high performance computing on graphics processing units: hgpu.org

Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha

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Tags: Bayesian, Computer science, CUDA, Deep learning, DSP, Neural networks, nVidia, nVidia GeForce GTX 1060

December 30, 2018 by hgpu

Performance Analysis of a Stereo Matching Implementation in OpenCL

Stephan Rotheneder

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 750 Ti, nVidia Quadro 1000 M, OpenCL, Stereo vision

December 16, 2018 by hgpu

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Stefan Rosenberger, Gundolf Haase

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, OpenACC, OpenMP, Sparse matrix

November 21, 2017 by hgpu

Computing Treewidth on the GPU

Tom C. van der Zanden, Hans L. Bodlaender

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Tags: Algorithms, Bloom filter, Computer science, Graph theory, nVidia, nVidia GeForce GTX 1060, OpenCL, Package

October 3, 2017 by hgpu

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Marco Tazzari, Frederik Beaujean, Leonardo Testi

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 1060, Package, Python, Tesla P100

September 28, 2017 by hgpu

clRNG: an OpenCL based software library containing random number generation functions

A tool set for random number generation on GPUs in R

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Faster-Mean-Shift-Euc

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Turbo: A constraint solver purely on GPUs (CUDA)

A Variant of Concurrent Constraint Programming on GPU

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high performance computing on graphics processing units: hgpu.org

Optimization of Compiler-generated OpenCL CNN Kernels and Runtime for FPGAs

Accelerating AutoDock VINA with GPUs

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

CUDA Tutorial – Cryptanalysis of Classical Ciphers Using Modern GPUs and CUDA

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

Pipelined Training with Stale Weights of Deep Convolutional Neural Networks

ALPyNA: Acceleration of Loops in Python for Novel Architectures

ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

Performance Analysis of a Stereo Matching Implementation in OpenCL

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Computing Treewidth on the GPU

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Recent source codes

clRNG: an OpenCL based software library containing random number generation functions

DLRM: An implementation of a deep learning recommendation model

OpenMM: A High Performance Molecular Dynamics Library

Fancier High-Performance API

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

Faster-Mean-Shift-Euc

Turbo: A constraint solver purely on GPUs (CUDA)

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