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Record W4292596050 · doi:10.1145/3556975

PISCOT: A Pipelined Split-Transaction COTS-Coherent Bus for Multi-Core Real-Time Systems

2022· article· en· W4292596050 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

VenueACM Transactions on Embedded Computing Systems · 2022
Typearticle
Languageen
FieldComputer Science
TopicReal-Time Systems Scheduling
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceCache coherenceCorrectnessEmbedded systemAvionicsTestbedCoherence (philosophical gambling strategy)Distributed computingLatency (audio)Real-time computingComputer architectureParallel computingCacheCPU cacheComputer networkAlgorithm

Abstract

fetched live from OpenAlex

Tasks in modern embedded systems such as automotive and avionics communicate among each other using shared data towards achieving the desired functionality of the whole system. In commodity platforms, cores communicate data through the shared memory hierarchy and correctness is maintained by a cache coherence protocol. Recent works investigated the deployment of coherence protocols in real-time systems and showed significant performance improvements. Nonetheless, we find these works to require modifications to commodity coherence protocols, assume simple in-order pipelines, and most importantly suffer from significant latency delays due to coherence interference along with average performance degradation. In this work, we propose PISCOT : a predictable and coherent bus architecture that (i) provides a considerably tighter bound compared to the state-of-the-art predictable coherent solutions (4× tighter bounds in a quad-core system). (ii) It does so with a negligible performance loss compared to conventional high-performance architecture coherence delays (less than 4% for SPLASH-3 benchmarks). This improves average performance by up to 5× (2.8× on average) compared to its predictable coherence counterpart. Finally, (iii) it achieves that without requiring any modifications to conventional coherence protocols. We show this by integrating PISCOT on top of two protocols with a detailed implementation with complete transient states: MSI and MESI.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.892
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.301
Teacher spread0.249 · 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