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OpenCL Programming Guide

Aaftab Munshi, Benedict Gaster, Timothy G. Mattson, James Fung, Dan Ginsburg

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Tags: Algorithms, Book, Computer science, OpenCL, Tutorial

December 27, 2011 by hgpu

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Marco Maggioni, Marco Domenico Santambrogio, Jie Liang

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Tags: Algorithms, Chemistry, CUDA, Databases, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTX 460, Optimization

December 27, 2011 by hgpu

Parallel Algorithms for GPU accelerated Probabilistic Inference

Nico Piatkowski

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package, Tesla C2050

December 27, 2011 by hgpu

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Mikolaj Mackowiak, Krzysztof Kurowski, Aleksandr Igumenov

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Tags: Algorithms, Computer science, CUDA, Distributed computing, Hybrid computing, MPI, nVidia, Optimization, Package

December 27, 2011 by hgpu

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

Lu Zheng, Ole J. Mengshoel, Jike Chong

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Tags: Algorithms, Bayesian, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 460

December 26, 2011 by hgpu

A Novel GPU-Based Deformation Pipeline

Muhammad Mobeen Movania, Lin Feng

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, OpenGL, Rendering

December 26, 2011 by hgpu

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Qi Li

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Optimization, Sorting, Tesla C1060, Tesla C2050, Tesla C2070, Thesis

December 26, 2011 by hgpu

Methodology of control and supervision of web connected mobile robots with CUDA technology application

Janusz Bedkowski, Andrzej Maslowski

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia Quadro FX 1600 M, nVidia Quadro FX 3700

December 25, 2011 by hgpu

G-CP: Providing Fault Tolerance on the GPU through Software Checkpointing

Felix Loh, Matt Sinclair

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Tags: Algorithms, Computer science, CUDA, Fault tolerance, nVidia, Tesla C1060

December 25, 2011 by hgpu

Design and Development of Optical Flow Based Obstacle Avoidance Using CUDA

S. Jeevith , N.D. Gangadhar, S. Santhosh Kumar

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

December 25, 2011 by hgpu

GPU-Parallel Implementation of Color based Medical Image Retrieval in Compressed Domain

Kuldeep Yadav, Avi Srivastava, M. A. Ansari

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT

December 25, 2011 by hgpu

Parallel Implementation of Shape based Image Retrieval Approach on CUDA in Compressed Domain

Kuldeep Yadav, Avi Srivastava, Ankush Mittal, M. A. Ansari

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT

December 25, 2011 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

OpenCL Programming Guide

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Parallel Algorithms for GPU accelerated Probabilistic Inference

Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

A Novel GPU-Based Deformation Pipeline

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Methodology of control and supervision of web connected mobile robots with CUDA technology application

G-CP: Providing Fault Tolerance on the GPU through Software Checkpointing

Design and Development of Optical Flow Based Obstacle Avoidance Using CUDA

GPU-Parallel Implementation of Color based Medical Image Retrieval in Compressed Domain

Parallel Implementation of Shape based Image Retrieval Approach on CUDA in Compressed Domain

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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