Application-Agnostic Generation of Synthetic Task Graphs for Stream Computing Applications

In order to process massive amounts of streaming data in real time, high-performance computing systems and software platforms are being developed. However, the pool of available streaming applications is small and really large streaming applications are even more scarce. As such, there is a need for synthetic generators of task graphs for performance evaluation and comparative analysis of various algorithmic techniques and hardware parameters.

In this paper, we identify the key properties of stream-computing graphs that are shared by most (if not all) streaming graphs, irrespective of their specific application domain. We then propose a new approach to generate task graphs and show that the generated graphs satisfy the identified properties.

By: Deepak Ajwani; Shoukat Ali; John P. Morrison

Published in: RC25181 in 2011


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