high performance computing on graphics processing units: hgpu.org

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Multi-Object Geodesic Active Contours (MOGAC): A Parallel Sparse-Field Algorithm for Image Segmentation

Blake C. Lucas, Michael Kazhdan, Russell H. Taylor

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Tags: Algorithms, Computer science, Computer vision, Java, nVidia, nVidia Quadro FX 4000, OpenCL

March 10, 2012 by hgpu

Asynchronous Parallel Computing Model of Global Motion Estimation with CUDA

Zuo Chen, Jialiang Ji, Renfa Li

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 220, Video encoding

March 9, 2012 by hgpu

A Study of CUDA Acceleration and Impact of Data Transfer Overhead in Heterogeneous Environment

Fahian Ahmed, Saddam Quirem, Bum Joo Shin, Duk Joo Son, Young Choon Woo, Byeong Kil Lee, Wan Choi

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Tags: Algorithms, Computer science, CUDA, Databases, Heterogeneous systems, nVidia, Optimization, Security, Tesla C1060

March 9, 2012 by hgpu

Relational Algorithms for Multi-Bulk-Synchronous Processors

Gregory Frederick Diamos, Haicheng Wu, Ashwin Lele, Jin Wang, Sudhakar Yalamanchili

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Databases, Design space exploration, nVidia, Optimization, Tesla C2050

March 9, 2012 by hgpu

Scalable framework for mapping streaming applications onto multi-GPU systems

Huynh Phung Huynh, Andrei Hagiescu, Weng-Fai Wong, Rick Siow Mong Goh

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Tags: Algorithms, Code generation, Computer science, CUDA, GPU cluster, nVidia, Tesla C2070

March 8, 2012 by hgpu

Efficient Relational Algebra Algorithms and Data Structures for GPU

Gregory Frederick Diamos, Haicheng Wu, Ashwin Lele, Jin Wang

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Databases, Design space exploration, nVidia, Tesla C2050

March 6, 2012 by hgpu

Parallel Implementation of Similarity Measures on GPU Architecture using CUDA

Kuldeep Yadav, Ankush Mittal, M.A Ansari, Vennktesh Vishwarup

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

March 2, 2012 by hgpu

Ray Tracing Visualization Toolkit

Christiaan Gribble, Jeremy Fisher, Daniel Eby, Ed Quigley, Gideon Ludwig

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Tags: 3D Graphics and Realism, Algorithms, Computer science, OpenCL, OpenGL, Raytracing, Rendering, Visualization

March 2, 2012 by hgpu

Parallel Hashing, Compression and Encryption with OpenCL under OS X

Vasileios Xouris

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Tags: Algorithms, Compression, Computer science, Hashing, nVidia, nVidia GeForce 9400 M, nVidia GeForce 9600 M GT, OpenCL, Security, Thesis

March 2, 2012 by hgpu

Parallel Loopy Belief Propagation in Conditional Random Fields

Nico Piatkowski, Katharina Morik

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla C2050

March 1, 2012 by hgpu

A Restructuring Algorithm for CUDA

M. A. Al-Mouhamed, A. H. Khan

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia

February 29, 2012 by hgpu

Parallel Computation for Discrete Orthogonal Moments of Images Using Graphic Processing Unit

Dongfeng Xu, Yehan Zheng, Yuefang Gao, Dong Wang

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9600 GSO

February 28, 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

Multi-Object Geodesic Active Contours (MOGAC): A Parallel Sparse-Field Algorithm for Image Segmentation

Asynchronous Parallel Computing Model of Global Motion Estimation with CUDA

A Study of CUDA Acceleration and Impact of Data Transfer Overhead in Heterogeneous Environment

Relational Algorithms for Multi-Bulk-Synchronous Processors

Scalable framework for mapping streaming applications onto multi-GPU systems

Efficient Relational Algebra Algorithms and Data Structures for GPU

Parallel Implementation of Similarity Measures on GPU Architecture using CUDA

Ray Tracing Visualization Toolkit

Parallel Hashing, Compression and Encryption with OpenCL under OS X

Parallel Loopy Belief Propagation in Conditional Random Fields

A Restructuring Algorithm for CUDA

Parallel Computation for Discrete Orthogonal Moments of Images Using Graphic Processing Unit

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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