MétaCan
Menu
Back to cohort
Record W1974526541 · doi:10.1145/944027.944034

Testing high-performance pipelined circuits with slow-speed testers

2003· article· en· W1974526541 on OpenAlexaff
Muhammad Nummer, Manoj Sachdev

Bibliographic record

VenueACM Transactions on Design Automation of Electronic Systems · 2003
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer sciencePipeline (software)Static timing analysisClock skewElectronic circuitComputer hardwareSynchronous circuitCMOSClock rateClock signalCPU multiplierDigital clock managerShift registerClock gatingEmbedded systemElectronic engineeringElectrical engineeringChipJitter

Abstract

fetched live from OpenAlex

This article presents a methodology for testing high-performance pipelined circuits with slow-speed testers. The technique uses a clock timing circuit to control data transfer in the pipeline in test mode. The technique adds no extra hardware in the data path of the pipeline and therefore has virtually no performance penalty. A clock timing circuit capable of achieving a timing resolution of 50 ps in 0.18 μm CMOS technology is presented. The design provides the ability to test the clock timing circuit itself. The effectiveness of the technique is demonstrated using a 16-bit pipelined multiplier as a test vehicle. Simulations show that we are able to detect delay faults as small as 50 ps at an input clock frequency of 100 MHz.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.199
Teacher spread0.181 · 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
GenreEmpirical

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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueACM Transactions on Design Automation of Electronic SystemsSame topicLow-power high-performance VLSI designFrench-language works237,207