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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

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

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

See all packages

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high performance computing on graphics processing units: hgpu.org

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

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

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

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Most viewed papers (last 30 days)