RAPIDS Highlights
The RAPIDS SciDAC Institute for Computer Science and Data has objective of assisting Office of Science (SC) application teams in overcoming computer science and data challenges in the use of DOE supercomputing resources to achieve science breakthroughs.
The following slides contain brief overviews of recent scientific achievements:
Lagrangian Particle Tracing for Next Generation Architectures
Surrogate Modeling for Spatio-Temporal Data from Earth System Models
Accelerating Sparse Triangular Solves in Fusion Science Codes through One-Sided Communication
Integrating Human Perception with Computational Power for Guided Exploratory Data Analysis
Accelerating Event Reconstruction for Liquid Argon TPC Neutrino Detectors
Enabling Global Adjoint Tomography at scale through next-generation I/O
Multivariate, Temporal Visual Analytics for Climate Model Analysis
Accelerating Weather Research Forecasting Simulations with Deep Neural Network Surrogates
Accelerating Computational Kernels of Tokamak Simulations (with FASTMath)
Performance Optimization for Multiscale Gyrokinetic Turbulence
Accelerating HEP Event Generation and Analysis on HPC Systems
Improving Network Throughput with Global Communication Reordering
Improving Collective Reduction Performance On Manycore Architectures
Autonomic Data Movement for Data Staging-based In-Situ Workflows
Robust IO Performance Modeling in Leadership-Class Systems by Automated Change Detection
In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning