Mapping filtering streaming applications with communication costs
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Computing the throughput of probabilistic and replicated streaming applications
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
International Journal of High Performance Computing Applications
Proceedings of the 44th Annual Simulation Symposium
Proceedings of the 45th Annual Simulation Symposium
Proceedings of the 46th Annual Simulation Symposium
Distributed workflow mapping algorithm for maximized reliability under end-to-end delay constraint
The Journal of Supercomputing
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Next-generation computation-intensive applications in various fields of science and engineering feature large-scale computing workflows with complex structures that are often modeled as directed acyclic graphs. Supporting such task graphs and optimizing their end-to-end network performances in heterogeneous computing environments are critical to the success of these distributed applications that require fast response. We construct analytical models for computing modules, network nodes, and communication links to estimate data processing and transport overhead, and formulate the task graph mapping with node reuse and resource sharing for minimum end-to-end delay as an NP-complete optimization problem. We propose a heuristic approach to this problem that recursively computes and maps the critical path to the network using a dynamic programming-based procedure. The performance superiority of the proposed approach is justified by an extensive set of experiments on simulated data sets in comparison with existing methods.