Computing the throughput of probabilistic and replicated streaming applications
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
A survey of pipelined workflow scheduling: Models and algorithms
ACM Computing Surveys (CSUR)
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In this paper, we focus on computing the throughput of replicated workflows. Given a streaming application whose dependence graph is a linear chain, and a mapping of this application onto a fully heterogeneous platform, how can we compute the optimal throughput, or equivalently the minimal period? The problem is easy when workflow stages are not replicated, i.e., assigned to a single processor: in that case the period is dictated by the critical hardware resource. But when stages are replicated, i.e., assigned to several processors, the problem gets surprisingly complicated, and we provide examples where the optimal period is larger than the largest cycle-time of any resource. We then show how to model the problem as a timed Petri net to compute the optimal period in the general case, and we provide a polynomial algorithm for the one-port communication model with overlap. Finally, we report comprehensive simulation results on the gap between the optimal period and the largest resource cycle-time.