high performance computing on graphics processing units: hgpu.org

hgpu.org » Neural networks

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

Xiao-Xi Chen, Ming-Hui Shi, H. de Garis

Tags: Computer science, Computer vision, CUDA, Image recognition, Neural networks, nVidia

April 30, 2011 by hgpu

Using parallel GPU architecture for simulation of planar I/F networks

Jan-Phillip Tiesel, Anthony S. Maida

Tags: Computer science, Neural networks, Shaders

April 23, 2011 by hgpu

Poster: GPU-accelerated artificial neural network for QSAR modeling

Edward W. Lowe Jr., Nils Woetzel, Jens Meiler

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Tags: ATI, ATI Radeon HD 5970, Biology, Neural networks, nVidia, nVidia GeForce GTX 470, OpenCL, Poster, Tesla C1060, Tesla C2050

April 1, 2011 by hgpu

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Mark Van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

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Tags: Computer science, CUDA, CULA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 295, Tesla C1060

March 20, 2011 by hgpu

Performance and Scalability of GPU-Based Convolutional Neural Networks

Daniel Strigl, Klaus Kofler, Stefan Podlipnig

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Tags: Computer science, CUDA, Neural networks, nVidia

March 8, 2011 by hgpu

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition

Dan Claudiu Ciresan, Ueli Meier, Luca Maria Gambardella, Juergen Schmidhuber

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Tags: Artificial intelligence, CUDA, Image processing, Image recognition, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX 280

February 9, 2011 by hgpu

Deep, Big, Simple Neural Nets for Handwritten Digit Recognition

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

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Tags: Artificial intelligence, CUDA, Image processing, Image recognition, Neural and Evolutionary Computing, Neural networks, nVidia

February 9, 2011 by hgpu

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

Andreas Fidjeland, Etienne B. Roesch, Murray P. Shanahan, Wayne Luk

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Source codes

Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, Package, Tesla C1060

February 5, 2011 by hgpu

Accelerating Large-Scale Convolutional Neural Networks with Parallel Graphics Multiprocessors

Dominik Scherer, Hannes Schulz, Sven Behnke

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 285

January 2, 2011 by hgpu

Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture

Gustavo Poli, Jose Hiroki Saito, Joao F. Mari, Marcelo R. Zorza

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Tags: CUDA, Image processing, Image recognition, Neural networks, nVidia, nVidia GeForce 8800 GTX, Video tracking

December 24, 2010 by hgpu

SOMGPU: An unsupervised pattern classifier on Graphical Processing Unit

R. D. Prabhu

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Tags: Computer science, DirectX, Neural networks, nVidia, nVidia GeForce 6150, Self-organizing map

December 8, 2010 by hgpu

Graphics Hardware Implementation of the Parameter-Less Self-organising Map

Alexander Campbell, Erik Berglund, Alexander Streit

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Tags: Cg, Computer science, Neural networks, nVidia, nVidia GeForce 6800, Self-organizing map

November 30, 2010 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

Using parallel GPU architecture for simulation of planar I/F networks

Poster: GPU-accelerated artificial neural network for QSAR modeling

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Performance and Scalability of GPU-Based Convolutional Neural Networks

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition

Deep, Big, Simple Neural Nets for Handwritten Digit Recognition

NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs

Accelerating Large-Scale Convolutional Neural Networks with Parallel Graphics Multiprocessors

Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture

SOMGPU: An unsupervised pattern classifier on Graphical Processing Unit

Graphics Hardware Implementation of the Parameter-Less Self-organising Map

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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