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Found 12 papers, 4 papers with code
Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties
System-Level Test (SLT) has been a part of the test flow for integrated circuits for over a decade and still gains importance.
Deep learning based surrogate modeling for thermal plume prediction of groundwater heat pumps
The ability for groundwater heat pumps to meet space heating and cooling demands without relying on fossil fuels, has prompted their mass roll out in dense urban environments.
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
With those metrics we identify tasks which are challenging for recent ML methods and propose these tasks as future challenges for the community.
A Deep Learning Approach for Thermal Plume Prediction of Groundwater Heat Pumps
Climate control of buildings makes up a significant portion of global energy consumption, with groundwater heat pumps providing a suitable alternative.
PLSSVM: A (multi-)GPGPU-accelerated Least Squares Support Vector Machine
Our implementation scales on many-core CPUs with a parallel speedup of 74. 7 on up to 256 CPU threads and on multiple GPUs with a parallel speedup of 3. 71 on four GPUs.
How to Avoid Trivial Solutions in Physics-Informed Neural Networks
The advent of scientific machine learning (SciML) has opened up a new field with many promises and challenges in the field of simulation science by developing approaches at the interface of physics- and data-based modelling.
Surrogate-data-enriched Physics-Aware Neural Networks
Neural networks can be used as surrogates for PDE models.
Learning Free-Surface Flow with Physics-Informed Neural Networks
The interface between data-driven learning methods and classical simulation poses an interesting field offering a multitude of new applications.
Self-Learning Tuning for Post-Silicon Validation
Increasing complexity of modern chips makes design validation more difficult.
ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems\
In PSV, the task is to approximate the underlying function of the data with multiple learning algorithms, each trained on a device-specific subset, instead of improving the performance of arbitrary classifiers on the entire data set.
Evaluation of Pool-based Testing Approaches to Enable Population-wide Screening for COVID-19
29 days in the US, 71 in the UK, 25 in Singapore, 17 in Italy and 10 in Germany (ca.
Populations and Evolution Applications
From Piz Daint to the Stars: Simulation of Stellar Mergers using High-Level Abstractions
We study the simulation of stellar mergers, which requires complex simulations with high computational demands.
Distributed, Parallel, and Cluster Computing Computational Engineering, Finance, and Science
