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Automatic classification of object code using machine learning

John Clemens

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Tags: Computer science, CUDA, Machine learning, nVidia, Security

August 14, 2015 by hgpu

Processing Markov Logic Networks with GPUs

Carlos Alberto Martinez-Angeles, Ines Dutra, Vitor Santos Costa, Jorge Buenabad-Chavez

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Tags: Computer science, CUDA, Databases, Machine learning, nVidia, Tesla K40

August 14, 2015 by hgpu

A Parallel Implementation of the Self Organising Map using OpenCL

Gavin Davidson

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Tags: Algorithms, Computer science, Machine learning, nVidia, nVidia GeForce GTX 590, OpenCL, Package, Self-organizing map

August 11, 2015 by hgpu

Optimising Reconfigurable Systems for Real-time Applications

Thomas Chun Pong Chau

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Tags: Algorithms, Computer science, CUDA, FPGA, Machine learning, Mixed precision, nVidia, Package, Tesla C2070, Thesis

August 7, 2015 by hgpu

Efficient Convolutional Patch Networks for Scene Understanding

Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler

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Tags: CNN, Computer science, Deep learning, Machine learning, OpenCL, Package

July 24, 2015 by hgpu

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Baoguang Shi, Xiang Bai, Cong Yao

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Tesla K40

July 24, 2015 by hgpu

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

Keiron O'Shea

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 580

July 24, 2015 by hgpu

On the use of deep Boltzmann machines for road signs classification

Carlo D'Eramo

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Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Python, Tesla C1060, Thesis

July 22, 2015 by hgpu

Adaptive parallelism mapping in dynamic environments using machine learning

Murali Krishna Emani

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Tags: Computer science, Machine learning, OpenMP, Performance, Thesis

July 15, 2015 by hgpu

Towards Good Practices for Very Deep Two-Stream ConvNets

Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, MPI, nVidia, OpenMPI, Package

July 10, 2015 by hgpu

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, OpenCL, Package, Python

July 6, 2015 by hgpu

Parallel Sparse Coding for Seafloor Image Analysis

Genlang Chen, Chenggang Lai, Miaoqing Huang

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Tags: CUDA, Image processing, Intel Xeon Phi, Machine learning, nVidia, Tesla K20

July 3, 2015 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

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high performance computing on graphics processing units: hgpu.org

Automatic classification of object code using machine learning

Processing Markov Logic Networks with GPUs

A Parallel Implementation of the Self Organising Map using OpenCL

Optimising Reconfigurable Systems for Real-time Applications

Efficient Convolutional Patch Networks for Scene Understanding

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

On the use of deep Boltzmann machines for road signs classification

Adaptive parallelism mapping in dynamic environments using machine learning

Towards Good Practices for Very Deep Two-Stream ConvNets

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Parallel Sparse Coding for Seafloor Image Analysis

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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