high performance computing on graphics processing units: hgpu.org

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hgpu.org » Programming » Algorithms

Parallel H-Tree Based Data Cubing on Graphics Processors

Baoyuan Wang, Yizhou Yu

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX

October 13, 2012 by hgpu

Accelerating Cost Aggregation for Real-Time Stereo Matching

Jianbin Fang, Ana Lucia Varbanescu, Jie Shen, Henk Sips, Gorkem Saygili, Laurens van der Maaten

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Tags: Algorithms, Image processing, nVidia, nVidia Quadro FX 5000, nVidia Quadro NVS 140 M, OpenCL, Optimization

October 13, 2012 by hgpu

GPU-Based Local-Dimming for Power Efficient Imaging

Chihao Xu, Michael Krause, Jens Kruger

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Tags: Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 555 M

October 13, 2012 by hgpu

Accelerating Mean Shift Segmentation Algorithm on Hybrid CPU/GPU Platforms

Liang Men, Miaoqing Huang, John Gauch

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Tags: Algorithms, Clustering, CUDA, Image processing, nVidia, Tesla C2075

October 9, 2012 by hgpu

Applying Genetic Algorithms to Tune Heterogeneous Platform Configurations

Max Grossman, Sameer Kulkarni

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Tags: Algorithms, ATI, Computer science, Heterogeneous systems, Machine learning, OpenCL, Optimization

October 9, 2012 by hgpu

Streaming Parallel GPU Acceleration of Large-Scale filter-based Spiking Neural Networks

Leszek Slazynski, Sander Bohte

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, Neural networks, nVidia, nVidia GeForce GTX 470, OpenCL

October 9, 2012 by hgpu

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

M. Prato, R. Cavicchioli, L. Zanni, P. Boccacci, M. Bertero

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Source codes

Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, Numerical Analysis, nVidia, nVidia GeForce GTX 280, Package

October 9, 2012 by hgpu

Learning hash codes for efficient content reuse detection

Qi Zhang, Yan Wu, Zhuoye Ding, Xuanjing Huang

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Tags: Algorithms, Computer science, CUDA, Hashing, Information Retrieval, nVidia, nVidia Quadro FX 4000, Security

October 8, 2012 by hgpu

Realtime Two-Way Coupling of Meshless Fluids and Nonlinear FEM

Lipeng Yang, Shuai Li, Aimin Hao, Hong Qin

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Tags: Algorithms, CUDA, FEM, Fluid dynamics, GLSL, nVidia, nVidia GeForce GTX 580

October 8, 2012 by hgpu

GPU Accelerated NIDS Search

Kristian Nordhaug

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 580, Security, Thesis

October 8, 2012 by hgpu

Techniques for Mapping Synthetic Aperture Radar Processing Algorithms to Multi-GPU Clusters

Eric Hayden, Mark Schmalz, William Chapman, Sanjay Ranka, Sartaj Sahni, Gunasekaran Seetharaman

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Tags: Algorithms, CUDA, GPU cluster, Image reconstruction, nVidia, Signal processing, Tesla C2050

October 6, 2012 by hgpu

Architectural explorations for streaming accelerators with customized memory layouts

Muhammad Shafiq

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Tags: Algorithms, Computer science, CUDA, Design space exploration, nVidia, Tesla C2050, Thesis

October 6, 2012 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel H-Tree Based Data Cubing on Graphics Processors

Accelerating Cost Aggregation for Real-Time Stereo Matching

GPU-Based Local-Dimming for Power Efficient Imaging

Accelerating Mean Shift Segmentation Algorithm on Hybrid CPU/GPU Platforms

Applying Genetic Algorithms to Tune Heterogeneous Platform Configurations

Streaming Parallel GPU Acceleration of Large-Scale filter-based Spiking Neural Networks

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

Learning hash codes for efficient content reuse detection

Realtime Two-Way Coupling of Meshless Fluids and Nonlinear FEM

GPU Accelerated NIDS Search

Techniques for Mapping Synthetic Aperture Radar Processing Algorithms to Multi-GPU Clusters

Architectural explorations for streaming accelerators with customized memory layouts

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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