HPC and Healthcare / Life Sciences Conference Posters

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

Accelerating Chemical Shift Prediction for Large-scale Biomolecular Modeling
Accelerating Chemical Shift Prediction for Large-scale Biomolecular Modeling

Eric Wright, Student, University of Delaware

Acceleration of divide-and-conquer density tight-binding method on GPU
Acceleration of divide-and-conquer density tight-binding method on GPU

Takeshi Yoshikawa, Lecturer, Waseda University

Generative Long Short-Term Memory Network for Simulation of Genomic Data
Generative Long Short-Term Memory Network for Simulation of Genomic Data

Peter McCaffrey,  Chief Technology Officer, VastBiome

GPU acceleration of X-ray ptychography reconstruction
GPU acceleration of X-ray ptychography reconstruction

Leo Fang, Assistant Computational Scientist, Brookhaven National Lab

NanoBraggACC: Accelerating Simulations of X-ray Diffraction from a Nanocrystal Using OpenACC Directives
NanoBraggACC: Accelerating Simulations of X-ray Diffraction from a Nanocrystal Using OpenACC Directives

Pranay Reddy Kommera, Graduate Student, Los Alamos National Laboratory

OpenChem: deep learning toolkit for computational chemistry and drug design
OpenChem: deep learning toolkit for computational chemistry and drug design

Mariya Popova, Graduate Student, University of North Carolina at Chapel Hill

Optimizing Molecules for Drug Discovery with Convolutional Neural Networks
Optimizing Molecules for Drug Discovery with Convolutional Neural Networks

Jocelyn Sunseri, Graduate Student Researcher, University of Pittsburgh

Probing Protein-Peptide Structural Interactions for Peptide Inhibitor Design Using GPU Accelerated Simulations
Probing Protein-Peptide Structural Interactions for Peptide Inhibitor Design Using GPU Accelerated Simulations

Raghavender Surya Upadhyayula, Scientist, Birla Institute of Scientific Research

Fast CUDA FFM for multiple charge configurations
Fast CUDA FFM for multiple charge configurations

Bartosz Kohnke, Software Developer, MPI for Biophysical Chemistry

GPU-Accelerated NMR Signal Analysis for the Muon g-2 Experiment
GPU-Accelerated NMR Signal Analysis for the Muon g-2 Experiment

Ran Hong, Postdoc Research Associate, Argonne National Laboratory

Large scale micromagnetics simulation on multi-GPUs
Large scale micromagnetics simulation on multi-GPUs

Hiroshi Tsukahara, Researcher, High Energy Accelerator Research Organization

Old Methods Meet New Hardware: Single Event Proton Scattering Algorithms on GPUs
Old Methods Meet New Hardware: Single Event Proton Scattering Algorithms on GPUs

Kristofer Zieb, Postdoctoral Research Staff Member, Lawrence Livermore National Laboratory

Performance Optimizations of the GooFit Library
Performance Optimizations of the GooFit Library

Bradley Hittle, Senior Research Software Engineer, Ohio State University

Solving the Kuramoto Oscillator Model on Random Graphs
Solving the Kuramoto Oscillator Model on Random Graphs

Jeffrey Kelling, Scientist, Helmholtz-Zentrum Dresden - Rossendorf

Accelerating Chemical Shift Prediction for Large-scale Biomolecular Modeling
Acceleration of divide-and-conquer density tight-binding method on GPU
Generative Long Short-Term Memory Network for Simulation of Genomic Data
GPU acceleration of X-ray ptychography reconstruction
NanoBraggACC: Accelerating Simulations of X-ray Diffraction from a Nanocrystal Using OpenACC Directives
OpenChem: deep learning toolkit for computational chemistry and drug design
Optimizing Molecules for Drug Discovery with Convolutional Neural Networks
Probing Protein-Peptide Structural Interactions for Peptide Inhibitor Design Using GPU Accelerated Simulations
Fast CUDA FFM for multiple charge configurations
GPU-Accelerated NMR Signal Analysis for the Muon g-2 Experiment
Large scale micromagnetics simulation on multi-GPUs
Old Methods Meet New Hardware: Single Event Proton Scattering Algorithms on GPUs
Performance Optimizations of the GooFit Library
Solving the Kuramoto Oscillator Model on Random Graphs
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