Simulation of large-scale electrical power networks on graphics processing units
Why this work is in the frame
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Bibliographic record
Abstract
In this paper suitability of applying graphics processing unit (GPU) based computing for electromagnetic transient (EMT) simulation of large scale power systems is demonstrated. As the network size increases there is a corresponding increase in simulation time with conventional central processing unit (CPU) based simulation tools. The paper shows that with a hybrid environment consisting of CPUs and GPUs, simulation time is much less compared to the CPU-only implementations. In this scheme the GPU is mainly used to do the computationally intensive part of the simulation in parallel on its built-in multiple processing cores, and the CPU is assigned for updating history terms and flow control of the simulation. The GPU-based approach is used to simulate a network with 117 nodes, and it is shown that the CPU-GPU based implementation takes less than half of the time taken by the CPU-only implementation of the simulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it