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Record W2553967290

On Pin-to-wire Routing in FPGAs

2012· dissertation· en· W2553967290 on OpenAlexfundno aff
Niyati Shah

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsField-programmable gate arrayRouting (electronic design automation)EngineeringComputer scienceElectrical engineeringEmbedded system
DOInot available

Abstract

fetched live from OpenAlex

While FPGA interconnect networks were originally designed to connect logic block output pins to input pins, FPGA users and architects sometimes become motivated to create connections between pins and specific wires in the interconnect. These pin-to-wire connections are motivated by both a desire to employ routing-by-abutment, in modular, pre-laid out systems, and to make direct use of resources in the fabric itself. The goal of this work is to measure the difficulty of forming such pin-to-wire connections. We show that compared to a flat placement of the complete system, the routed wirelength and critical path delay increase by 6% and 15% respectively, and the router effort increases 3.5 times. We show that while pin-to-wire connections impose increased stress on the router, they can be used under some circumstances. We also measure the impact of increasing routing architecture flexibility on these results, and propose a low-cost enhancement to improve pin-to-wire routing.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.990

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 head0.014
GPT teacher head0.298
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2012
Admission routes1
Has abstractyes

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