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Record W2103466822 · doi:10.1109/shpcc.1994.296619

An efficient single copy cache coherence protocol for multiprocessors with multistage interconnection networks

2002· article· en· W2103466822 on OpenAlexaff
R.A. Omran, Mokhtar Aboelaze

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsYork University
Fundersnot available
KeywordsComputer scienceCache coherenceMESI protocolInterconnectionCacheMESIF protocolParallel computingProtocol (science)Shared memoryBus sniffingMultiprocessingScalabilityOverhead (engineering)Distributed shared memoryDistributed computingMultistage interconnection networksComputer networkCache algorithmsCPU cacheMemory managementUniform memory accessOperating systemOverlay

Abstract

fetched live from OpenAlex

Multistage interconnection networks offer an efficient, scalable, and cost effective solution for the problem of connecting processors to memory in a shared memory multiprocessor system. In this paper, we present an efficient single copy cache coherence protocol for multiprocessors with multistage interconnection networks. Our protocol depends on incorporating the cache memory into the switches (caching switches) of the multistage interconnection network. In our proposed protocol, data blocks move between the switches in order to minimize the memory access time. We also develop a migration policy for data blocks not only to minimize the average memory response time but also to minimize the overhead in locating a specific memory block in case of a cache miss. We use two variations of our proposed protocol, the first allows caches to be only in the caching switches in the second of the interconnection network, while the first allows the caches to be in any switch of the interconnection network. We use simulation to evaluate the performance of our protocol and compare it with two multiple copy cache coherence protocols designed for systems employing multistage interconnection networks. The simulation results indicate that our proposed protocol outperforms the distributed write and distributed invalidate protocols for a wide range of memory access patterns.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.707

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 science0.0010.000
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 head0.043
GPT teacher head0.281
Teacher spread0.238 · 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
Published2002
Admission routes1
Has abstractyes

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