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Record W2126795434 · doi:10.1109/ipdps.2008.4536190

Extended characterization of DMA transfers on the Cell BE processor

2008· article· en· W2126795434 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings - IEEE International Parallel and Distributed Processing Symposium · 2008
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsComputer scienceCopyingThread (computing)Message passingParallel computingMulti-core processorComputer architectureLatency (audio)Embedded systemDistributed computingOperating system

Abstract

fetched live from OpenAlex

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. A significant portion of the software communication overhead is attributed to message copying. Recently, a set of factors has been leading high- performance processor architectures toward designs that feature multiple processing cores on a single chip (a.k.a. CMP). The Cell Broadband Engine (BE) shows potential to provide high-performance to parallel applications (e.g., MPI applications). The Cell's non-homogeneous architecture along with small local storage in SPEs impose restrictions and challenges for parallel applications. In this work, we first characterize various data delivery mechanisms in the Cell BE processor; then, we propose techniques to facilitate the delivery of a message in MPI environments implemented in the Cell BE processor. We envision a cluster system comprising several cell processors each supporting several computation threads.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score0.778

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 communication0.0000.001
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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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