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Record W2124752818 · doi:10.1109/tc.2003.1159751

General models and a reduction design technique for FPGA switch box designs

2003· article· en· W2124752818 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Computers · 2003
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of LethbridgeUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceRouting (electronic design automation)Reduction (mathematics)Field-programmable gate arraySet (abstract data type)Topology (electrical circuits)Embedded systemMathematicsCombinatorics

Abstract

fetched live from OpenAlex

An FPGA switch box is said to be hyper-universal if it is detailed-routable for any set of multipin nets specifying a routing requirement over the switch box. Comparing with the known "universal switch modules", where only 2-pin nets are considered, the hyper-universal switch box model is more general and powerful. This paper studies the generic problem and proposes a systematic designing methodology for hyper-universal (k, W)-switch boxes, where k is the number of sides and W is the number of terminals on each side. We formulate this hyper-universal (k, W)-switch box design problem as a k-parfite graph design problem and propose an efficient reduction design technique. Applying this technique, we can design hyper-universal (k, W)-switch boxes with low O(W) switches for any fixed k. For illustration, we provide optimum hyper-universal (2, W) and (3, W)-switch boxes and a hyper-universal (4, W)-switch box with switch number quite close to the lower bound 6W, which is used in a well-known commercial design without hyper-universal routability. We also conclude that the proposed reduction method can yield an efficient detailed routing algorithm for any given routing requirement as well.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.595
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.243
Teacher spread0.199 · 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