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Record W2042627331

Performance Boosting under Reliability and Power Constraints

2015· article· en· W2042627331 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
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsVoltage droopBandwidth throttlingVoltageVoltage reductionComputer sciencePower gatingVoltage regulatorEngineeringElectrical engineeringTransistor
DOInot available

Abstract

fetched live from OpenAlex

Abstract—Voltage droops resulting from inductive noise are common in state-of-the-art processors. Many of the techniques used to reduce energy consumption-- clock gating, power gating, process shrinks, and voltage reduction-- lead to increased voltage droops or increased sensitivity to voltage variations. Designers use voltage guardbands to minimize errors due to voltage fluctuations and inductive noise; however, this leads to lower performance because the voltage and frequency points are set to deal with voltage droops from a worst-case benchmark or stressmark. Although most applications do not approach the voltage droop caused by the stressmark, there is no mechanism to guarantee correct operation outside the tested range. In this paper, we examine floating-point issue throttling (FP throttling), a hardware technique that reduces worst-case voltage droop. By lowering the issue rate in the FP scheduler, the

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.212

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 head0.028
GPT teacher head0.262
Teacher spread0.234 · 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