high performance computing on graphics processing units: hgpu.org

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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

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

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

See all packages

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high performance computing on graphics processing units: hgpu.org

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

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

Real-Time Object Tracking by CUDA-accelerated Neural Network

Recent source codes

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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