Reconfigurable array for transcendental functions calculation
Why this work is in the frame
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Bibliographic record
Abstract
Expanding transcendental functions in a series of Shift-and-Add operations is an alternative to Taylor or Chebyshev series expansions when fixed-point arithmetic with reduced wordlength is required. Typically, reconfigurable arrays do not provide architectural support for shift operations. Instead, shift operations are emulated by either multiplexing logic or multiplication by a power of 2. In this paper we describe the architecture of a reconfigurable array that can natively support shift operations. Rather than augmenting the reconfigurable fabric with dedicated shift units, the interconnection network is extended with shift capabilities. This is conceptually possible since a shift operation is a rearrangement and not a combination of the signals. Layers of computing tiles supporting Shift-and-Add/Subtract and Add-and-Select operations are interleaved with interconnect layers. On such a reconfigurable array, a variety of transcendental functions can be efficiently implemented.
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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 | 0.000 |
| 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