Selecting GVT interval for time-warp-based distributed simulation using reinforcement learning technique
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Bibliographic record
Abstract
In a Time-Warp-based distributed simulation system, a simulation process must save its states and events to handle rollbacks. Periodically, the global minimum of the timestamps of events and messages in the entire system is calculated. This value is known as the global virtual time (GVT), and it plays an important role in a Time Warp system. GVT is only computed periodically because of the computation overhead. An important problem is to determine the optimal interval between two GVT computations. In this paper we present a new approach that uses a simple Reinforcement Learning technique to select the optimal GVT interval. Used in a Time-Warp-based distributed VLSI simulation system, our method was successful in selecting good GVT interval and improving the system's performance.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it