Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
Scheduling Multiprocessor Tasks to Minimize Schedule Length
IEEE Transactions on Computers
List scheduling of parallel tasks
Information Processing Letters
Generalised multiprocessor scheduling using optimal control
SPAA '91 Proceedings of the third annual ACM symposium on Parallel algorithms and architectures
A heuristic of scheduling parallel tasks and its analysis
SIAM Journal on Computing
Approximate algorithms scheduling parallelizable tasks
SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
Dynamic scheduling on parallel machines
Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Optimal Scheduling of Compute-Intensive Tasks on a Network of Workstations
IEEE Transactions on Parallel and Distributed Systems
The SPLASH-2 programs: characterization and methodological considerations
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
A Strip-Packing Algorithm with Absolute Performance Bound 2
SIAM Journal on Computing
Efficient approximation algorithms for scheduling malleable tasks
Proceedings of the eleventh annual ACM symposium on Parallel algorithms and architectures
Scheduling malleable and nonmalleable parallel tasks
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
A Near-Optimal Solution to a Two-Dimensional Cutting Stock Problem
Mathematics of Operations Research
IEEE Transactions on Computers
Approximation Algorithms for Scheduling Independent Malleable Tasks
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Preemptable Malleable Task Scheduling Problem
IEEE Transactions on Computers
A $\frac32$-Approximation Algorithm for Scheduling Independent Monotonic Malleable Tasks
SIAM Journal on Computing
Approximation Algorithms for Scheduling Parallel Jobs: Breaking the Approximation Ratio of 2
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
A fast 5/2-approximation algorithm for hierarchical scheduling
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
The solution algorithms for the multiprocessor scheduling with workspan criterion
Expert Systems with Applications: An International Journal
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The Malleable Parallel Task Scheduling problem (MPTS) is an extension of one of the most classic scheduling problems (P@?C"m"a"x). The only difference is that for MPTS, each task can be processed simultaneously by more than one processor. Such flexibility could dramatically reduce the makespan, but greatly increase the difficulty for solving the problem. By carefully analyzing some existing algorithms for MPTS, we find each of them suitable for some specific cases, but none is effective enough for all cases. Based on such observations, we introduce some optimization algorithms and improving techniques for MPTS, with their performance analyzed in theory. Combining these optimization algorithms and improving techniques gives rise to our novel scheduling algorithm OCM (Optimizations Combined for MPTS), a 2-approximation algorithm for MPTS. Extensive simulations on random datasets and SPLASH-2 benchmark reveal that for all cases, schedules produced by OCM have smaller makespans, compared with other existing algorithms.