High Performance Computing Conference Posters

Check out this collection of posters to see how researchers in HPC and Supercomputing are accelerating their work with the power of GPUs.

Accelerating the Solar Wind with OpenACC
Accelerating the Solar Wind with OpenACC

Ronald Caplan, Computational Scientist, Predictive Science Inc.

Improving Particle Discrimination in Dark Matter Detection Experiments Using Neural Networks
Improving Particle Discrimination in Dark Matter Detection Experiments Using Neural Networks

Brendon Matusch, Deep Learning Research Intern, SNOLAB  

Deep Learning for Detecting Gravitational Waves
Deep Learning for Detecting Gravitational Waves

Daniel George,  AI Research Scientist, Google X

GPU Accelerated CFD Flow Solver - Code LEO
GPU Accelerated CFD Flow Solver - Code LEO

Michael Ni, Product Manager, ADS CFD Inc

Boosting GCN Application with Batched Sparse Matrix Multiplication
Boosting GCN Application with Batched Sparse Matrix Multiplication

Yusuke Nagasaka , Student, Tokyo Institute of Technology  

CUDA-Accelerated Matrix-Free Solver for Marginalized Graph Kernels
CUDA-Accelerated Matrix-Free Solver for Marginalized Graph Kernels

Yu-Hang Tang, Luis W. Alvarez Postdoctoral Fellow, Lawrence Berkeley National Laboratory  

Enabling an On Premise NVIDIA GPU Cloud with Kubernetes
Enabling an On Premise NVIDIA GPU Cloud with Kubernetes

John Lockman, AI Research, DellEMC

LTFB: Training Neural Networks at Sierra Scale
LTFB: Training Neural Networks at Sierra Scale

Sam Ade Jacobs, Computer Scientist, Lawrence Livermore National Lab

MixSOM: Mixed Precision Self-Organizing Maps for Digital Rock Physics
MixSOM: Mixed Precision Self-Organizing Maps for Digital Rock Physics

Rached Abdelkhalak, Research Scientist, KAUST

Taskify Everything - FMM Meets Whippletree
Taskify Everything - FMM Meets Whippletree

Ivo Kabadshow, Scientist, Juelich Supercomputing Centre

Using GPU for accelerate dataset classification
Using GPU for accelerate dataset classification

Marcelo de Caux, Student, High Energy Universidade Federal Fluminense - UFF

Work-Efficient Parallel Non-Maximum Suppression for Tegra Platforms
Work-Efficient Parallel Non-Maximum Suppression for Tegra Platforms

Paolo Oranges, Senior Software Architect, Herta Security

Classification and Metadata Extraction Using Machine Learning
Classification and Metadata Extraction Using Machine Learning

Parminder Kaur, Senior Data Scientist, Agile Data Decisions

Enhanced Geologic Modeling Capability via GPU-Accelerated Visualization at Ultra-High Resolution
Enhanced Geologic Modeling Capability via GPU-Accelerated Visualization at Ultra-High Resolution

Ingrid Tobar, Postdoc Sr. Data Scientist, Anadarko Petroleum Corporation

Exploiting IGI Technique for Tomography Using Artificial Intelligence
Exploiting IGI Technique for Tomography Using Artificial Intelligence

Lionel Boillot, HPC Software Development Engineer, Total

AMR Framework with multiple GPUs to Realize Effective High-Resolution Simulations
AMR Framework with multiple GPUs to Realize Effective High-Resolution Simulations

Takashi Shimokawabe, Associate Professor, The University of Tokyo

Exploiting GPUDirect Technology and Hardware Multicast for Streaming and Deep Learning Applications
Exploiting GPUDirect Technology and Hardware Multicast for Streaming and Deep Learning Applications

Ching-Hsiang Chu, Graduate Research Associate, The Ohio State University

Towards Unified Tasking on CPUs and GPUs
Towards Unified Tasking on CPUs and GPUs

Laura Morgenstern, PhD Student Computer Science, Julich Supercomputing Centre

Accelerating the Solar Wind with OpenACC
Improving Particle Discrimination in Dark Matter Detection Experiments Using Neural Networks
Deep Learning for Detecting Gravitational Waves
GPU Accelerated CFD Flow Solver - Code LEO
Boosting GCN Application with Batched Sparse Matrix Multiplication
CUDA-Accelerated Matrix-Free Solver for Marginalized Graph Kernels
Enabling an On Premise NVIDIA GPU Cloud with Kubernetes
LTFB: Training Neural Networks at Sierra Scale
MixSOM: Mixed Precision Self-Organizing Maps for Digital Rock Physics
Taskify Everything - FMM Meets Whippletree
Using GPU for accelerate dataset classification
Work-Efficient Parallel Non-Maximum Suppression for Tegra Platforms
Classification and Metadata Extraction Using Machine Learning
Enhanced Geologic Modeling Capability via GPU-Accelerated Visualization at Ultra-High Resolution
Solving the Kuramoto Oscillator Model on Random Graphs
AMR Framework with multiple GPUs to Realize Effective High-Resolution Simulations
Exploiting GPUDirect Technology and Hardware Multicast for Streaming and Deep Learning Applications
Towards Unified Tasking on CPUs and GPUs
Engage
Discover
More