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UVM Verification IP for AXI

2021· article· en· W3208979388 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
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceVerilogFunctional verificationIntelligent verificationReusabilityHigh-level verificationEmbedded systemInterface (matter)VerificationFormal verificationComputer architectureRuntime verificationFlexibility (engineering)Coding (social sciences)Programming languageOperating systemField-programmable gate arraySoftware

Abstract

fetched live from OpenAlex

Over time, the complexity of ICs design increasing which making these designs more error-prone. Verification of Integrated Circuits using Verilog lacks the flexibility and reusability of the environment. System Verilog UVM methodology gives building blocks and OOP concepts to work with. That allows to create much more flexible test environment with reusable components. This paper presents a verification architecture of configurable Verification IP for AXI interface. This paper presents an architecture of verification environment for AMBA AXI interface and can be used to test any AXI device. A functional coverage model has been developed to determine if the verification process covers all possible scenarios or not. Each testcase reports coverage which is later used to analyze the effectiveness of the testcase. Full coverage has been achieved using both random and directed test cases. The coding is done using System Verilog and the simulation is done using VCS.

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: Methods · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.112

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 head0.031
GPT teacher head0.254
Teacher spread0.223 · 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

Citations22
Published2021
Admission routes1
Has abstractyes

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