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
FPGA technology is commonly used to prototype new digital designs before entering fabrication. Whilst these physical prototypes can operate many orders of magnitude faster than through a logic simulator, a fundamental limitation is their lack of on-chip visibility when debugging. To counter this, trace-buffer-based instrumentation can be installed into the prototype, allowing designers to capture a predetermined window of signal data during live operation for offline analysis. However, instead of requiring the designer to recompile their entire circuit every time the window is modified, this article proposes that an overlay network is constructed using only spare FPGA routing multiplexers to connect all circuit signals through to the trace instruments. Thus, during debugging, designers would only need to reconfigure this network instead of finding a new place-and-route solution. Furthermore, we describe how this network can deliver signals to both the trigger and trace units of these instruments, which are implemented simultaneously using dual-port RAMs. Our results show that new network configurations connecting any subset of signals to 80--90% of the available RAM capacity can be computed in less than 70 seconds, for a 100,000 LUT circuit, as many times as necessary. Our tool—QuickTrace—is available for download.
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 | 0.001 | 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 it