Decimal floating‐point fused multiply‐add with redundant internal encodings
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
Decimal floating‐point (DFP) arithmetic has attracted attention in the applications of financial and commercial computing. However, the processing efficiency of DFP is still far away from that of binary designs. On the other hand, a floating‐point fused multiply‐add (FMA) function is widely used in many processors within functional iterations to implement division, square root, and many other functions due to the better accuracy achieved by a single rounding of continuous multiplication and addition. In this work, a new architecture of FMA is proposed to speed up the DFP processing. Compared with previous architectures, first, the proposed design applies a specific decimal redundant encoding system. The circuits to decide and shift the rounding position on a redundant result are therefore simplified. Second, the only digit‐set conversion in the entire design is combined with the rounding operation to further reduce the critical path. Third, the techniques applied in different previous FMAs are merged in the proposed design. In addition the multiplier and adder referred to the previous designs are further optimised. Consequently, compared with the fastest previous design, the synthesis results show about 33.7% speed advantage and about 16.6% area advantage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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