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hgpu.org » nVidia GeForce 8200 M

Techniques for designing GPGPU games

Mark Joselli, Jose Ricardo da Silva Junior, Marcelo Zamith, Esteban Clua, Mateus Pelegrino, Evandro Mendonca, Eduardo Soluri
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October 23, 2012 by hgpu

An adaptative game loop architecture with automatic distribution of tasks between CPU and GPU

Mark Joselli, Marcelo Zamith, Esteban Clua, Anselmo Montenegro, Regina Leal-Toledo, Aura Conci, Paulo Pagliosa, Luis Valente, Bruno Feijo
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September 19, 2011 by hgpu

A Hybrid Method for Computing Apparent Ridges

Eric Jardim, Luiz Henrique de Figueiredo
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August 2, 2011 by hgpu

GpuWars: Design and Implementation of a GPGPU Game

Mark Joselli, Esteban Clua
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April 5, 2011 by hgpu

Recent source codes

Tornado

Tornado

Using Compiler Snippets to Exploit Parallelism on Heterogeneous Hardware: A Java Reduction Case Study
pocl: Portable Computing Language

pocl: Portable Computing Language

Exploiting Task Parallelism with OpenCL: A Case Study
TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

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 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

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

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

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications
CL-kmeans: Efficient k-Means in OpenCL

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

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

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
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