high performance computing on graphics processing units: hgpu.org

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Parallel Implementation of Otsu’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Parallel Implementation of Souvola’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Rajat Phull, Pradip Mainali, Qiong Yang, Patrice Rondao Alface, Henk Sips

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 280

November 9, 2011 by hgpu

Effects of GPU and CPU Loads on Performance of CUDA Applications

Maksim Bobrov, Roy Melton, Stanislaw Radziszowski, Marcin Lukowiak

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Tags: AES, Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 285, Performance, Security

November 9, 2011 by hgpu

Large data visualization on distributed memory multi-GPU clusters

Thomas Fogal, Hank Childs, Siddharth Shankar, Jens Kruger, R. Daniel Bergeron, Philip Hatcher

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Tags: Algorithms, Computer science, GLSL, GPU cluster, nVidia, nVidia GeForce 8800 GTX, nVidia Quadro FX 5800, OpenGL, Performance, Rendering, Visualization

November 9, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

Parallel Implementation of Niblack’s Binarization Approach on CUDA

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems in a Hybrid CPU-GPU Computing Environment

Jun-ichi Muramatsu, Takeshi Fukaya, Shao-Liang Zhang, Kinji Kimura, Yusaku Yamamoto

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C1060

November 8, 2011 by hgpu

A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures

Mitch Horton, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 480, Tesla M2070

November 8, 2011 by hgpu

Flocking Implementation for the Blender Game Engine

Myrna I. Merced Serrano

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Tags: Algorithms, Computer science, Games, nVidia, nVidia GeForce GTX 480, OpenCL, Thesis

November 7, 2011 by hgpu

GPUinspiral – a low-latency, high-performance implementation of the matched-filter gravitational wave search algorithm

G. Debreczeni, B. Somhegyi

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Source codes

Tags: Algorithms, Astrophysics, ATI, ATI Radeon HD 5970, Filtering, Gravitation, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Tesla C2050

November 7, 2011 by hgpu

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Sylvain Henry

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Optimization, Performance, Programming Languages, Programming techniques

November 7, 2011 by hgpu

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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

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high performance computing on graphics processing units: hgpu.org

Parallel Implementation of Otsu’s Binarization Approach on GPU

Parallel Implementation of Souvola’s Binarization Approach on GPU

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Effects of GPU and CPU Loads on Performance of CUDA Applications

Large data visualization on distributed memory multi-GPU clusters

Automatic transformation and optimization of applications on GPUs and GPU clusters

Parallel Implementation of Niblack’s Binarization Approach on CUDA

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems in a Hybrid CPU-GPU Computing Environment

A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures

Flocking Implementation for the Blender Game Engine

GPUinspiral – a low-latency, high-performance implementation of the matched-filter gravitational wave search algorithm

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Recent source codes

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

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

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