high performance computing on graphics processing units: hgpu.org

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Implementing Neural Networks Efficiently

Ronan Collobert, Koray Kavukcuoglu, Clement Farabet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural networks, nVidia, Tesla M2090

December 29, 2013 by hgpu

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

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Tags: Computer science, Computer vision, CUDA, Data parallelism, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K20

December 24, 2013 by hgpu

Single Server Multi-GPU Training of ConvNets

Omry Yadan, Keith Adams, Yaniv Taigman, Marc'Aurelio Ranzato

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Tags: Computer science, Computer vision, Machine learning, Neural networks

December 23, 2013 by hgpu

GPU and CPU Cooperative Accelerated Road Detection

Peng Xiong, Cheng Xu, Zheng Tian, Tao Li

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Tags: Computer science, Computer vision, Neural networks, OpenCV

December 3, 2013 by hgpu

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Roger V. Hoang, Devyani Tanna, Laurence C. Jayet Bray, Sergiu M. Dascalu, Frederick C. Harris Jr.

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Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Tesla C2050

September 14, 2013 by hgpu

GPU-based simulation of brain neuron models

H. A. Du Nguyen

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Tags: CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GT 640, Review, Tesla C2075, Thesis

September 7, 2013 by hgpu

Multiple Time Scales Recurrent Neural Network for Complex Action Acquisition

Martin Peniak, Davide Marocco, Jun Taniy, Yuichi Yamashitay, Kerstin Fischerz, Angelo Cangelosi

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Tags: Computer science, CUDA, Neural networks, nVidia, Package

August 27, 2013 by hgpu

Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit

Giandomenico Amendola, Giovanni Angiulli, Emilio Arnieri, Luigi Boccia, Domenico De Carlo

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Tags: CUDA, Electrodynamics, Neural networks, nVidia, Tesla C2070

July 25, 2013 by hgpu

GPU Implementation of Real-Time Biologically Inspired Face Detection using CUDA

Zeinab Farhoudi, Ali Broumandnia, Elham Askary, Sara Motamed

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Tags: Computer science, Computer vision, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTX

July 8, 2013 by hgpu

Artificial Neural Network Simulation on CUDA

John Pendlebury, Huanhuan Xiong, Ray Walshe

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 480

June 21, 2013 by hgpu

Deep learning with COTS HPC systems

Adam Coates, Brody Huval, Tao Wang, David J. Wu, Andrew Y. Ng, Bryan Catanzaro

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Tags: Computer science, CUDA, Machine learning, MPI, Neural networks, nVidia, nVidia GeForce GTX 680

June 19, 2013 by hgpu

Multicore and GPU Parallelization of Neural Networks for Face Recognition

Altaf Ahmad Huqqani, Erich Schikuta, Sicen Ye, Peng Chen

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, OpenMP, Tesla C1060

June 16, 2013 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

See all packages

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high performance computing on graphics processing units: hgpu.org

Implementing Neural Networks Efficiently

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Single Server Multi-GPU Training of ConvNets

GPU and CPU Cooperative Accelerated Road Detection

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

GPU-based simulation of brain neuron models

Multiple Time Scales Recurrent Neural Network for Complex Action Acquisition

Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit

GPU Implementation of Real-Time Biologically Inspired Face Detection using CUDA

Artificial Neural Network Simulation on CUDA

Deep learning with COTS HPC systems

Multicore and GPU Parallelization of Neural Networks for Face Recognition

Recent source codes

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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