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hgpu.org » Applications » Computer science » Computer vision

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

A Framework for the Volumetric Integration of Depth Images

Victor Adrian Prisacariu, Olaf Kahler, Ming Ming Cheng, Julien Valentin, Philip H.S. Torr, Ian D. Reid, David W. Murray

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Tags: Computer science, Computer vision, CUDA, nVidia

October 8, 2014 by hgpu

High performance histogramming on massively parallel processors

Wen-Mei Hwu

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Tags: Computer science, Computer vision, CUDA, Databases, Machine learning, nVidia, nVidia GeForce GTX 570, nVidia GeForce GTX 780, Thesis

September 20, 2014 by hgpu

Acceleration of stereo-matching on multi-core CPU and GPU

Tian Xu, Paul Cockshott, Susanne Oehler

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 770, Stereo vision

September 4, 2014 by hgpu

Surface Normal Integration for Convex Space-time Multi-view Reconstruction

Martin R. Oswald, Daniel Cremers

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

August 27, 2014 by hgpu

Non-Local Total Generalized Variation for Optical Flow Estimation

Rene Ranftl, Kristian Bredies, Thomas Pock

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 780 Ti, Optical flow

August 13, 2014 by hgpu

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA CUDA

Mehran Maghoumi

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Source codes

Tags: Computer science, Computer vision, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660, Package, Thesis

August 9, 2014 by hgpu

Discriminative Convolutional Sum-Product Networks on GPU

Tobias Hartmann

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Tags: Algorithms, Benchmarking, Computer science, Computer vision, CUDA, Neural networks, nVidia, Tesla K20, Thesis

August 1, 2014 by hgpu

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Kannappan Palaniappan

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Tags: Algorithms, Benchmarking, Cell processor, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Tesla C2070

July 24, 2014 by hgpu

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

Hon Ming Yip, John C. S. Li, Kai Xie, Xin Cui, Agrim Prasad, Qiannan Gao, Chi Chiu Leung, Raymond H. W. Lam

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 640

July 22, 2014 by hgpu

High Performance Low Power Embedded Vision Systems

Antonis S. Nikitakis

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Tags: Algorithms, ARM, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, OpenCV, Thesis

July 22, 2014 by hgpu

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Ken Chatfield, Karen Simonyan, Andrew Zisserman

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan, Pattern recognition

July 18, 2014 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

Applications

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

A Framework for the Volumetric Integration of Depth Images

High performance histogramming on massively parallel processors

Acceleration of stereo-matching on multi-core CPU and GPU

Surface Normal Integration for Convex Space-time Multi-view Reconstruction

Non-Local Total Generalized Variation for Optical Flow Estimation

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA CUDA

Discriminative Convolutional Sum-Product Networks on GPU

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

High Performance Low Power Embedded Vision Systems

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

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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