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Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Albert Haque

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Tags: CUDA, Machine learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX 750 Ti, Package

January 8, 2015 by hgpu

Disjunctive Normal Networks

Mehdi Sajjadi, Mojtaba Seyedhosseini, Tolga Tasdizen

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

January 2, 2015 by hgpu

Spectral classification using convolutional neural networks

Pavel Hala

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Tags: Astrophysics, Computer science, CUDA, Instrumentation and Methods for Astrophysics, Machine learning, Neural and Evolutionary Computing, nVidia, Thesis

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

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

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

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

Hongsheng Li, Rui Zhao, Xiaogang Wang

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, Tesla K40

December 16, 2014 by hgpu

MatConvNet – Convolutional Neural Networks for MATLAB

Andrea Vedaldi, Karel Lenc

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

December 16, 2014 by hgpu

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Minjie Wang, Tianjun Xiao, Jianpeng Li, Jiaxing Zhang, Chuntao Hong, Zheng Zhang

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Neural networks, nVidia

December 15, 2014 by hgpu

Graph Processing on GPU

Zhang Jingbo

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Tags: Algorithms, Computer science, CUDA, Data mining, Graph theory, Machine learning, nVidia, nVidia GeForce 9400 GT, nVidia GeForce GT 330, nVidia GeForce GT 520, Thesis

December 14, 2014 by hgpu

Real-Time Grasp Detection Using Convolutional Neural Networks

Joseph Redmon, Anelia Angelova

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Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Tesla K20

December 12, 2014 by hgpu

Theano-based Large-Scale Visual Recognition with Multiple GPUs

Weiguang Ding, Ruoyan Wang, Fei Mao, Graham Taylor

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Tags: Computer science, CUDA, Data parallelism, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

December 9, 2014 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Disjunctive Normal Networks

Spectral classification using convolutional neural networks

Automatic Tuning of Local Memory Use on GPGPUs

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Purine: A bi-graph based deep learning framework

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

MatConvNet – Convolutional Neural Networks for MATLAB

Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning

Graph Processing on GPU

Real-Time Grasp Detection Using Convolutional Neural Networks

Theano-based Large-Scale Visual Recognition with Multiple GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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