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Record W2801455238 · doi:10.1109/iscas.2018.8351128

NIZCache: Energy-efficient Non-uniform Cache Architecture for Chip-multiprocessors Based on Invalid and Zero Lines

2018· article· en· W2801455238 on OpenAlexaff
Pooneh Safayenikoo, Arghavan Asad, Mahmood Fathy, Farah Mohammadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCacheParallel computingComputer scienceCache algorithmsCache pollutionStatic random-access memoryCache-only memory architectureCache coloringCPU cacheSmart CachePage cacheEnergy consumptionLeakage (economics)Embedded systemComputer hardwareEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The 3D design of SRAM LLCs has made the thermal problem, even more, sever and therefore incurs more leakage energy consumption compared to conventional SRAM cache architectures in 2Ds due to dense integration. In this paper, we propose a runtime cache architecture called NIZCache. The core idea of NIZCache is to use the non-uniform distribution of the accesses, invalid lines, and zero-value lines in banks of last level cache for decreasing both dynamic and leakage energy. The proposed architecture that is based on non-uniform cache architectures (NUCA) disables cache banks that have low accesses and high invalid and zero lines and leads to high energy-efficiency. The Experimental results show that the proposed method improves the energy-delay product by about 17% on average under PARSEC benchmarks compared to previous work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.563
Threshold uncertainty score0.621

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 science0.0010.000
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 head0.016
GPT teacher head0.259
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2018
Admission routes1
Has abstractyes

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