Guest Editors' Introduction: Systolic Arrays-From Concept to Implementation

Fortes, J.A.B.; Wah,

doi:10.1109/mc.1987.1663616

Cited by 59 publications

(8 citation statements)

References 15 publications

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“…Applications in signal processing were pointed out: convolution, Finite Impulse Response (FIR) filter, and the Discrete Fourier Transform (DFT). General discussion and motivation for systolic arrays is given in another publication by Kung [9] and also Fortes and Wah [10]. Systematic treatment of the topic is provided in books by Robert [11], [12] and Evans [13].…”

Section: A Systolic Arraysmentioning

confidence: 99%

Virtual Systolic Array for QR Decomposition

Kurzak¹,

Łuszczek²,

Gates³

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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Abstract-Systolic arrays offer a very attractive, datacentric, execution model as an alternative to the von Neumann architecture. Hardware implementations of systolic arrays turned out not to be viable solutions in the past. This article shows how the systolic design principles can be applied to a software solution to deliver an algorithm with unprecedented strong scaling capabilities. Systolic array for the QR decomposition is developed and a virtualization layer is used for mapping of the algorithm to a large distributed memory system. Strong scaling properties are discovered, superior to existing solutions.

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Section: A Systolic Arraysmentioning

confidence: 99%

Virtual Systolic Array for QR Decomposition

Kurzak¹,

Łuszczek²,

Gates³

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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“…At each clock cycle, each processing element (PE) acquires data from the neighboring elements or the outside world, and feeds the neighboring elements in other directions with the data it has processed during the previous operation cycle [12].…”

Section: B Windowed Kriging Interpolation Fo R Natural Imagesmentioning

confidence: 99%

Parallel image transmission and compression Using windowed kriging interpolation

Panggabean

Tamer

Rønningen

2010

The 10th IEEE International Symposium on Signal Processing and Information Technology

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“…The linear system (12) and the relation (1 1) yield the solution of the original problem (I), (2). Each of these recurrences is decomposable into vector or matrix operations and linear systems of equations.…”

Section: Parallel Granularity Levelmentioning

confidence: 99%

Vlsi interconnection network for numerical solution of two point boundary value problems

Surós

Montagne

1989

International Journal of Computer Mathematics

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We present the bhooting parallel method implemented In systolic systems to solve Ordinary Dfferential Equat~ons. taking ad\antage of the fact that this method ma) be greatly parallelised and that it generates dispcx~:il o r triangular sparse matrices.The original problem is part~tioned Into subproblems whose individual size fit ava~lable qstolic netuork d~mensions. The netuork sizes depend on the order of the matrices used. The fitted technique i\ ;ipplied to halie the slze of sqstol~c netuorks used and therefore the sizes of n e t~o r k s are halved. We propose an organimtion x h e m e for the network interconnections.KEY K'ORDS: S)stollc arra). matrix computation. VLSI systems. solving ordinary differential equations. parallel algorithms.

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Guest Editors' Introduction: Systolic Arrays-From Concept to Implementation

Cited by 59 publications

References 15 publications

Virtual Systolic Array for QR Decomposition

Virtual Systolic Array for QR Decomposition

Parallel image transmission and compression Using windowed kriging interpolation

Vlsi interconnection network for numerical solution of two point boundary value problems

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