.113
M3 - Article
AN - SCOPUS:54249165363
VL - 19
SP - 1445
EP - 1457
JO - IEEE Transactions on Parallel and Distributed Systems
JF - IEEE Transactions on Parallel and Distributed Systems
SN - 1045-9219
IS - 11
ER -