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Record W2075137913 · doi:10.1109/fpl.2012.6339278

Analytical placement for heterogeneous FPGAs

2012· article· en· W2075137913 on OpenAlex

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsField-programmable gate arraySpeedupComputer scienceLookup tablePlacementLogic blockParallel computingSimulated annealingPlacer miningApplication-specific integrated circuitMultiplier (economics)Computer hardwareAlgorithmEmbedded systemPhysical designCircuit design

Abstract

fetched live from OpenAlex

We present HeAP, an analytical placement algorithm for heterogeneous FPGAs comprised of LUT-based logic blocks, multiplier/DSP blocks and block RAMs. Specifically, we adapt a state-of-the-art ASIC-based analytical placer to target FPGAs with heterogeneous blocks located at discrete locations throughout the fabric. Our placer also handles macros of LUT-based blocks with specific layout requirements, such as carry chains. Results show that our placer delivers a 4× speedup, on average, compared to Altera's non-timing driven flow, at the cost of a 5% increase in postrouted wirelength, and an 11× speedup compared to Altera's timing-driven flow, at the cost of a 4% increase in post-routed wirelength and a 9% reduction in maximum operating frequency. We also compare with an academic simulated annealing-based placer and demonstrate a 7.4× runtime advantage with 6% better placement quality.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.225

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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

Quick stats

Citations90
Published2012
Admission routes1
Has abstractyes

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