high performance computing on graphics processing units: hgpu.org

Programming

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Jose M. Cecilia, Andy Nisbet, Martyn Amos, Jose M. Garcia, Manuel Ujaldon

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Tags: Algorithms, Computational modelling, Computer science, CUDA, Data parallelism, nVidia, Optimization, P systems, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Efficient Parallelization of Natural Language Applications using GPUs

Chao-Yue Lai

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Thesis

May 11, 2012 by hgpu

Data Regression with Normal Equation on GPU using CUDA

Vaibhav Mohan, Mayank Gupta

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Tags: Algorithms, Computer science, CUDA, nVidia

May 11, 2012 by hgpu

Large scale parallel state space search utilizing graphics processing units and solid state disks

Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Probabilistic model checking, Search strategies, Thesis

May 11, 2012 by hgpu

Enhancing data parallelism for Ant Colony Optimization on GPUs

Jose M. Cecilia, Jose M. Garcia, Andy Nisbet, Martyn Amos, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Optimization, Tesla C2050

May 10, 2012 by hgpu

A GPU-Accelerated Algorithm for Self-Organizing Maps in a Distributed Environment

Peter Wittek, Sandor Daranyi

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Tags: Algorithms, Computer science, CUDA, MapReduce, nVidia, Package, Self-organizing map, Tesla M2050

May 10, 2012 by hgpu

An Efficient Common Substrings Algorithm for On-the-Fly Behavior-Based Malware Detection and Analysis

Jaime C. Acosta, Brenda G. Medina, Humberto Mendoza

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro 1000 M, Security

May 10, 2012 by hgpu

Constructing Natural Neighbor Interpolation Based Grid DEM Using CUDA

Simin You, Jianting Zhang

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, Software Engineering

May 10, 2012 by hgpu

GHOSTM: A GPU-Accelerated Homology Search Tool for Metagenomics

Shuji Suzuki, Takashi Ishida, Ken Kurokawa, Yutaka Akiyama

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Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, Package, Tesla S1070

May 10, 2012 by hgpu

Exploration of Optimization Options for Increasing Performance of a GPU Implementation of a Three-Dimensional Bilateral Filter

E. Wes Bethel

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Tags: Algorithms, CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 280, Optimization, Performance

May 9, 2012 by hgpu

Automatic Discovery of Algorithms for Multi-Agent Systems

Sjors van Berkel, Daniel Turi, Andrei Pruteanu, Stefan Dulman

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Search strategies

May 9, 2012 by hgpu

Implementation and Optimization of Image Processing Algorithms on Embedded GPU

Nitin Singhal, Jin Woo Yoo, Ho Yeol Choi, In Kyu Park

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Tags: Algorithms, ARM, Computer vision, Image processing, OpenGL, Optimization, Rendering

May 7, 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

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Efficient Parallelization of Natural Language Applications using GPUs

Data Regression with Normal Equation on GPU using CUDA

Large scale parallel state space search utilizing graphics processing units and solid state disks

Enhancing data parallelism for Ant Colony Optimization on GPUs

A GPU-Accelerated Algorithm for Self-Organizing Maps in a Distributed Environment

An Efficient Common Substrings Algorithm for On-the-Fly Behavior-Based Malware Detection and Analysis

Constructing Natural Neighbor Interpolation Based Grid DEM Using CUDA

GHOSTM: A GPU-Accelerated Homology Search Tool for Metagenomics

Exploration of Optimization Options for Increasing Performance of a GPU Implementation of a Three-Dimensional Bilateral Filter

Automatic Discovery of Algorithms for Multi-Agent Systems

Implementation and Optimization of Image Processing Algorithms on Embedded GPU

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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