Fast and cycle-accurate simulation of multi-threaded applications on SMP architectures using hybrid prototyping
Bibliographic record
Abstract
This paper presents a fast and cycle accurate simulation environment for early power-performance analysis of multithreaded applications targeted to symmetric multiprocessing embedded architectures. Our simulation environment leverages the hybrid prototyping technique, where a lightweight emulation kernel performs logical simulation of multiple identical cores on top of a single physical instance of a core. The technique does not require a detailed timing model of the core hardware because the application threads execute directly on the target core. Previous work on hybrid prototyping supported modeling of only statically scheduled threads, thereby severely limiting its modeling capabilities. In this work, we describe the modeling of dynamic RTOS scheduler as well as hardware interrupts on top of the emulation kernel, in order to support the simulation of unmodified multi-threaded applications. Our experimental results demonstrate the high accuracy, simulation speed and scalability of our hybrid prototyping-based simulation models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".