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To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Vajira Thambawita, Roshan Ragel, Dhammika Elkaduwe

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Performance, String matching

December 30, 2014 by hgpu

Automatic Tuning of Local Memory Use on GPGPUs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Benchmarking, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla M2090

December 26, 2014 by hgpu

Accelerating Correlation Power Analysis Using Graphics Processing Units

Hasindu Gamaarachchi, Roshan Ragel, Darshana Jayasinghe

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, Performance, Security, Tesla C2075

December 26, 2014 by hgpu

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan

December 26, 2014 by hgpu

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Shohidul Islam, Cheol-Hong Kim, Jong-Myon Kim

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, Signal processing

December 26, 2014 by hgpu

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

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Tags: Algorithms, CNN, Computer science, CUDA, FFT, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Package, Tesla K40

December 26, 2014 by hgpu

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

Michael Edward Bauer

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Package, Tesla K20, Tesla M2090, Thesis

December 22, 2014 by hgpu

Purine: A bi-graph based deep learning framework

Min Lin, Shuo Li, Xuan Luo, Shuicheng Yan

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia

December 22, 2014 by hgpu

Manycore processing of repeated k-NN queries over massive moving objects observations

Francesco Lettich, Salvatore Orlando, Claudio Silvestri

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Tags: Computer science, CUDA, Data Structures and Algorithms, Databases, Nearest neighbour, nVidia, nVidia GeForce GTX 580

December 22, 2014 by hgpu

GPU Pro 5: Advanced Rendering Techniques

Wolfgang Engel

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Tags: 3D Graphics and Realism, ATI, Computer science, nVidia, OpenCL, OpenGL, Rasterization, Raytracing, Rendering

December 22, 2014 by hgpu

GPGPU-Sim

Filip Andersson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Tesla C2050, Thesis

December 22, 2014 by hgpu

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian

Sankha Baran Dutta

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Tags: Ant colony optimization, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Thesis, Vehicular traffic

December 22, 2014 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Automatic Tuning of Local Memory Use on GPGPUs

Accelerating Correlation Power Analysis Using Graphics Processing Units

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

Purine: A bi-graph based deep learning framework

Manycore processing of repeated k-NN queries over massive moving objects observations

GPU Pro 5: Advanced Rendering Techniques

GPGPU-Sim

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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