Self-sorting FFT method eliminating trivial multiplication and suitable for embedded DSP processor
Why this work is in the frame
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Bibliographic record
Abstract
The Discrete Fourier Transform (DFT) is a mathematical procedure at the core of processing inside a Digital Signal Processor. Speed and low complexity are crucial in the FFT process; they can be achieved by avoiding trivial multiplications through a proper handling of the input/output data and the twiddle factors. Accordingly, this paper presents an innovative approach for handling the input/output data efficiently by avoiding trivial multiplications. This approach consists of a simple mapping of the three indices (FFT stage, butterfly and element) to the addresses of the input/output data with their corresponding coefficient multiplier. A self-sorting algorithm that reduces the amount of memory accesses to the coefficient multipliers' memory can also reduce the computational load by avoiding all trivial multiplications. Compared with the most-recent work [5], performance evaluation in terms of the number of cycles on the general-purpose TMS320C6416 DSP shows a reduction of 29% (FFT of size 4096) and a 50% memory reduction to stock twiddle factors. The algorithm has also shown a speed gain of 24% on the FFTW platform for a FFT of size 4096.
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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 | 0.001 | 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