A re-usable verification framework of Open Core Protocol (OCP)
Bibliographic record
Abstract
Open core protocol (OCP) establishes itself as the only non-proprietary, openly licensed, core-centric protocol that is used to support ldquoplug-and-playrdquo SOC (system-on-chip) design practices. Designer can reuse OCP-compliance IP cores based on system integration and verification approach in multiple designs without reworking, reducing the development time and cutting down overall design costs. This paper addresses the development of a reusable verification framework of OCP. Assertion-based verification was chosen in order to enforce the flow. An OCP System Verilog monitor which was developed in house is used to verify the OCP SystemC TL1 (cycle-accurate level) design. The monitor can also be reused for OCP designs described at different abstraction level and thus dramatically reduce the time needed for OCP functional verification. With proper configuration of this monitor along with our System Verilog Assertion suite, we have found a potential bug in the OCP TL1 implementation which awaits confirmation of the OCP-IP group.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".