MétaCan
Menu
Back to cohort
Record W1980386426 · doi:10.1109/dsd.2013.19

pCache: An Observable L1 Data Cache Model for FPGA Prototyping of Embedded Systems

2013· article· en· W1980386426 on OpenAlexaff
Parthasarathy Ravishankar, Samar Abdi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceCacheEmbedded systemDebuggingField-programmable gate arrayEmulationCache algorithmsFPGA prototypeSoftwareCPU cacheComputer hardwareParallel computingOperating system

Abstract

fetched live from OpenAlex

This paper presents a configurable and observable model of L1 data cache memory and a novel method for integrating the model into an FPGA prototype. Embedded system software designers use in-circuit emulation on FPGA platforms to validate the functionality and performance of embedded software. Data cache, particularly L1, has a major impact of system performance, yet remains unobservable during software debugging and analysis. Our solution is to model the data cache as an on-chip hardware peripheral that can be integrated into the processor system and can display the state of the data cache at any given time. The model is synthesized on Xilinx Virtex 5 FPGA and validated using several benchmarks. The experimental results show that the model can accurately track cache hits and misses and can estimate the run time of an embedded software application with an average error of only 5.4%, and a worst case error of only 13.7%.

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)0.001
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: Methods
Teacher disagreement score0.209
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.150
GPT teacher head0.327
Teacher spread0.177 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicParallel Computing and Optimization TechniquesFrench-language works237,207