Formalizing hardware/software interface specifications

Li, Juncao; Xie, Fei; Ball, Thomas; Levin, Vladimir; McGarvey, Con

doi:10.1109/ase.2011.6100048

Cited by 15 publications

(5 citation statements)

References 16 publications

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“…Achieving a transition to incorporating collective intelligence in parallel and distributed computing however will require comprehensive metrics for a GCI to use, regarding which models of logic, which models of cooperation, and which functional components implementing those models, are more "fit" at achieving each targeted outcome. This is a massive modeling effort that has yet to be even contemplated widely, though effort to model hardware semantically do exist [11].…”

Section: Discussionmentioning

confidence: 99%

General Collective Intelligence as a System for Facilitating Parallel and Distributed Computing

Williams¹

2022

Preprint

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A General Collective Intelligence or GCI is a hypothetical platform able to self-organize individuals or intelligent agents working on behalf of those individuals, into potentially massive networks of cooperation on a self-sustaining basis, where those networks might exponentially increase the complexity and duration of reasoning the group is able to execute. When applied to the computing processes that might be executed by each individual, the algorithm represented by GCI creates the potential to take any computing process that has been abstracted into a logical model (a model in which each component of logic might be implemented in a separate functional component), and to automatically search for and apply patterns of solution by which it might be possible to increase outcomes. Such patterns might involve distributing processing across multiple instances of those functional components, and scaling processing by increasing the instances of those functional components in series and in parallel, as well as ensuring this effort has more value than cost to performance so it is possible to sustain the effort at doing so, until computing outcomes are scaled as necessary to achieve a given target, or until returns from scaling diminish to the point that further investment in scaling is unproductive. This paper explores how such processes of cooperation might include all forms of parallel and distributed activity, how that cooperative activity might be abstracted into a logical model, and how GCI might facilitate parallel and distributed computing through that model.

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Section: Discussionmentioning

confidence: 99%

General Collective Intelligence as a System for Facilitating Parallel and Distributed Computing

Williams¹

2022

Preprint

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“…This can prevent some of the problems noted earlier. While there has been some work done on formal specification of HW/SW interfaces [10], [11], it has not yet matured enough to be widely adopted by the industry.…”

Section: Ronny Morad Ibm Research -Haifa Israelmentioning

confidence: 99%

Panel: Future SoC verification methodology: UVM evolution or revolution?

Drechsler¹,

Chevallaz²,

Fummi³

et al. 2014

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2014

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With increasing design complexity System on Chip (SoC) verification is becoming a more and more important and challenging aspect of the overall development process. The Universal Verification Methodology (UVM) is thereby a common solution to this problem; although it still keeps some problems unsolved. In this panel leading experts from industry (both users and vendors) and academy will discuss the future of SoC verification methodology.

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Section: Ronny Morad Ibm Research -Haifa Israelmentioning

confidence: 99%