Bibliographic record
Abstract
As field-programmable gate array (FPGA) capacities continue to increase in lockstep with semiconductor process shrinking, they are being used for increasingly complex applications. However, because FPGAs are bit-level programmable, the task of generating an FPGA implementation from a user's application description is quite complicated. The CAD tools responsible for this are long-running, taking up to a day to generate an FPGA implementation for the largest applications. This thesis presents several approaches to speed-up FPGA CAD tools.The first proposed approach is to parallelize routing, one of the longest running FPGA CAD steps. The second approach is to modify the FPGA architecture such that a coarsened graph representation can be used during the routing stage, which reduces run-time. This approach involves both architectural and algorithmic changes.Next, a fast analytical technique is proposed for the placement stage, another of the longest-running CAD phases. Following that, this thesis proposes that a library of pre-compiled solutions to commonly occurring application fragments be maintained and re-used when possible. Re-using these application fragments leads to a reduction in CAD run-time, since the entire FPGA implementation need not be generated from scratch. Lastly, this thesis presents an approach that can be used to reduce bitwidths, leading to smaller circuits, which reduces CAD complexity and run-time.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".