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Record W2103079270 · doi:10.1109/ccece.2003.1226268

Hardware-software co-synthesis of partially re-configurable embedded systems optimized for reduced power consumption

2004· article· en· W2103079270 on OpenAlex
Jacob Levman, Gul N. Khan, Javad Alirezaie, K. Raahemifar

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
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsControl reconfigurationComputer scienceField-programmable gate arrayScheduling (production processes)Embedded systemLocalitySoftwarePower consumptionOverhead (engineering)Distributed computingPower (physics)Operating systemEngineering

Abstract

fetched live from OpenAlex

In this paper, we present a scheduling algorithm as part of the hardware-software co-synthesis of low power distributed embedded devices. We used a location priority based algorithm in order to address embedded computer systems consisting of processors, partially reprogrammable FPGAs, and other resources. Our proposed locality emphasized two-dimensional scheduling algorithm prioritizes the unused FPGA locations and chooses a task to match the given position. This is an unusual approach to task scheduling, where the norm is to prioritize the candidate pool of tasks and then decide on a location. The FPGA reconfiguration process consumes large amounts of power. This algorithm is optimized to reduce overall system power consumption and to ensure all tasks meet their respective deadlines. Preliminary experimental results reveal significant reconfiguration overhead reduction while maintaining a low deadline violation rate.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.604
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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