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Record W4251343752 · doi:10.1109/eurdac.1992.246230

Routing algorithms for multi-chip modules

2003· article· en· W4251343752 on OpenAlexaff
Jens Lienig, K. Thulasiraman, M.N.S. Swamy

Bibliographic record

VenueProceedings EURO-DAC '92: European Design Automation Conference · 2003
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceStatic routingRouting (electronic design automation)Link-state routing protocolEqual-cost multi-path routingPolicy-based routingPlacementMultipath routingDynamic Source RoutingDestination-Sequenced Distance Vector routingAlgorithmChannel (broadcasting)Distributed computingComputer networkPhysical designRouting protocolEmbedded systemCircuit design

Abstract

fetched live from OpenAlex

Routing algorithms for multi-chip modules are presented. Two routing strategies, a channel routing and a grid-based routing, are discussed. The channel routing enables the designer to examine an effective routing during the placement phase. The grid-based routing calculates the net ordering with a new cost function and includes an effective rip-up and reroute procedure. The routing results of three different multichip modules are presented. Experimental results show that there is no direct correlation between the routing results of the channel algorithm and the grid-based one. It is concluded that channel routing is preferable only if the placement structure enables the generation of regular channels. In all other cases the grid-based algorithm is more effective using the channel routing just as a fast placement estimation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.090
GPT teacher head0.267
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2003
Admission routes1
Has abstractyes

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