high performance computing on graphics processing units: hgpu.org

hgpu.org » Neural networks

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

Alessandro Giusti, Dan C. Ciresan, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Artificial intelligence, Computational Complexity, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX 580

February 12, 2013 by hgpu

Extending the Computational Application of Reaction-Diffusion Chemistry by Modelling Artificial Neural Networks

James Stovold

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Tags: Biology, Chemistry, CUDA, Neural networks, nVidia, nVidia GeForce 9600 M GT

February 12, 2013 by hgpu

Implementation of Fast Artificial Neural Network for Pattern Classification on Heterogeneous System

Devendra Singh Bharangar, Amit Doeger, Yogesh Kumar Mittal

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Tags: ATI, Computer science, Heterogeneous systems, Neural networks, nVidia, OpenCL

February 6, 2013 by hgpu

Regularization and nonlinearities for neural language models: when are they needed?

Marius Pachitariu, Maneesh Sahani

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Tags: CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 680, Statistics

January 25, 2013 by hgpu

Radionuclides migration modelling using artificial neural networks and parallel computing

O.S. Hilko, S.P. Kundas, I.A. Gishkeluk

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Tags: Algorithms, Biology, CUDA, MPI, Neural networks, nVidia, nVidia GeForce 9500 GT, nVidia GeForce 9800 GT, nVidia GeForce GT 220 M

December 29, 2012 by hgpu

Acceleration of multivariate analysis techniques in TMVA using GPUs

A. Hoecker, H. McKendrick, J. Therhaag, A. Washbrook

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Tags: Biological Physics, CUDA, Neural networks, nVidia, Physics, Tesla C1060, Tesla C2050

December 16, 2012 by hgpu

Pattern Recognition with OpenCL Heterogeneous Platform

Jordan Vrtanoski, Toni Draganov Stojanovski

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, Neural networks, OpenCL, Pattern recognition

November 21, 2012 by hgpu

Facial Recognition Using Neural Networks over GPGPU

Juan Pablo Balarini, Sergio Nesmachnow, Martin Rodriguez

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 480

November 18, 2012 by hgpu

Streaming Parallel GPU Acceleration of Large-Scale filter-based Spiking Neural Networks

Leszek Slazynski, Sander Bohte

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, Neural networks, nVidia, nVidia GeForce GTX 470, OpenCL

October 9, 2012 by hgpu

Exploring Multi-level Parallelism for Large-Scale Spiking Neural Networks

Vivek K. Pallipuram, Melissa C. Smith, Nimisha Raut, Xiaoyu Ren

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, Neural networks, nVidia, Tesla M2070

September 23, 2012 by hgpu

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Paola Arce, Cristian Maureira, Roberto Bonvallet, Cesar Fernandez

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Tags: Algorithms, CUBLAS, CUDA, Finance, Linear Algebra, Machine learning, Neural networks, nVidia, Tesla M2050

September 20, 2012 by hgpu

Simulating spiking neural networks on GPU

Romain Brett

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Source codes

Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 580, Package, Python, Review

September 19, 2012 by hgpu

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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high performance computing on graphics processing units: hgpu.org

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

Extending the Computational Application of Reaction-Diffusion Chemistry by Modelling Artificial Neural Networks

Implementation of Fast Artificial Neural Network for Pattern Classification on Heterogeneous System

Regularization and nonlinearities for neural language models: when are they needed?

Radionuclides migration modelling using artificial neural networks and parallel computing

Acceleration of multivariate analysis techniques in TMVA using GPUs

Pattern Recognition with OpenCL Heterogeneous Platform

Facial Recognition Using Neural Networks over GPGPU

Streaming Parallel GPU Acceleration of Large-Scale filter-based Spiking Neural Networks

Exploring Multi-level Parallelism for Large-Scale Spiking Neural Networks

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Simulating spiking neural networks on GPU

Recent source codes

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

spotPython: Sequential Parameter Optimization in Python

Test benchmarks for CELERITY

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Redwood heterogeneous framework

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