Slack: maximizing performance under technological constraints
ISCA '02 Proceedings of the 29th annual international symposium on Computer architecture
Graph-partitioning based instruction scheduling for clustered processors
Proceedings of the 34th annual ACM/IEEE international symposium on Microarchitecture
Dynamic, Reliability-Driven Scheduling of Parallel Real-Time Jobs in Heterogeneous Systems
ICPP '02 Proceedings of the 2001 International Conference on Parallel Processing
Region-based hierarchical operation partitioning for multicluster processors
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
GridFlow: Workflow Management for Grid Computing
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Emerging Technologies for MultiCluster/Grid Computing
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
Mapping heterogeneous task graphs onto heterogeneous system graphs
HCW '97 Proceedings of the 6th Heterogeneous Computing Workshop (HCW '97)
Dynamic, Competitive Scheduling of Multiple DAGs in a Distributed Heterogeneous Environment
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Fast and Effective Task Scheduling in Heterogeneous Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Scheduling loosely connected task graphs
Journal of Computer and System Sciences
Dynamic Scheduling of Parallel Jobs with QoS Demands in Multiclusters and Grids
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
The impact of predictive inaccuracies on execution scheduling
Performance Evaluation - Performance modelling and evaluation of high-performance parallel and distributed systems
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Dynamic, capability-driven scheduling of DAG-based real-time jobs in heterogeneous clusters
International Journal of High Performance Computing and Networking
Queue waiting time aware dynamic workflow scheduling in multicluster environments
Journal of Computer Science and Technology
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Before an application modelled as a Directed Acyclic Graph (DAG) is executed on a heterogeneous system, a DAG mapping policy is often enacted. After mapping, the tasks (in the DAG-based application) to be executed at each computational resource are determined. The tasks are then sent to the corresponding resources, where they are orchestrated in the pre-designed pattern to complete the work. Most DAG mapping policies in the literature assume that each computational resource is a processing node of a single processor, i.e. the tasks mapped to a resource are to be run in sequence. Our studies demonstrate that if the resource is actually a cluster with multiple processing nodes, this assumption will cause a misperception in the tasks' execution time and execution order. This will disturb the pre-designed cooperation among tasks so that the expected performance cannot be achieved. In this paper, a DAG mapping algorithm is presented for multicluster architectures. Each constituent cluster in the multicluster is shared by background workload (from other users) and has its own independent local scheduler. The multicluster DAG mapping policy is based on theoretical analysis and its performance is evaluated through extensive experimental studies. The results show that compared with conventional DAG mapping policies, the new scheme that we present can significantly improve the scheduling performance of a DAG-based application in terms of the schedule length*.