Acceleration of finite-difference time-domain (FDTD) using graphics processor units (GPU)
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.
Bibliographic record
Abstract
The Finite-Difference Time-Domain (FDTD) method is used extensively in areas of microwave engineering and optics. However, FDTD runs too slow for some simulations to be practical, especially when run on standard desktop computers. The suitability of dedicated hardware for the acceleration of FDTD computations has been investigated. It is demonstrated that standard consumer Graphics Processor Units (GPUs) can be used to accelerate FDTD simulations by a factor of over seven, relative to an Intel CPU of similar technology generation. With OpenGL as the Application Programming Interface (API), a standard commercial graphics card has been programmed to solve a 2-D electromagnetic scattering problem.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it