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Improving the speed of neural networks on CPUs

Vincent Vanhoucke, Andrew Senior, Mark Z. Mao

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Tags: Computer science, CUDA, Neural networks, nVidia, Speech recognition, Tesla C2070, Tutorial

December 28, 2011 by hgpu

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

Micah Richert, Jayram Moorkanikara Nageswaran, Nikil Dutt, Jeffrey L. Krichmar

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Source codes

Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C1060

December 19, 2011 by hgpu

Speed sign detection and recognition by convolutional neural networks

Maurice Peemen, Bart Mesman, Henk Corporaal

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Image recognition, Neural networks, nVidia, nVidia GeForce GTX 460

December 15, 2011 by hgpu

Fast thermal simulation of 2D/3D integrated circuits exploiting neural networks and GPUs

Alessandro Vincenzi, Arvind Sridhar, Martino Ruggiero, David Atienza

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

December 14, 2011 by hgpu

Fast Neural Network Training on General Purpose Computers

Harshit Kharbanda, Roy H. Campbell

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Tags: Benchmarking, Computer science, CUDA, Neural networks, nVidia, nVidia Quadro FX 1800

December 14, 2011 by hgpu

Evolving Neural Networks on GPUs

Johannes Hofmann

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Finance, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla C1060

December 7, 2011 by hgpu

GPU Implementation of Spiking Neural Networks for Color Image Segmentation

Ermai Xie, Martin McGinnity, QingXiang Wu, Jianyong Cai, Rontai Cai

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Tags: CUDA, Image processing, Neural networks, nVidia, nVidia Quadro FX 3800

November 27, 2011 by hgpu

Flexible neuronal network simulation framework using code generation for NVidia CUDA

Thomas Nowotny

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Tags: Bioinformatics, Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia Quadro FX 5800, Poster

October 26, 2011 by hgpu

Evaluation of GPU Architectures Using Spiking Neural Networks

Vivek K. Pallipuram, Mohammad A. Bhuiyan, Melissa C. Smith

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Tags: ATI, ATI Radeon HD 5870, Computer science, Neural networks, nVidia, OpenCL, Optimization, Performance, Presentation, Tesla C2050

October 10, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

Flexible, high performance convolutional neural networks for image classification

Dan C. Ciresan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Benchmarking, Computer science, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580

October 5, 2011 by hgpu

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Li Liang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, OpenCL, Optimization

October 3, 2011 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

Improving the speed of neural networks on CPUs

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

Speed sign detection and recognition by convolutional neural networks

Fast thermal simulation of 2D/3D integrated circuits exploiting neural networks and GPUs

Fast Neural Network Training on General Purpose Computers

Evolving Neural Networks on GPUs

GPU Implementation of Spiking Neural Networks for Color Image Segmentation

Flexible neuronal network simulation framework using code generation for NVidia CUDA

Evaluation of GPU Architectures Using Spiking Neural Networks

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Flexible, high performance convolutional neural networks for image classification

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Recent source codes

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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