Workshops

Predictive Plasma Simulations at the Exascale: Scalable Algorithms for HPC and Data Analytics

Notions of Efficiency – the Role of Algorithm and Performance Engineering

Sparse sampling methods for large scale experimental data

Big Compute: Under the Hood

Making Sense of our Universe with Supercomputers

Resilient algorithmics: How much relevant information can be extracted from my data?

Scalable approximation algorithms for kernel matrices

Big Data at the LHC

From high-performance computing to big-data analytics of materials science and back

Polynomial approximation via compressed sensing of high dimension systems

Accurate reconstruction of sparsely sub sampled data

Data communications and analysis in simulation of plasma turbulence on a five-dimensional phase space

Localized operator compression for elliptic operators

Representations of operators in MADNESS (Multiresolution ADaptive Numerical Environment for Scientific Simulation)

Solving Multiscale Kinetic Equations with Uncertainty by Asymptotic-Preserving Methods with Sparse Grids.

Stochastic algorithms for high dimensional PDEs

Tensor network skeletonization

Scalable Data Science and Apache Flink: Key Challenges and (Some) Solutions

Scalability and Algorithm-Based Fault Tolerance for Plasma Physics Simulations with GENE

An Overview of Tensor Decompositions for Data Analysis, with Emphasis on Computation and Scalability

Compression algorithms for Electronic Structure Computations

Vlasov simulations in 6D phase space based on compressed data formats

Making Every Bit Count: Variable Precision?

Bridging big data and small data: a new effort in immunophysics

Physics-based modeling of materials and uncertainty quantification as drivers for exascale computing