Computer-aided design of VLSI circuits

Newton, A.R.

doi:10.1109/proc.1981.12160

Cited by 25 publications

(4 citation statements)

References 70 publications

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“…In parallel, his interests evolved to cover all branches of EDA [3]. His main technical contributions in this period were in the field of CAD frameworks where he spearheaded the development of unified databases and graphical user-interfaces for the design of electronic circuits.…”

Section: Richard: the Man And His Historymentioning

confidence: 99%

Remembering Richard [Obituary, Richard A.Newton]

Sangiovanni-Vincentelli

2007

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Section: Richard: the Man And His Historymentioning

confidence: 99%

Remembering Richard [Obituary, Richard A.Newton]

Sangiovanni-Vincentelli

2007

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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“…Verification in this model is achieved by first generating another level i+l design object through inverse mapping and then by an equivalence test of the two level i+l object descriptions. For example, CVS (Connectivity Verification System) was one of the earliest systems built reflecting this approach [NeVi86]. After the transistor-level design object has been transformed to a corresponding design object at the layout level, CVS extracts from the layout description another transistor-level design objecL This second version is compared with the original design object for connectivity equivalence.…”

Section: The Transformation Processmentioning

confidence: 99%

“…The major advantage of this approach is its potential for tremendous savings in simulation time. Time savings of orders of magnitudes at certain levels have been reported [NeVi86]. The feasibility of this approach clearly depends on the existence of the inverse mapping and a canonical representation of a design object.…”

Section: The Transformation Processmentioning

confidence: 99%

ASIC System Design with VHDL: A Paradigm

Leung¹,

Shanblatt²

1989

The Kluwer International Series in Engineering and Computer Science

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Logic Minimization Algorithms jor VLSI Synthesis. R.K. Brayton, 0.0. Hachtel, C.T. McMullen, and A.L. Sangiovanni-Vincentelli. ISBN 0-89838-164-9. Adaptive Filters: Structures, Algorithms, and Applications. M.L. Honig and D.O. Messerschmitt. ISBN 0-89838-163-0. Introduction to VLSI Silicon Devices: Physics, Technology and Characterization. B. El-Kareh and R.I. Bombard. ISBN 0-89838-210-6. Latchup in CMOS Technology: The Problem and Its Cure. R.R. Troutman. ISBN 0-89838-215-7. Digital CMOS Circuit Design. M. Annaratone. ISBN 0-89838-224-6. The Bounding Approach to VLSI Circuit Simulation. C.A. Zukowski. ISBN 0-89838-176-2. Multi-Level Simulationjor VLSI Design. D.O. Hill and D.R. Coelho. ISBN 0-89838-184-3. RelQXlltion Techniques jor the Simulation oj VLSI Circuits. 1. White and A. Sangiovanni-Vincentelli. ISBN 0-89838-186-X. VLSI CAD Tools and Applications. W. Fichtner and M. Morf, editors. ISBN 0-89838-193-2. A VLSI Architecturejor Concurrent Data Structures. W.l. Dally. ISBN 0-89838-235-1. Yield Simulation jor Integrated Circuits. D.M.H. Walker. ISBN 0-89838-244-0.

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“…It is also more prone to be influenced by high order effects and nonidealities (distortion, parasitic interference, noise, etc.). This puts pressure on circuit designers that must be experienced and skilled to understand the design tradeoffs and conflicting performance requirements that affect their design [8], [9]. As a consequence, even though the majority of the transistors in typical mixed electronic systems are used in their digital portions, analog circuit design is often a bottleneck (this is true in many systems on chip (SOCs) [10]).…”

Section: Introductionmentioning

confidence: 99%

Causal Information Prediction for Analog Circuit Design Using Variable Selection Methods Based on Machine Learning

Abuelnasr

Amer

Ragab

et al. 2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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This paper proposes a methodology based on machine learning to find apparent causal relations between performance targets and design variables in analog circuits. Diversified filtering and wrapping variable selection algorithms are utilized to construct a causal graph that identifies the major circuit design parameters that can be used to optimize the performance of analog circuits. Based on the constructed causal graph, a sequence of design procedures can be extracted and followed to optimize the performance of a design. The proposed methodology is validated using a two-stage op-amp. The obtained causal graph agrees with analytical design equations published in the literature for the selected two-stage op-amp. The results also show that the proposed methodology can accelerate the circuit design process and effectively help designers understand the reasoning behind different design decisions.

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Computer-aided design of VLSI circuits

Cited by 25 publications

References 70 publications

Remembering Richard [Obituary, Richard A.Newton]

Remembering Richard [Obituary, Richard A.Newton]

ASIC System Design with VHDL: A Paradigm

Causal Information Prediction for Analog Circuit Design Using Variable Selection Methods Based on Machine Learning

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