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The Risks of WebGL: Analysis, Evaluation and Detection

Alex Belkin, Nethanel Gelernter, Israel Cidon

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Tags: Computer science, nVidia, nVidia GeForce GTX 1080, Security, WebGL

May 1, 2019 by hgpu

TensorFlow.js: Machine Learning for the Web and Beyond

Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viegas, Martin Wattenberg

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Tags: Computer science, CUDA, Deep learning, Java, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, TensorFlow, WebGL

February 17, 2019 by hgpu

Optimizing Web Virtual Reality

Rabimba Karanjai

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

August 26, 2018 by hgpu

Automated Testing of Graphics Shader Compilers

Alastair F. Donaldson, Hugues Evrard, Andrei Lascu, Paul Thomson

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Tags: AMD Radeon R9 Fury, ARM, ATI, ATI Radeon HD 7700, Compilers, Computer science, GLSL, Intel, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan X, OpenGL, Rendering, Security, Shaders, WebGL

September 21, 2017 by hgpu

GPU-based visualization of domain-coloured algebraic Riemann surfaces

Stefan Kranich

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Tags: Computer science, Graphics, OpenGL, Visualization, WebGL

July 17, 2015 by hgpu

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: Performance-portable geometric search library

ArborX: A Performance Portable Search Library

FlowSeq: Generative Flow based Sequence-to-Sequence Toolkit

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Compositional Deep Learning in Futhark

MLPerf Benchmark Suite

Demystifying the MLPerf Benchmark Suite

stdgpu: Efficient STL-like Data Structures on the GPU

ikra-cpp: C++ Library for Object-oriented Programming with Structure of Arrays Layout

Memory-Efficient Object-Oriented Programming on GPUs

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Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

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Rome, Italy

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high performance computing on graphics processing units: hgpu.org

The Risks of WebGL: Analysis, Evaluation and Detection

TensorFlow.js: Machine Learning for the Web and Beyond

Optimizing Web Virtual Reality

Automated Testing of Graphics Shader Compilers

GPU-based visualization of domain-coloured algebraic Riemann surfaces

Recent source codes

Watershed analysis algorithm implementation in CUDA and OpenACC

OpenCL Performance Prediction using Architecture-Independent Features

PySPH: a Python-based SPH framework

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: Performance-portable geometric search library

FlowSeq: Generative Flow based Sequence-to-Sequence Toolkit

Compositional Deep Learning in Futhark

MLPerf Benchmark Suite

stdgpu: Efficient STL-like Data Structures on the GPU

ikra-cpp: C++ Library for Object-oriented Programming with Structure of Arrays Layout

Most viewed papers (last 30 days)

Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019