Parallel filtering and thresholding of images on the SIMD DSP-RAM architecture
Bibliographic record
Abstract
DSP-RAM is a moderately-parallel, single-chip SIMD (single instruction stream, multiple data stream) architecture that has been proposed as a suitable hardware platform for accelerating signal processing applications. Our goal is to evaluate the potential of DSP-RAM as a coprocessor for important low-level graphical operations such as convolution filtering and thresholding. Insights gained during the initial implementation prompted a minor improvement to the original design. The benchmark operations were microcoded for DSP-RAM and then simulated on an architectural simulator written in C++. The simulation results were compared to the measured execution times for the corresponding Intel integrated performance primitives functions running on a conventional 1 GHz Pentium III personal computer A modest 25 MHz DSP-RAM coprocessor was found to give equivalent or superior performance for mid to large-sized image frames.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".