A Configurable FPGA Implementation of the Tanh Function Using DCT Interpolation
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Bibliographic record
Abstract
Efficient implementation of non-linear activation functions is essential to the implementation of deep learning models on FPGAs. We introduce such an implementation based on the Discrete Cosine Transform Interpolation Filter (DCTIF). The proposed interpolation architecture combines simple arithmetic operations on the stored samples of the hyperbolic tangent function and on input data. It achieves almost 3× better precision than previous works while using a similar amount computational resources and a small amount of memory. Various combinations of DCTIF parameters can be chosen to trade off the accuracy and the overall circuit complexity of the tanh function. In one case, the proposed architecture approximates the hyperbolic tangent activation function with 0.004 maximum error while requiring only 1.45 kbits BRAM memory and 21 LUTs of a Virtex-7 FPGA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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