FPGA-Based Efficient Design Approach for Large-Size Two's Complement Squarers
Bibliographic record
Abstract
This paper presents an optimized design approach of two's complement large-size squarers using embedded multipliers in FPGAs. The realization is based on Baugh-Wooley's algorithm, which partitions the multiplication into unsigned and signed sections. To achieve efficient implementation, a set of optimized schemes for the realization of multi-level additions of the partial products is proposed. Our approach has been evaluated through the implementation of squarers for operands with sizes ranging from 20 to 128 bits. The designs are synthesized and implemented on Xilinx' Spartan-3 with ISE 8.1 design platform and compared with the standard implementation, and with Xilinx' IP Core. The results indicate that our approach offers substantial LUT savings by up to 52% with an average delay reduction of 13%. The usage of the number of embedded multipliers is reduced by 38% compared with the standard schemes.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".