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Record W3036728738 · doi:10.1109/tcad.2020.3003906

A Design Framework for Invertible Logic

2020· article· en· W3036728738 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsMcGill University
FundersPrecursory Research for Embryonic Science and TechnologyMinistry of Education, Culture, Sports, Science and TechnologyCanon Medical Systems Corporation
KeywordsSystemCComputer scienceLogic synthesisInvertible matrixStochastic computingLogic familySequential logicField-programmable gate arrayProbabilistic logicDigital electronicsTheoretical computer scienceLogic gateComputer engineeringComputer architectureElectronic circuitAlgorithmParallel computingEmbedded systemMathematicsEngineeringComputation

Abstract

fetched live from OpenAlex

Invertible logic using a probabilistic magnetoresistive device model has been recently presented that can compute functions in bidirectional ways and solve several problems quickly, such as factorization and combinational optimization. In this article, we present a design framework for invertible logic circuits. Our approach makes use of linear programming to create a Hamiltonian library with the minimum number of nodes for small invertible-logic functions. In addition, as the device model is approximated based on stochastic computing in synthesizable SystemVerilog, a faster simulation using the compiled SystemC binary is realized than a conventional SPICE-level simulation and is verified using field-programmable gate array (FPGA) as prototyping. Using our design framework, several invertible-logic circuits are designed and emulated (verified) in SystemC, exhibiting five order-of-magnitude faster simulation than conventional work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.234
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it