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Record W2044274432 · doi:10.1145/1147349.1147358

Hiding message delivery and reducing memory access latency by providing direct-to-cache transfer during receive operations in a message passing environment

2005· article· en· W2044274432 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 SIGARCH Computer Architecture News · 2005
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceCacheCopyingCache invalidationMessage passingLatency (audio)Computer networkThread (computing)Cache pollutionFalse sharingCache algorithmsBus sniffingCPU cacheDistributed computingParallel computingOperating systemTelecommunications

Abstract

fetched live from OpenAlex

The focus of this work is on techniques that promise to reduce the message delivery latency in message passing environments. The main contributors to message delivery latency in message passing environments are the copying operations needed to transfer and bind a received message to the consuming process/thread. To reduce this copying overhead and to reach to finer granularity, we introduced architectural extensions comprising of specialized network cache and instructions to manage the operations of this extension. In this work we study the caching environment. Our simulations show that messages can be bound and transferred into the data cache where they persist long enough to be consumed. We also study the structure of the required network cache and show that a small capacity cache is sufficient.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.002
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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