Co-optimizing application partitioning and network topology for a reconfigurable interconnect

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Title: Co-optimizing application partitioning and network topology for a reconfigurable interconnect
Authors: Ajwani, Deepak
Hackett, Adam
Ali, Shoukat
Permanent link: http://hdl.handle.net/10197/9893
Date: Oct-2016
Online since: 2019-04-10T11:40:50Z
Abstract: To realize the full potential of a high-performance computing system with a reconfigurable interconnect, there is a need to design algorithms for computing a topology that will allow for a high-throughput load distribution, while simultaneously partitioning the computational task graph of the application for the computed topology. In this paper, we propose a new framework that exploits such reconfigurable interconnects to achieve these interdependent goals, i.e., to iteratively co-optimize the network topology configuration, application partitioning and network flow routing to maximize throughput for a given application. We also present a novel way of computing a high-throughput initial topology based on the structural properties of the application to seed our co-optimizing framework. We show the value of our approach on synthetic graphs that emulate the key characteristics of a class of stream computing applications that require high throughput. Our experiments show that the proposed technique is fast and computes high-quality partitions of such graphs for a broad range of hardware parameters that varies the bottleneck from computation to communication. Finally, we show how using a particular topology as a seed to our framework significantly reduces the time to compute the final topology.
Type of material: Journal Article
Publisher: Elsevier
Journal: Journal of Parallel and Distributed Computing
Volume: 96
Start page: 12
End page: 26
Copyright (published version): 2016 Elsevier
Keywords: Network configuration algorithmReconfigurable interconnect topologyOptical circuit switchTopology-aware graph partitioningStream-computing
DOI: 10.1016/j.jpdc.2016.04.010
Language: en
Status of Item: Peer reviewed
Appears in Collections:Computer Science Research Collection

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