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Record W4246053076 · doi:10.1109/dac.2001.935505

On optimum switch box designs for 2-D FPGAs

2002· article· en· W4246053076 on OpenAlexaff
Hongbing Fan, Jiping Liu, Yu‐Liang Wu

Bibliographic record

VenueProceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232) · 2002
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of LethbridgeUniversity of Victoria
Fundersnot available
KeywordsRouting (electronic design automation)Field-programmable gate arrayComputer scienceTopology (electrical circuits)Network topologyNetwork switchEmbedded systemElectrical engineeringComputer networkEngineering

Abstract

fetched live from OpenAlex

An FPGA switch box is said to be universal (hyper-universal) if it can detailed route all possible surrounding 2-pin (multi-pin) net topologies satisfying the global routing density constraints. A switch box is optimum if it is hyper-universal and the switches inside are minimum. It has been shown that if the net topology is restricted to 2-pin nets, then a 2-D (4-way) switch box can be built to be universal with only 6W switches, where W is the global routing channel density. As the routing resource is relatively expensive in FPGA chips, study of the optimum switch box designs is clearly a topic with theoretical and commercial value of reducing silicon cost. A previous work has constructed a formal mathematical model of this optimum design problem for switch boxes with arbitrary dimensions, and gave a scheme to produce hyper-universal designs with less than 6.7W switches for 4-way FPGA switch boxes. In this paper, we will further investigate this most common 4-way switch box case, and will give new theoretical results followed by extensive experimental justification, The results seem to be quite attractive. We show that such an optimum switch box can be built with a very low number of additional switches beyond 6 W for today's practical range of low W's (e.g. just 6W plus 1 or 2 additional switches for W's up to 7). Even for arbitrary large W's, the bound can be shown to be under 6.34W. To make experimental comparison, we run today's published best FPGA router VPR on large benchmarks for the popular disjoint structure and our proposed designs. The results are quite encouraging.

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 score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.098
GPT teacher head0.257
Teacher spread0.159 · 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
Published2002
Admission routes1
Has abstractyes

Explore more

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