High Performance and Energy Efficient Floating-Point Multiplier on FPGA
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a high performance and energy efficient double-precision floating-point multiplier is designed and implemented on FPGA devices. A novel mapping solution of the mantissa multiplier is proposed which makes full use of the DSP blocks and requires less pipeline stages. In addition, a dual-mode floating-point multiplier is also proposed in this paper which is designed by splitting the components of the proposed double-precision multiplier. Two parallel single-precision operations are supported. For comparison purpose, the proposed architecture is implemented on Xilinx Virtex-5 (xc5vlx155ff1760-3) device, where the proposed double-precision multiplier can run 3.4% faster than previous work with less latency and can run 32.3% faster than the IP core multiplier with same latency. The proposed dual-mode multiplier can run 20.9% faster than previous fastest dual-mode design. In terms of energy consumption, the proposed double-precision multiplier consumes 43.3% less energy per operation compared to the double-precision IP core. The proposed dual-mode multiplier can achieve 24.5% less energy per operation compared to the double-precision IP core. The implementation results of the proposed architectures on latest Xilinx Virtex-7 and Altera Arria-10 devices are provided.
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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