Scala defined hardware generators for Chisel
Bibliographic record
Abstract
We describe digital hardware designs in hardware description languages such as VHDL and SystemVerilog. Both languages were developed in the 1980s and, although regularly updated, are still in the style of their time. They lack the constructs to write more configurable generators than just the number of bits for an operation. Based on Scala, Chisel is a hardware construction language that helps to write hardware generators. Hardware generators are not a new idea. Scripting languages, such as Perl and TCL, are often used to generate VHDL or Verilog code from other sources of system description. However, mixing two languages and embedding VHDL or Verilog strings in generator code is not scalable. As Chisel is embedded in Scala, we can write the generators using the same language/environment as we use to describe the digital logic. This paper explores different examples and patterns to describe parameterizable hardware generators. We are confident that practices from software development can improve the productivity of hardware designers to build and test the next billion transistor chips.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.013 |
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".