high performance computing on graphics processing units: hgpu.org

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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

Bayesian neural networks for detecting epistasis in genetic association studies

Andrew L Beam, Alison Motsinger-Reif, Jon Doyle

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Tags: Bayesian, Biology, CUDA, CULA, Neural networks, nVidia, Package, Python

December 15, 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

MLitB: Machine Learning in the Browser

Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling

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Tags: Algorithms, Computer science, Distributed computing, Heterogeneous systems, Java, Machine learning, Neural networks, Package

December 9, 2014 by hgpu

Neural Networks through Shared Maps in Mobile Devices

William Raveane, Maria Angelica Gonzalez Arrieta

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Tags: Computer science, Computer vision, Image recognition, Machine learning, Neural networks, OpenGL

December 7, 2014 by hgpu

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Naresh Balaji, Esin Yavuz, Thomas Nowotny

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Tags: Algorithms, Code generation, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GT 755 M, Package

December 2, 2014 by hgpu

CUDArray: CUDA-based NumPy

Anders Boesen Lindbo Larsen

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Tags: Computer science, CUDA, Neural networks, nVidia, Package, Python

November 16, 2014 by hgpu

Dogwild! – Distributed Hogwild for CPU & GPU

Cyprien Noel, Simon Osindero

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Tags: Computer science, Computer vision, CUDA, Distributed computing, Machine learning, Neural networks, nVidia

November 9, 2014 by hgpu

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K10, Tesla K20

October 29, 2014 by hgpu

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

Michelle Perry

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Tags: Bayesian, CUDA, High Energy Physics - Phenomenology, Neural networks, nVidia, nVidia GeForce GT 320 M, Physics, Tesla M2050

October 27, 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

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high performance computing on graphics processing units: hgpu.org

MatConvNet – Convolutional Neural Networks for MATLAB

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

Bayesian neural networks for detecting epistasis in genetic association studies

Real-Time Grasp Detection Using Convolutional Neural Networks

Theano-based Large-Scale Visual Recognition with Multiple GPUs

MLitB: Machine Learning in the Browser

Neural Networks through Shared Maps in Mobile Devices

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

CUDArray: CUDA-based NumPy

Dogwild! – Distributed Hogwild for CPU & GPU

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

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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