high performance computing on graphics processing units: hgpu.org

hgpu.org » OpenGL

Optimizing Web Virtual Reality

Rabimba Karanjai

View

Tags: Benchmarking, Computer science, Java, OpenGL, Rendering, Thesis, Virtual reality, WebGL

August 26, 2018 by hgpu

Cross-Compiling Shading Languages

Lukas Hermanns

View

Tags: 3D Graphics and Realism, Algorithms, DirectX, GLSL, HLSL, OpenGL, Real-time graphics, Rendering, Thesis

July 15, 2018 by hgpu

Migrating from OpenGL ES to Vulkan

Imagination Technologies Limited

View

Tags: 3D Graphics and Realism, OpenGL, Rendering, Vulkan

June 28, 2018 by hgpu

Neural scene representation and rendering

S. M. Ali Eslami, Danilo J. Rezende, Frederic Besse, Fabio Viola, Ari S. Morcos, Marta Garnelo, Avraham Ruderman, Andrei A. Rusu, Ivo Danihelka, Karol Gregor, David P. Reichert, Lars Buesing, Theophane Weber, Oriol Vinyals, Dan Rosenbaum, Neil Rabinowitz, Helen King, Chloe Hillier, Matt Botvinick, Daan Wierstra, Koray Kavukcuoglu, Demis Hassabis

View

Tags: Computer science, Deep learning, Neural networks, nVidia, OpenGL, Package, Rendering, Tesla K80

June 17, 2018 by hgpu

A Comparison between GPU-based Volume Ray Casting Implementations: Fragment Shader, Compute Shader, OpenCL, and CUDA

Francisco Sans, Rhadames Carmona

View

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660, OpenCL, OpenGL, Performance, Rendering

March 31, 2018 by hgpu

Equalizer 2.0 – Convergence of a Parallel Rendering Framework

Stefan Eilemann, David Steiner, Renato Pajarola

View

Tags: Algorithms, Computer science, Graphics, nVidia, nVidia GeForce GTX 970, OpenGL, Package, Rendering, Virtual reality, Visualization

March 3, 2018 by hgpu

Rubus: A compiler for seamless and extensible parallelism

Muhammad Adnan, Faisal Aslam, Zubair Nawaz, Syed Mansoor Sarwar

View

Tags: Aparapi, Benchmarking, Computer science, CUDA, Java, Matrix multiplication, nVidia, nVidia GeForce GT 630 M, OpenCL, OpenGL, Package

January 6, 2018 by hgpu

STAR-RT: Visual attention for real-time video game playing

Iuliia Kotseruba, John K. Tsotsos

View

Tags: AMD FirePro W7000, Artificial intelligence, ATI, Computer science, Games, GLSL, OpenCL, OpenGL

December 3, 2017 by hgpu

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

Maxence Reberol, Bruno Levy

View

Tags: Computer science, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, Traingular meshes

November 26, 2017 by hgpu

GPU Pro 7: Advanced Rendering

Wolfgang Engel (editor)

View

Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, nVidia, OpenGL, Package, Rendering, Visualization

November 26, 2017 by hgpu

Radeon PRO Solid State Graphics (SSG) API User Manual

AMD

View

Tags: AMD Radeon Pro SSG, ATI, Computer science, DirectX, OpenCL, OpenGL

November 7, 2017 by hgpu

On Pre-Trained Image Features and Synthetic Images for Deep Learning

Stefan Hinterstoisser, Vincent Lepetit, Paul Wohlhart, Kurt Konolige

View

Tags: Computer science, Computer vision, Deep learning, OpenGL, Rendering

October 31, 2017 by hgpu

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Integer sorting on multicore

A study of integer sorting on multicores

See all packages

* * *

* * *

2019

February

25-28

Shanghai, China

International Conference on Image, Video and Signal Processing (IVSP), 2019

2018

November

20-22

Khalifa University, Abu Dhabi, UAE

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

2018

December

13-15

Wellington, New Zealand

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

2018

December

10-12

Wellington, New Zealand

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

2018

December

13-15

Wellington, New Zealand

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018

+

HGPU group © 2010-2018 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: