Poster Gallery

Explore A Broad Range Of GPU Posters

  Explore over 140 research posters detailing how the brightest minds from a range of topics and industries are accelerating applications with the power of GPUs. Please sign up to view high resolution PDF.

  • Accelerated Data Science

    CheetahDB: A System for High-Throughput Database Processing on GPUs

    Chengcheng Mou, University of South Florida

  • Algorithms / Numerical Techniques

    A New Convolution Algorithm to Leverage Tensor Cores

    Mickaël Seznec, Thales / Centralesupelec

    Tensor Core Accelerated Sparse GEMM

    Orestis Zachariadis, University of Cordoba

     

    Efficient 3D Convolutional Network Design for Human Instance-Level Video Action Recognition

    Inwoong Lee, Artificial Intelligence Research Institute (AIRI)

    A Software Systolic Array on GPUs

    Mohamed Wahib, AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology  

    GraphDefense: Toward Robust Large-Scale Graph Convolutional Network

    Xiaoyun Wang, University of California, Davis

    Fromage optimiser for deep neural networks

    Jeremy Bernstein, California Institute of Technology

    Hybrid Option Pricing through AI and GPU-Powered SDEs Solvers

    Pawel Przybyłowicz, AGH University of Science and Technology

  • Autonomous Machines

    MemEAPF for Mobile Robot Path Planning on Jetson Platform

    Ulises Orozco-Rosas, CETYS Universidad  

    Sim-to-Real: Virtual Guidance for Robot Navigation

    Chun-Yi Lee, National Tsing Hua University

    Mobile Manipulation Toward Cleaning Dining Tables

    Ka-Shing Chung, National University of Singapore

    Beyond-Line-of-Sight (BLOS) Perception System for Autonomous Vehicles

    Chanyoung Chung, KAIST (Korea Advanced Institute of Science and Technology)

  • Climate / Weather / Ocean Modeling

  • Computational Fluid Dynamics

    Toward Optimal Implementation of Lattice Boltzmann CFD Simulator for Multi-GPU Clusters

    Jakub Klinkovský, Department of Mathematics, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University, Prague

    An Improved Immersed Boundary-Lattice Boltzmann Method for Incompressible Fluid-Flow Simulations on GPU

    Pavel Eichler, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University, Prague

    Performance Comparison of Search for Neighbor-Particle in MPS on Xeon, Xeon Phi and GPU

    Takaaki Miyajima, RIKEN Center for Computational Science

  • Computational Physics

    N-Body Simulation of Binary Star Mass Transfer

    Mason McCallum, Tarleton State University

    Explosive DGX Performance for Weapon Component Modeling

    Dan Ibanez, Sandia National Laboratories

    Deep-Learning Model for Finding New Superconductors

    Tomohiko Konno, National Institute of Information and Communications Technology

  • Deep Learning & Data Science

    CapsNet-Lite: A Lightweight and High Performance CapsNet Architecture

    Francisco José García, Universidad Rey Juan Carlos

    Multi-Task Learning for Sparse Sensor Body Tracking

    Aditya Tewari, Xsens Technologies

    Adversarial Learning of Deepfakes in Financial Accounting

    Marco Schreyer, University of St. Gallen

    Intelligent Risk Scenario Creation

    Amit Kalele, Tata Consultancy Services Limited

    Learning Human Objectives by Evaluating Hypothetical Behavior

    Siddharth Reddy, University of California at Berkeley

    How Humans Leverage Machines for Quick Response in High-Demand Customer Service Environment

    Weicheng Liu, Wells Fargo

  • Deep Learning Training at Scale

    Knowledge Transfer Graph for Deep Collaborative Learning

    Hironobu Fujiyoshi, Chubu University

  • Design & Engineering

    N-body Adaptive Optimization of Lattice Towers

    Jaryd Domine, Tarleton State University

  • Frameworks / Libraries / Runtimes

  • Genomics

    Rapid Pathogen Genomics using Nanopore Sequencing and GPUs

    Devin Drown, University of Alaska Fairbanks

  • HPC & AI

    Turbulence Forecasting via Neural ODEs

    Gavin Portwood, Los Alamos National Laboratory

    Reynolds-Averaged Turbulence Modeling Using Neural Networks with Grid Information

    Huiying Ren, Computer Network Information Center, Chinese Academy of Sciences

    Container-Based Artificial Intelligence Applications Deployment Platform for GPU High Performance Computing Clusters

    Rongqiang Cao, Computer Network Information Center, Chinese Academy of Sciences

    TNL: Template Numerical Library for Modern Parallel Architectures

    Tomáš Oberhuber, Czech Technical University in Prague

    Data Mining Pipeline for Predictive Synthesis of Advanced Materials

    Olga Kononova, University of California, Berkeley

    Applications of Convolutional Neural Network to the Important Earth Science Problems

    Daisuke Sugiyama, Japan Agency for Marine-Earth Science and Technology

    Implementation of Artificial Intelligence (AI)/Deep Learning Disruption Predictor into a Plasma Control System

    Ge Dong, Princeton Plasma Physics Laboratory

  • Inference, Optimization, & Deployment

    Tiki: A Prototype Virtual Assistant for VQA

    Brent Biseda, Seneca Resources