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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

Cellular GPU Models to Euclidean Optimization Problems

Naiyu Zhang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 570, Optimization, Self-organizing map, Thesis

April 27, 2014 by hgpu

MAP-based Brain Tissue Segmentation using Manifold Learning and Hierarchical Max-Flow regularization

Martin Rajchl, John S.H. Baxter, A. Jonathan McLeod, Jing Yuan, Wu Qiu, Terry M. Peters, James A. White, Ali R. Khan

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Tags: CUDA, Image processing, Medicine, nVidia, Self-organizing map, Tesla C2070

April 12, 2014 by hgpu

Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment

Peter Wittek, Sandor Daranyi

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Tags: Algorithms, Computer science, CUDA, MapReduce, nVidia, Package, Self-organizing map, Tesla M2050, Text mining

August 31, 2013 by hgpu

Somoclu: An Efficient Distributed Library for Self-Organizing Maps

Peter Wittek

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Tags: Computer science, CUDA, Mathematical Software, MPI, Neural and Evolutionary Computing, nVidia, Package, Self-organizing map, Tesla M2050, Text mining

May 8, 2013 by hgpu

A GPU-Accelerated Algorithm for Self-Organizing Maps in a Distributed Environment

Peter Wittek, Sandor Daranyi

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Tags: Algorithms, Computer science, CUDA, MapReduce, nVidia, Package, Self-organizing map, Tesla M2050

May 10, 2012 by hgpu

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Masato Yoshimi, Takuya Kuhara, Kaname Nishimoto, Mitsunori Miki, Tomoyuki Hiroyasu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 280, Optimization, Self-organizing map, Tesla C1060, Visualization

April 5, 2012 by hgpu

Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA

Sabine McConnell, Robert Sturgeon, Gregory Henry, Andrew Mayne, Richard Hurley

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Tags: Algorithms, Computer science, CUDA, Data mining, GPU cluster, nVidia, nVidia GeForce GT 220, OpenCL, Self-organizing map, Tesla S1070

February 11, 2012 by hgpu

Efficient Computation of SOM for Outage Database

Petr Gajdos, Michal Kratky, David Bednar, Radim Baca, Radomir Gono, Jiri Walder

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Tags: Computer science, CUDA, Databases, Neural networks, nVidia, Self-organizing map, Tesla C1060, Visualization

February 5, 2012 by hgpu

Improving the usability of hierarchical representations for interactively labeling large image data sets

Julia Moehrmann, Stefan Bernstein, Thomas Schlegel, Gunter Werner, Gunther Heidemann

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Tags: ATI, ATI Mobility Radeon HD 4200, Clustering, Image processing, Image recognition, nVidia, nVidia GeForce 9600 M GT, Self-organizing map, Visualization

December 22, 2011 by hgpu

Parallel Batch Training of the Self-Organizing Map Using OpenCL

Masahiro Takatsuka, Michael Bui

Tags: Computer science, Neural networks, OpenCL, Self-organizing map

August 18, 2011 by hgpu

A self-organization based optical flow estimator with GPU implementation (thesis)

Manish Shiralkar

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, nVidia Quadro FX 5600, nVidia Quadro NVS 140 M, Optical flow, Self-organizing map, Tesla T10, Thesis

July 22, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

A Parallel Implementation of the Self Organising Map using OpenCL

Cellular GPU Models to Euclidean Optimization Problems

MAP-based Brain Tissue Segmentation using Manifold Learning and Hierarchical Max-Flow regularization

Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment

Somoclu: An Efficient Distributed Library for Self-Organizing Maps

A GPU-Accelerated Algorithm for Self-Organizing Maps in a Distributed Environment

Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA

Efficient Computation of SOM for Outage Database

Improving the usability of hierarchical representations for interactively labeling large image data sets

Parallel Batch Training of the Self-Organizing Map Using OpenCL

A self-organization based optical flow estimator with GPU implementation (thesis)

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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