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Record W2588724429 · doi:10.1109/isco.2017.7855984

Cache coherency controller verification IP using SystemVerilog Assertions (SVA) and Universal Verification Methodologies (UVM)

2017· article· en· W2588724429 on OpenAlexfundno aff
Barada P. Biswal, Anurag Prakash Singh, Balwinder Singh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsnot available
FundersMinistère de l'Économie, de la Science et de l'Innovation - Québec
KeywordsComputer scienceFunctional verificationHigh-level verificationIntelligent verificationVerificationSoftware verificationFormal verificationSynchronization (alternating current)Runtime verificationEmbedded systemModel checkingComputer architectureProgramming languageSoftwareSoftware developmentSoftware construction

Abstract

fetched live from OpenAlex

Shared memory resources are inevitable components in modern SOC architecture due to Multi-core Architectures resulting ease synchronization with enhanced speed and reliability. Again architectural verification are challenging for these protocols for coherency systems. Hence this project work has come out with complete verification environment for such a complex MESI coherency protocol based on model checking and assumes guarantee verification methods developed through compositional approach of SystemVerilog Assertions (SVA) with functional verification using Universal Verification Methodologies (UVM) packages to substantially ameliorate the difficulties for design accuracy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.131
GPT teacher head0.357
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2017
Admission routes1
Has abstractyes

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