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Advances in the design of the TOTEM neurochip

Lee, Peter, Lazzizzera, I., Zorat, Alessandro, Sartori, Alvise, Tecchiolli, G. (1997) Advances in the design of the TOTEM neurochip. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 389 (1-2). pp. 134-137. ISSN 0168-9002. (doi:10.1016/S0168-9002(97)00063-6) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:18154)

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The TOTEM neurochip has proved its viability as a system for real-time computation in HEP and space applications requiring high performance for event classification, data mining, and signal processing. ISA and VME boards integrating the TOTEM chip as a coprocessor have been made available to selected experimental groups which reported satisfactory results. This paper presents a new architectural solution yielding higher performance and reduced silicon area, The on-chip computational structures have been entirely redesigned to take advantage of a novel approach to number representation that, at the cost of a provably bounded approximation, leads to a much-reduced silicon area, lower power dissipation, and faster computation. This approach is validated by simulation results on experimental data, as presented in the paper.

Item Type: Article
DOI/Identification number: 10.1016/S0168-9002(97)00063-6
Additional information: Document Type: Proceedings Paper Conference Information: 5th International Workshop on Software Engineering, Neural Nets, Genetic Algorithms, Expert Systems, Symbolic Algebra and Automatic Calculations in Physics Research (AIHENP 96) Lausanne, Switzerland, Sep 02-06, 1996 UNIL; EPFL
Uncontrolled keywords: neural networks; processors; computer arithmetic; VLSI
Subjects: Q Science
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Q Science > QC Physics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: M.A. Ziai
Date Deposited: 20 Apr 2009 18:42 UTC
Last Modified: 16 Nov 2021 09:56 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Lee, Peter.

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