Lookup NU author(s): Dr Andrey Mokhov,
Alessandro de Gennaro,
Dr Ghaith Tarawneh,
Professor Alex Yakovlev
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Springer Verlag, 2018.
For re-use rights please refer to the publisher's terms and conditions.
© Springer Nature Switzerland AG 2019. Graphs are important in many applications. However, their analysis on conventional computer architectures is generally inefficient because it involves highly irregular access to memory when traversing vertices and edges. As an example, when finding a path from a source vertex to a target one the performance is typically limited by the memory bottleneck whereas the actual computation is trivial. This paper presents a methodology for embedding graphs into silicon, where graph vertices become finite state machines communicating via the graph edges. With this approach many common graph analysis tasks can be performed by propagating signals through the physical graph and measuring signal propagation time using the on-chip clock distribution network. This eliminates the memory bottleneck and allows thousands of vertices to be processed in parallel. We present a domain-specific language for graph description and transformation, and demonstrate how it can be used to translate application graphs into an FPGA board, where they can be analyzed up to 1000× faster than on a conventional computer.
Author(s): Mokhov A, De Gennaro A, Tarawneh G, Wray J, Lukyanov G, Mileiko S, Scott J, Yakovlev A, Brown A
Editor(s): Daniel Große, Sara Vinco, Hiren Patel
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Languages, Design Methods, and Tools for Electronic System Design
Year of Conference: 2018
Online publication date: 20/12/2018
Acceptance date: 02/04/2016
Date deposited: 05/03/2019
Publisher: Springer Verlag
Library holdings: Search Newcastle University Library for this item
Series Title: Lecture Notes in Electrical Engineering