Bibliographic record
Abstract
Field programmable gate arrays (FPGAs) are an increasingly popular implementation medium for digital circuits. An FPGA is a prefabricated piece of silicon that can be configured by the user to implement any digital circuit. This ability enables them to offer two key advantages over other implementation technologies: low cost and fast time-to-market. However, the flexibility they offer comes at a steep price. Circuits implemented in FPGAs are three times slower and ten times larger than an equivalent circuit implemented using standard cells or mask programmed gate arrays. This dissertation presents area optimizations in FPGA architecture and CAD. The primary focus is on a new area efficient adaptive FPGA (AFPGA) architecture. An AFPGA is obtained from an FPGA by replacing a fraction of the configuration SRAM with adaptive SRAM whose functionality changes in response to changes in a control signal. Adaptive programmable structures (logic elements, multiplexers, and routing switches) are produced wherever adaptive SRAM is used, and the resulting structures can be shared by two subcircuits that are not required to “exist” simultaneously. To support the new architecture, a new CAD flow is proposed and a set of CAD tools
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 | 0.000 |
| 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".