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Record W1970019860 · doi:10.1049/iet-cdt.2010.0024

Reordering the assembly instructions in basic blocks to reduce switching activities on the instruction bus

2011· article· en· W1970019860 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

VenueIET Computers & Digital Techniques · 2011
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsHeuristicsOperandComputer scienceParallel computingInteger (computer science)Power (physics)Reduction (mathematics)ComputationInteger programmingEmbedded systemCode (set theory)DissipationComputer hardwareProgramming languageAlgorithmOperating systemMathematics

Abstract

fetched live from OpenAlex

Execution time is no longer the only target to achieve when designing programmes for today and next-generation CMOS-based digital systems. One needs to also consider reducing power dissipation. Buses contribute to the power dissipation during the execution of a given programme since instructions and/or operands have to be fetched from the memory. Reducing power dissipation in buses has been addressed in the literature. In this study, the authors address the problem of reducing power dissipation of the instruction bus by reordering the instructions in basic blocks without increasing the executing time and the code size, and while maintaining the original functionality of the programme. The authors target embedded processors having Harvard architecture. They focus on solving this problem for programmes developed at the assembly level, since at that level the machine code can be obtained by simply running an assembler, which allows an accurate computation of switching activities on the instruction bus by considering each pair of instructions. The authors formulate this problem as an integer linear programme (ILP), and they provide two heuristics. Experimental results have shown that the proposed approach can reduce switching activities. The ILP has reduced switching activities by as high as 38%. One of the two proposed heuristics has always resulted in reducing switching activities, and its relative savings are within an average of 5% from the optimum produced using the ILP.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.026
GPT teacher head0.245
Teacher spread0.219 · 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