Introduction to algorithms
Modeling the benefits of mixed data and task parallelism
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures
Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
IEEE Transactions on Parallel and Distributed Systems
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
A Low-Cost Approach towards Mixed Task and Data Parallel Scheduling
ICPP '02 Proceedings of the 2001 International Conference on Parallel Processing
Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Bi-criteria algorithm for scheduling jobs on cluster platforms
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
Critical Path and Area Based Scheduling of Parallel Task Graphs on Heterogeneous Platforms
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
An Integrated Approach for Processor Allocation and Scheduling of Mixed-Parallel Applications
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
A batch scheduler with high level components
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms
ISPDC '07 Proceedings of the Sixth International Symposium on Parallel and Distributed Computing
Precise and realistic utility functions for user-centric performance analysis of schedulers
Proceedings of the 16th international symposium on High performance distributed computing
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
SimGrid: A Generic Framework for Large-Scale Distributed Experiments
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Scheduling Parallel Task Graphs on (Almost) Homogeneous Multicluster Platforms
IEEE Transactions on Parallel and Distributed Systems
Scheduling mixed-parallel applications with advance reservations
Cluster Computing
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Scheduling multiple DAGs onto heterogeneous systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Workflow fairness control on online and non-clairvoyant distributed computing platforms
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
The Journal of Supercomputing
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Many scientific applications can be structured as parallel task graphs (PTGs), that is, graphs of data-parallel tasks. Adding data parallelism to a task-parallel application provides opportunities for higher performance and scalability, but poses additional scheduling challenges. In this paper, we study the off-line scheduling of multiple PTGs on a single, homogeneous cluster. The objective is to optimize performance without compromising fairness among the PTGs. We consider the range of previously proposed scheduling algorithms applicable to this problem, from both the applied and the theoretical literature, and we propose minor improvements when possible. Our main contribution is an extensive evaluation of these algorithms in simulation, using both synthetic and real-world application configurations, using two different metrics for performance and one metric for fairness. We identify a handful of algorithms that provide good trade-offs when considering all these metrics. The best algorithm overall is one that structures the schedule as a sequence of phases of increasing duration based on a makespan guarantee produced by an approximation algorithm.