MétaCan
Menu
Back to cohort

Memory‐Conserving Bounding Volume Hierarchies with Coherent Raytracing

2006· article· en· W2021838328 on OpenAlexafffund
J. Mahovsky, Brian Wyvill

Bibliographic record

VenueComputer Graphics Forum · 2006
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBounding volumeEncoding (memory)Bounding overwatchRay tracing (physics)Volume (thermodynamics)Scheme (mathematics)Overhead (engineering)Parallel computingComputer graphics (images)AlgorithmTheoretical computer scienceArtificial intelligenceMathematicsOpticsCollision detection

Abstract

fetched live from OpenAlex

Abstract Bounding volume hierarchies (BVHs) are a popular method for speeding up raytracing, but they can consume a large amount of memory for complex scenes. We investigate a hierarchical scheme for encoding BVHs that reduces the BVH storage requirements by 63%–75%. The computational overhead of the scheme can be reduced to negligible levels by shooting bundles of rays through the BVH (coherent raytracing). This gives the speed of a coherency‐based raytracer combined with substantial memory savings.

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)0.003
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.232
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

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

Citations33
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueComputer Graphics ForumSame topicComputer Graphics and Visualization TechniquesFrench-language works237,207