High Performance Computing

Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis.- Machine-Learning-Based Control of Perturbed and Heated Channel Flows.- Novel DNNs for Stiff ODEs with Applications to Chemically Reacting Flows.- Lettuce: PyTorch-based Lattice Boltzmann Framework.- Reservoir computing in reduced order modeling for chaotic dynamical systems.- Film cooling prediction and optimization based on deconvolution neural network.- Turbomachinery Blade Surrogate Modeling using Deep Learning.- A Data-driven Wall-shear Stress Model for LES using Gradient Boosted Decision Trees.- Nonlinear mode decomposition and reduced-order modeling for three-dimensional cylinder flow by distributed learning on Fugaku.- Using physics-informed enhanced super-resolution generative adversarial networks to reconstruct mixture fraction statistics of turbulent jet flows.- HPC I/O in the Data Center.- Toward a Workflow for Identifying Jobs with Similar I/O Behavior Utilizing Time Series Analysis.- H3: An Application-Level, Low-Overhead Object Store.- Compiler-assisted Correctness Checking and Performance Optimization for HPC.- Automatic partitioning of MPI operations in MPI+OpenMP applications.- heimdallr: Improving Compile Time Correctness Checking for Message Passing with Rust.- Potential of Interpreter Specialization for Data Analysis.- Refactoring for Performance with Semantic Patching: Case Study with Recipes.- Negative Perceptions About the Applicability of Source-to-Source Compilers in HPC: A Literature Review.- Machine Learning on HPC Systems.- Automatic Tuning of Tensorflow's CPU Backend using Gradient-Free Optimization Algorithms.- MSM: Multi-Stage Multicuts for Scalable Image Clustering.- OmniOpt - a tool for hyperparameter optimization on HPC.- Parallel/distributed intelligent hyperparameters search for GANs.- Machine learning for generic energy models of high performance