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Record W3001830075 · doi:10.1109/les.2020.2966791

Configurable Logic Blocks and Memory Blocks for Beyond-CMOS FPGA-Based Embedded Systems

2020· article· en· W3001830075 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 Embedded Systems Letters · 2020
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of Saskatchewan
FundersMinistry of Electronics and Information technology
KeywordsComputer scienceField-programmable gate arrayCMOSElectronic circuitQuantum dot cellular automatonLogic gateEmbedded systemComputer architectureElectronic engineeringComputer hardwareElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Field programmable gate arrays (FPGAs)-based embedded systems are easy to implement, reconfigure, test, and validate. Configurable logic blocks (CLBs) and memory blocks are the building blocks of FPGA. The rising issues in CMOS fabrication at smaller nanometer levels has increased the need for beyond-CMOS technologies to build complex circuits at extremely smaller nanometer levels. Quantum-dot cellular automata (QCA) is a nascent beyond-CMOS nanotechnology technique to design low-power and high-performance digital circuits. In this letter, a layout strategy is proposed to design QCA circuits. Using the proposed strategy, novel and cost-efficient designs of CLBs and memory blocks are proposed. The proposed blocks can be used to develop FPGA architecture and FPGA-based embedded systems in QCA. The proposed circuits are cost effective and perform better than many state-of-the-art designs. Simulation and verification are done in QCADesigner using coherence vector simulation engine.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.027
GPT teacher head0.237
Teacher spread0.209 · 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