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Record W1984981318 · doi:10.1109/fpt.2012.6412117

An FPGA with power-gated switch blocks

2012· article· en· W1984981318 on OpenAlexaff
Assem A. M. Bsoul, Steven J. E. Wilton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPower gatingIdleField-programmable gate arrayBenchmark (surveying)Power (physics)Computer scienceLow-power electronicsLogic synthesisLogic gateEmbedded systemDissipationElectronic engineeringPower consumptionEngineeringElectrical engineeringTransistorVoltageAlgorithmPhysics

Abstract

fetched live from OpenAlex

Static power consumption is an important component of the total power consumption in FPGAs built using 90nm and smaller technology nodes. A previous study proposed powering down regions of logic blocks in an FPGA when idle to reduce the static power dissipation. This previous work did not consider powering down the switch blocks (SBs). However, the static power of SBs constitute more than 50% of an FPGA's static power. In this paper, we present an architecture that enables selectively powering down SBs along with the logic blocks during their idle periods. The potential power savings from this architecture depends on the proportion of SBs that can be powered down. We present modifications to our CAD flow to maximize the number of such SBs, and we experimentally estimate their proportion using a set of synthetic benchmark circuits. Our estimation results show that 53% to 83% of the SBs can be powered down in a functional module of size 24×24 tiles and an architecture power gating regions of size 4×4 tiles, leading to overall static power reductions of 70% to 84% compared to an architecture that does not support power gating.

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 categoriesInsufficient payload (model declined to judge)
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 score0.394
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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 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

Citations16
Published2012
Admission routes1
Has abstractyes

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