high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures

Daehyun Kim, Joshua Trzasko, Mikhail Smelyanskiy, Clifton Haider, Pradeep Dubey, Armando Manduca

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Tags: Algorithms, CUDA, Image processing, Medicine, MRI, nVidia, Sensing, Tesla C2050

February 21, 2012 by hgpu

Acceleration of Composite Order Bilinear Pairing on Graphics Hardware

Ye Zhang, Chun Jason Xue, Duncan S. Wong, Nikos Mamoulis, S.M. Yiu

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Tags: Algorithms, Cloud, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Security, Tesla M2050

February 21, 2012 by hgpu

Introducing ‘Bones’: A Parallelizing Source-to-Source Compiler Based on Algorithmic Skeletons

Cedric Nugteren, Henk Corporaal

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL

February 20, 2012 by hgpu

Review: Kd-tree Traversal Algorithms for Ray Tracing

M. Hapala, V. Havran

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Tags: 3D Graphics and Realism, Algorithms, Computer science, KD-tree, nVidia, Raytracing, Review

February 20, 2012 by hgpu

Exploiting Segmentation for Robust 3D Object Matching

Michael Krainin, Kurt Konolige, Dieter Fox

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Source codes

Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 450, OpenGL, Package

February 18, 2012 by hgpu

Cone-beam Computed tomography image reconstruction based on GPU

Hongwei Xu, Fucang Jia, Wenyan Chen, Xiaodong Zhang

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Tags: Algorithms, Computed tomography, CT, CUDA, Image reconstruction, Medicine, nVidia, nVidia GeForce GT 240 M, Tomography

February 18, 2012 by hgpu

Proposition for propagated occupation grids for non-rigid moving objects tracking

Benjamin Lefaudeux, Gwennael Gate, Fawzi Nashashibi

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia

February 17, 2012 by hgpu

Joint-MAP Tomographic Reconstruction with Patch Similarity Based Mixture Prior Model

Yang Chen, Yinsheng Li, Weimin Yu, Limin Luo, Wufan Chen, Christine Toumoulin

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Tags: Algorithms, Bayesian, Computed tomography, CT, CUDA, Medicine, nVidia, nVidia GeForce GTX 465, Tomography

February 17, 2012 by hgpu

Skeleton-based Automatic Parallelization of Image Processing Algorithms for GPUs

Cedric Nugteren, Henk Corporaal, Bart Mesman

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Tags: Algorithms, Code generation, CUDA, Image processing, nVidia, nVidia GeForce GTX 470, Optimization

February 17, 2012 by hgpu

Interactive Manycore Photon Mapping

Bartosz Fabianowski

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Tags: Algorithms, Computer science, CUDA, KD-tree, Nearest neighbour, nVidia, nVidia GeForce GTX 280, Rendering, Thesis

February 17, 2012 by hgpu

An Efficient Implementation of Double Precision 1-D FFT for GPUs Using CUDA

Yanjun Liu, Licai Guo, Bin Luo, Xingyi Zhang

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 260, Programming techniques

February 17, 2012 by hgpu

Accurate real-time stereo correspondence using intra- and inter-scanline optimization

Li Yao, Dong-xiao Li, Jing Zhang, Liang-hao Wang, Ming Zhang

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia Quadro FX 4800, Optimization, Stereo vision

February 15, 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

High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures

Introducing ‘Bones’: A Parallelizing Source-to-Source Compiler Based on Algorithmic Skeletons

Review: Kd-tree Traversal Algorithms for Ray Tracing

Exploiting Segmentation for Robust 3D Object Matching

Cone-beam Computed tomography image reconstruction based on GPU

Proposition for propagated occupation grids for non-rigid moving objects tracking

Joint-MAP Tomographic Reconstruction with Patch Similarity Based Mixture Prior Model

Skeleton-based Automatic Parallelization of Image Processing Algorithms for GPUs

Interactive Manycore Photon Mapping

An Efficient Implementation of Double Precision 1-D FFT for GPUs Using CUDA

Accurate real-time stereo correspondence using intra- and inter-scanline optimization

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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