ARTSim: A Robust Thermal Simulator for Heterogeneous Integration Platforms
Bibliographic record
Abstract
Chiplet-based integration is a paradigm shift in system design and advanced packaging methodologies. A robust early-stage design tool supporting the thermal simulation of chiplet-based systems is essential to ensure efficient thermal management and high thermal design power. ARTSim, a robust compact thermal simulator for heterogeneous integration platforms, is presented in this work. ARTSim supports efficient thermal modeling of chiplet-based systems. ARTSim is based on a novel hybrid meshing structure that enables customization of the simulation granularity at the functional block level. Furthermore, ARTSim is backward-compatible with conventional two- and three-dimensional packaging platforms. Simulation results from ARTSim on a floorplan similar to the Alpha 21264/EV6 processor, were compared to results obtained from state-of-the-art finite element method tools. Simulation results confirm that the temperature accuracy of the thermal maps generated by ARTSim is within 3.7% maximum error, while exhibiting a reduction in runtime of up to two orders of magnitude.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".