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Record W2024174517 · doi:10.1145/2499625.2499627

Towards development of an analytical model relating FPGA architecture parameters to routability

2013· article· en· W2024174517 on OpenAlex
Joydip Das, Steven J. E. Wilton

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

VenueACM Transactions on Reconfigurable Technology and Systems · 2013
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsField-programmable gate arrayRouterComputer scienceLogic blockBlock (permutation group theory)Routing (electronic design automation)Embedded systemFPGA prototypeComputer architectureCADDesign flowParallel computingComputer hardwareEngineeringEngineering drawingComputer network

Abstract

fetched live from OpenAlex

We present an analytical model relating FPGA architectural parameters to the routability of the FPGA. The inputs to the model include the channel width and the connection and the switch block flexibilities. The output is an estimate of the proportion of nets in a large circuit that can be expected to be successfully routed on the FPGA. We assume that the circuit is routed to the FPGA using a single-step combined global/detailed router. We show that the model correctly predicts routability trends. We also present an example application to demonstrate that this model may be a valuable tool for FPGA architects. When combined with the earlier works on analytical modeling, our model can be used to quickly predict the routability without going through any stage of an expensive CAD flow. We envisage that this model will benefit FPGA architecture designers and vendors to quickly evaluate FPGA routing fabrics.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.026
GPT teacher head0.243
Teacher spread0.218 · 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