Processor allocation in an N-cube multiprocessor using gray codes
IEEE Transactions on Computers
Complexity of scheduling parallel task systems
SIAM Journal on Discrete Mathematics
A Distributed Resource Management Mechanism for a Partitionable Multiprocessor System
IEEE Transactions on Computers
Microprocessor implementation of a parallel processor
ISCA '77 Proceedings of the 4th annual symposium on Computer architecture
Scheduling multiple queries on a parallel machine
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
A Hierarchical Approach to Parallel Multiquery Scheduling
IEEE Transactions on Parallel and Distributed Systems
Multi-dimensional resource scheduling for parallel queries
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An Efficient Dynamic Scheduling Algorithm for Multiprocessor Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Processor Allocation and Task Scheduling of Matrix Chain Products on Parallel Systems
IEEE Transactions on Parallel and Distributed Systems
The SegBus platform - architecture and communication mechanisms
Journal of Systems Architecture: the EUROMICRO Journal
Local search: is brute-force avoidable?
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Moldable parallel job scheduling using job efficiency: an iterative approach
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
An effective approximation algorithm for the Malleable Parallel Task Scheduling problem
Journal of Parallel and Distributed Computing
| Hi-index | 14.98 |
A partitionable multiprocessor system can form multiple partitions, each consisting of a controller and a varying number of processors. Given such a system and a set of tasks, each of which can be executed on partitions of varying sizes, the authors study the problem of choosing the partition sizes and a minimum completion time schedule for the execution of these tasks. They assume that the number of tasks to be scheduled on the system is no more than the maximum number of partitions that can be formed simultaneously by the system, and that parallelization of the tasks can achieve at most perfect speedup. They show this scheduling problem to be NP-hard, and present a polynomial time approximation algorithm for this problem. The authors derive a parameter dependent, asymptotically tight worst-case performance bound for the algorithm, and evaluate its average performance through simulation.