Bibliographic record
Abstract
Processor concepts, implementation details, and performance analysis are fundamental in computer architecture education, and MIPS (microprocessor without interlocked pipeline stages) processor designs are used by many universities in teaching the subject. In this paper we present a MIPS32 processor simulator, which enriches students’ learning and instructors’ teaching experiences. A family of single-cycle, multi-cycle, and pipeline processor models for the MIPS32 architecture are developed according to the parallel Discrete Event System Specification (DEVS) modeling formalism. A collection of elementary sequential and combinational model components along with the processor models are implemented in DEVS-Suite. The simulator supports multi-level model abstractions, register-transfer level animation, performance data collection, and time-based trajectory observation. These features, which are partially supported by a few existing simulators, enable important structural and behavioral details of computer architectures to be described and understood. The MIPS processor models can be reused and systematically extended for modeling and simulating other MIPS processors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".