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Record W230790256 · doi:10.1504/ijhpcn.2006.013476

Performance evaluation of the Sun Fire Link SMP clusters

2006· article· en· W230790256 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

VenueInternational Journal of High Performance Computing and Networking · 2006
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceInterconnectionLatency (audio)Link (geometry)Node (physics)Bandwidth (computing)SoftwareRemote direct memory accessCluster (spacecraft)Computer networkComputer architectureOperating systemEngineeringTelecommunications

Abstract

fetched live from OpenAlex

The interconnection networks and the communication system software are critical in achieving high performance in clusters. Sun Fire Link interconnect is a memory-based interconnect, where the Sun MPI uses the Remote Shared Memory (RSM) model for its user-level inter-node messaging. This paper presents the overall architecture of the Sun Fire Link and its messaging layer. We provide an in-depth performance evaluation of a Sun Fire Link cluster at the RSM, MPI, and application layers. The MPI ping-pong latency and bandwidth are five microseconds and 660 MB/s, respectively. In general, the Sun Fire Link cluster performs relatively well in most cases.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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