In this video from PASC18, Kamil Deja presents: Using Generative Models for Fast Cluster Simulation in TPC Detector for the ALICE Experiment. “Simulation of the events happening in the particle detector is a key component of many High Energy Physics experiments. Currently used Monte Carlo techniques allow to do it accurately, but their precision often […]
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PASC18 – Video of Alice-Agnes Gabriel on Unravelling Earthquake Dynamics through Extreme-Scale Multiphysics Simulations
In this video from the PASC18 conference in Basel, Alice-Agnes Gabriel presents: Unravelling Earthquake Dynamics through Extreme-Scale Multiphysics Simulations. “Earthquakes are highly non-linear multiscale problems, encapsulating geometry and rheology of faults within the Earth’s crust torn apart by propagating shear fracture and emanating seismic wave radiation. This talk will focus on using physics-based scenarios, modern numerical […]
PASC18 – Video of Leonardo Bautista Gomez on Easy and Efficient Multilevel Checkpointing for Extreme Scale Systems
In this video from PASC18, Leonardo Bautista Gomez from the Barcelona Supercomputing Center presents: Easy and Efficient Multilevel Checkpointing for Extreme Scale Systems. “Extreme scale supercomputers offer thousands of computing nodes to their users to satisfy their computing needs. As the need for massively parallel computing increases in industry, computing centers are being forced to […]
PASC18 – Video of Jakub Tomczak on The Success of Deep Generative Models
In this video from PASC18, Jakub Tomczak from the University of Amsterdam presents: The Success of Deep Generative Models. “Deep generative models allow us to learn hidden representations of data and generate new examples. There are two major families of models that are exploited in current applications: Generative Adversarial Networks (GANs), and Variational Auto-Encoders (VAE). […]
PASC18 – Video of Fernanda Foertter on Practical Scaling Techniques for Deep Learning
In this video from PASC18, Fernanda Foertter from NVIDIA presents: Practical Scaling Techniques for Deep Learning. “The need for large scale training of neural networks is stemming from the advent of ever growing labeled datasets in data science combined with the successes of deep learning at achieving super-human performance at pattern recognition tasks and others. […]