Bibliographic record
Abstract
A Field-Programmable Gate Array (FPGA) is an integrated circuit that allows users to program product features and functions after manufacturing. Verilog-to-Routing (VTR) is an open source CAD tool for conducting FPGA architecture and CAD research and development. As one of the core tools of VTR, Odin II is responsible for Verilog elaboration and hard block synthesis. This project describes the improvements in Odin II on three aspects: for loop support, abstract syntax tree (AST) simplification and hard block reduction. This work allows elaboration of a for loop statement by modifying the Abstract Syntax Tree (AST). There are different alternatives to simplify an AST, and this paper demonstrates three ways: simplifying expressions with variables, reducing parameters with values and using shift operations to replace multiplications or divisions. For a circuit design, some hard blocks in the netlist have the same high-level function. This project further provides a method to reduce redundant hard blocks. Each implementation is tested with designed testing cases or sets of benchmarks, and the results of running them through Odin II and VTR are demonstrated.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".