Bibliographic record
Abstract
Synthesizable FPGA fabrics offer several advantages over the full-custom FPGAs produced by the leading commercial FPGA vendors, including process portability and ease of customization to a particular application. In this work, we consider the dynamic power consumption of standard-cell synthesizable FPGAs and quantify the "gap" in power between a synthesized FPGA and its full-custom equivalent. An Intel Stratix-IV-like FPGA, targetable by the VTR flow [9], is implemented in 45nm standard cells using an ASIC toolflow. Post-layout RC extraction is performed, permitting an accurate delay-based simulation for a set of application benchmarks, and detailed power analysis using PrimeTime PX (PTPX). Power results are compared with the same benchmarks implemented on the commercial Stratix-IV (40nm technology). Results show that glitches are a more significant component of power in the standard-cell vs. full-custom FPGA, and that for sequential circuits, the dynamic power gap ranges from 1.3-3.3×.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".