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Record W1545343273 · doi:10.1109/fpt.2003.1275747

A high-speed ray tracing engine built on a field-programmable system

2004· article· en· W1545343273 on OpenAlex
J. Fender, Jonathan Rose

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of Toronto
FundersXilinx
KeywordsPentiumField-programmable gate arrayComputer scienceRay tracing (physics)Rendering (computer graphics)VirtexSoftwareTracingComputer hardwareEmbedded systemComputer graphics (images)Operating system

Abstract

fetched live from OpenAlex

Ray tracing is a method of rendering high-quality images and video by calculating what happens to virtual light rays in a 3-dimensional scene. It is capable of creating for more realism than traditional Z-buffering methods. This paper describes the design of a hardware ray tracing system implemented on a multi-FPGA Xilinx Virtex-E prototyping system. The result is a hardware ray tracer that is capable of out-performing a 2.4GHz Pentium 4, running a well-known high performance software ray tracing algorithm, by up to a factor of thirty. When these results are projected forward into a next generation FPGA system, consisting of a single large Virtex 2 Pro FPGA, it is found that the system should be able to out perform the same Pentium 4 by up to two orders of magnitude, and the fastest known hardware implementation, the AR350, by up to a factor of three.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.406

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 communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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

Quick stats

Citations30
Published2004
Admission routes1
Has abstractyes

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