Proceedings of the 2006 ACM/SIGDA 14th international symposium on Field programmable gate arrays
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
Welcome to FPGA 2006, the Fourteenth International Symposium on Field-Programmable Gate Arrays. FPGA remains the premier conference for advances in all areas related to FPGA technology. With ever increasing NRE costs, DSM effects, and FPGA capacities, the importance of FPGAs today is as high as ever. Continuing our traditional themes, the papers in this year's symposium present new developments in architecture, the impact of technology on FPGA designs, improved CAD techniques and algorithms, and new techniques for efficiently mapping applications to FPGAs. Papers and the panel discussion demonstrate increasing attention to power and point out where there is still much room for innovation and improvement in FPGA architecture and CAD.This year the symposium attracted one hundred submissions. We have selected 22 papers for presentation. We also invited 30 papers for poster presentation.FPGA 2006 provides a relaxed atmosphere for informal information exchange, networking, and stimulating discussion with leaders in the FPGA field from both industry and academia. Paper sessions are separated by ample time to peruse the poster presentations and discuss the latest developments in the field. We hope you will take this opportunity to see the cutting-edge of FPGA innovation, make new contacts, and reacquaint yourself with old colleagues.
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 | 0.000 | 0.000 |
| Open science | 0.002 | 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