Performance Analysis of Asynchronous Circuits Using Markov Chains

Beerel, Peter A.; Xie, Aiguo

doi:10.1007/3-540-36190-1_9

Cited by 6 publications

(3 citation statements)

References 41 publications

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“…There are two main alternative approaches to model event timing: (i) using stochastic models (e.g. exponential delay), 27,28 or (ii) using minmax bounds. 29 The former approach provides metrics for averagecase throughput, which can be used both to derive early performance estimates and to guide performancedriven optimization.…”

Section: Sidebar Ii: Testingmentioning

confidence: 99%

Asynchronous Design—Part 2: Systems and Methodologies

Nowick

Singh

2015

IEEE Des. Test

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Section: Sidebar Ii: Testingmentioning

confidence: 99%

Asynchronous Design—Part 2: Systems and Methodologies

Nowick

Singh

2015

IEEE Des. Test

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“…For conditional circuits, Beerel et al [20] have proposed transforming such circuit to unconditional by unfolding their scenarios. Although this technique achieves a solution in a reasonable time, it may encounter state-explosion in largescale problems.…”

Section: Related Workmentioning

confidence: 99%

De-Elastisation: From Asynchronous Dataflows to Synchronous Circuits

Mamaghani

Garside

Edwards

2015

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2015

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Abstract-Asynchronous VLSI programming provides a flexible abstract formalism for concurrent systems but the is an issue for industrial adoption. The asynchronous design paradigm provides 'elasticity' enabling the system to tolerate delays in communication and computation but can impose a prohibitive communication overhead when applied at a fine-grained level. This paper proposes 'De-elastisation' in a CAD flow for asynchronous dataflow networks to improve the circuits' performance and area. To preserve the architectural advantages of asynchronous design (e.g. short cycles), circuits are classified into blocking and non-blocking loops which the De-elastisation scheme relies upon. The technique is incorporated in the Teak CAD flow. Experimental results on substantial case studies show significant performance and area improvements. This work shows 3× improvement for the first category of circuits, suitable for iterative realisations and DSP-like architectures and 4× for the second category which are suitable for concurrent realisations.

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“…In this paper we consider the use of Markov Chains as a simpler alternative to high fidelity simulations. Markov Chains have been applied to predict the performance of asynchronous circuits, communication networks, and other systems [2,3,4]. The proposed approach models critical aspects of the tracking process and provides fairly accurate estimates with low computational cost and complexity.…”

Section: Introductionmentioning

confidence: 99%

Markov chains for the prediction of tracking performance

Arambel

Antone

2007

SPIE Proceedings

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Highly accurate predictions of tracking performance usually require high fidelity Monte Carlo simulations that entail significant implementation time, run time, and complexity. In this paper we consider the use of Markov Chains as a simpler alternative that models critical aspects of the tracking process and provides reasonable estimates of tracking performance, while maintaining much lower cost and complexity. We describe a general procedure for Markov-Chain based performance prediction, and illustrate the use of this procedure in the context of an airborne system that employs a steerable EO/IR sensor to track single targets or multiple targets in non-overlapping fields of view. We discuss the effects of key model parameters, including measurement sampling rates, track termination, target occlusions, and missed detections. We also present plots of performance as a function of occlusion probability and target recognition probability that exemplify the use of the model.

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Performance Analysis of Asynchronous Circuits Using Markov Chains

Cited by 6 publications

References 41 publications

Asynchronous Design—Part 2: Systems and Methodologies

Asynchronous Design—Part 2: Systems and Methodologies

De-Elastisation: From Asynchronous Dataflows to Synchronous Circuits

Markov chains for the prediction of tracking performance

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