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Record W4318224776 · doi:10.29292/jics.v17i3.648

Towards a Reference Place and Route Flow for Academic Research

2022· article· en· W4318224776 on OpenAlex
Tiago Augusto Fontana, Renan Netto, Sheiny Fabre Almeida, Erfan Aghaeekiasaraee, Laleh Behjat, José Luís Güntzel

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

VenueJournal of Integrated Circuits and Systems · 2022
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of Calgary
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsCONTESTComputer scienceRouting (electronic design automation)PlacementPhysical designConvergence (economics)Flow (mathematics)Work (physics)Closure (psychology)Network routingQuality (philosophy)Distributed computingComputer engineeringComputer networkCircuit designEmbedded systemMathematicsMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Due to the complexity of contemporary circuits, physical synthesis has become a crucial step for achieving design closure. The placement of cells direct impacts the routing solution. For example, a region with a high cell density can lead to pin access issues in detailed routing. Therefore, small inefficiencies in the placement solution can be boosted during routing, which has a negative impact on design quality and convergence. Unfortunately, most academic research works evaluate the results only in the target step without considering the complete place and route flows. In this work, we experimentally explored different flows built up from academic placers and routers to find which one leads to the best overall results so that researchers can use them as a reference. In order to evaluate those flows, we used the ISPD 2018 and ISPD 2019 CAD Contest benchmarks, which are the most realistic academic benchmarks available with placement and routing information. Considering the evaluator reports, no combination of tools achieved the best result for all circuits. Nevertheless, the flow Contest placement + CUGR + TritonRoute achieved the best results in fifteen out of twenty benchmarks.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.096
GPT teacher head0.322
Teacher spread0.226 · 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