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Record W2094341653 · doi:10.1145/2489068.2491624

AutoPilot

2013· article· en· W2094341653 on OpenAlexaff
B. Kelly, William B. Gardner, Shorin Kyo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of GuelphGoogle (Canada)
Fundersnot available
KeywordsComputer scienceSIMDMulti-core processorParallel computingInterface (matter)Message passingCacheVMEbusAutopilotMessage Passing InterfaceOperating systemEmbedded systemComputer architectureSoftware

Abstract

fetched live from OpenAlex

The Renesas Electronics IMAPCAR2 embedded realtime image processor combines a single core with a 128-way SIMD array. At runtime, sections of the SIMD array can be reconfigured as additional CPU cores, interconnected via a message ring. Effective use is made difficult by the low-level message passing API and lack of cache coherency between processors. The AutoPilot library addresses this by providing a high-level message-oriented parallel programming model mirroring that of Pilot, itself a wrapper around the Message Passing Interface (MPI) for cluster computing. AutoPilot shows that Pilot's processes-and-channels architecture is a viable choice for parallel programming on cache-incoherent multicore and manycore architectures. It provides a simpler API for programmers, with built-in safety checks that eliminate some common sources of errors. Since the IMAPCAR2 is targeted chiefly at automotive applications, open source AutoPilot has a large degree of MISRA-C compliance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.135
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1350.066

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 head0.235
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2013
Admission routes1
Has abstractyes

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