high performance computing on graphics processing units: hgpu.org

hgpu.org » Neural networks

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

A GPU-based Method for Computing Eigenvector Centrality of Gene-expression Networks

Ahmed Shamsul Arefin, Regina Berretta, Pablo Moscato

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Tags: Computer science, CUDA, Neural networks, nVidia, Tesla C2050

June 16, 2013 by hgpu

Real-Time Object Tracking by CUDA-accelerated Neural Network

Mikhail S. Tarkov, Sergey V. Dubynin

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Tags: Algorithms, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce 9800 GT

May 11, 2013 by hgpu

A General-Purpose GPU Reservoir Computer

Tureiti Keith

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

April 22, 2013 by hgpu

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

Klaus Kofler, Ivan Grasso, Biagio Cosenza, Thomas Fahringer

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Task scheduling

April 21, 2013 by hgpu

A Massively Parallel Associative Memory Based on Sparse Neural Networks

Zhe Yao, Vincent Gripon, Michael G. Rabbat

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Tags: Artificial intelligence, Computer science, CUDA, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla C1060

March 31, 2013 by hgpu

Efficiency of Parallelization of Neural Network Algorithm on Graphic Cards

Dariusz Konieczny, Karol Radziszewski

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia Quadro FX 3700 M, Tesla T10

March 16, 2013 by hgpu

Utilizing Graphics Processing Units for Network Anomaly Detection

Jonathan D. Hersack

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 280, Security, Thesis

February 27, 2013 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

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

A GPU-based Method for Computing Eigenvector Centrality of Gene-expression Networks

Real-Time Object Tracking by CUDA-accelerated Neural Network

A General-Purpose GPU Reservoir Computer

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

A Massively Parallel Associative Memory Based on Sparse Neural Networks

Efficiency of Parallelization of Neural Network Algorithm on Graphic Cards

Utilizing Graphics Processing Units for Network Anomaly Detection

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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