Multicore acceleration of Discrete Event System Specification systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Parallel discrete-event simulation on heterogeneous multicore platforms requires innovative redesign of existing algorithms in return for better performance. Based on the Discrete Event System Specification (DEVS) methodology, a technique called Multicore Acceleration of DEVS Systems is proposed for efficient parallel discrete-event simulation on the IBM Cell processor. The technique combines multi-grained parallelism and various optimizations to overcome performance bottlenecks, while hiding the technical details of multicore programming from non-expert users. By explicitly exploiting the data- and event-level parallelism inherent in the simulation, the technique significantly accelerates both memory-bound and compute-bound computational kernels in demanding parallel DEVS simulations, as shown in the experimental results. Several key concepts and methods derived from this research can also be applied to other multicore and shared-memory architectures.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it