Fine-grained vs. coarse-grained shift-and-add arithmetic in FPGAs (abstract only)
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
This study compares the speed, area, and latency of shift-and-add arithmetic implemented within fine-grained FPGA resources and within a proposed coarse-grained embedded block for FPGAs. It begins by optimizing the mapping of various shift-and-add architectures within the fine-grained resources of a commercial FPGA to determine which provides the best area, delay, and latency for various word-lengths. It then proposes a new coarse-grained block that supports 16, 32, and 64-bit shift-and-add arithmetic and finally compares coarse-grained implementations to the best fine-grained implementations. Our results show that the coarse-grain implementations are between 15 and 47 times smaller and 5 to 18 times faster, depending on the implementation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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