high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

Cryptanalysis of the Full AES Using GPU-Like Special-Purpose Hardware

Alex Biryukov and Johann Grossschadl

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Tags: AES, Algorithms, Block Ciphers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Security

January 8, 2012 by hgpu

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

Guido Klingbeil, Radek Erban, Mike Giles, Philip K. Maini

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Tags: Algorithms, Chemistry, CUDA, nVidia, nVidia GeForce GTX 260, Stochastic simulation

January 7, 2012 by hgpu

Efficient Parallel Graph Exploration on Multi-Core CPU and GPU

Sungpack Hong, Tayo Oguntebi, Kunle Olukotun

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 275, Tesla C2050

January 7, 2012 by hgpu

GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement

Hartwig Anzt, Piotr Luszczek, Jack Dongarra, Vincent Heuveline

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Tags: Algorithms, Computer science, CUDA, Mixed precision, nVidia, Tesla C2070

January 6, 2012 by hgpu

Artifact-Free JPEG Decompression with Total Generalized Variation

Kristian Bredies, Martin Holler

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, nVidia Quadro FX 3700

January 6, 2012 by hgpu

Hyper neural network on OpenCL

Frantisek Sindelar

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Tags: Algorithms, Compression, Computer science, Genetic programming, Neural networks, nVidia, nVidia Quadro NVS 140 M, OpenCL, Thesis

January 6, 2012 by hgpu

Applying OOC Techniques in the Reduction to Condensed Form for Very Large Symmetric Eigenproblems on GPUs

Davor Davidovic, Enrique S. Quintana-Orti

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Tags: Algorithms, CUBLAS, CUDA, Linear Algebra, Mathematics, nVidia, Tesla C2050

January 6, 2012 by hgpu

A GPU Implementation of Inclusion-based Points-to Analysis

Mario Mendez-Lojo, Martin Burtscher, Keshav Pingali

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Source codes

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Performance, Programming techniques, Tesla C2070

January 5, 2012 by hgpu

Selecting the Best Tridiagonal System Solver Projected on Multi-Core CPU and GPU Platforms

Pablo Quesada-Barriuso, Julian Lamas-Rodriguez, Dora B. Heras, Montserrat Boo, Francisco Arguello

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 295, OpenMP

January 5, 2012 by hgpu

Implementation of a Fast Image Coding and Retrieval System Using a GPU

Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan N. Ramamurthy, Andreas Spanias

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 460

January 5, 2012 by hgpu

Fully 3D list-mode time-of-flight PET image reconstruction on GPUs using CUDA

Jing-yu Cui, Guillem Pratx, Sven Prevrhal, Craig S. Levin

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Tags: Algorithms, CUDA, Image reconstruction, Medicine, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, PET, Tomography

January 5, 2012 by hgpu

Pyramidal Image Blending Using CUDA Framework

Pritam Prakash Shete, Venkat P. P. K., S. K. Bose

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia Quadro FX 4600, Optimization

January 5, 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

Cryptanalysis of the Full AES Using GPU-Like Special-Purpose Hardware

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

Efficient Parallel Graph Exploration on Multi-Core CPU and GPU

GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement

Artifact-Free JPEG Decompression with Total Generalized Variation

Hyper neural network on OpenCL

Applying OOC Techniques in the Reduction to Condensed Form for Very Large Symmetric Eigenproblems on GPUs

A GPU Implementation of Inclusion-based Points-to Analysis

Selecting the Best Tridiagonal System Solver Projected on Multi-Core CPU and GPU Platforms

Implementation of a Fast Image Coding and Retrieval System Using a GPU

Fully 3D list-mode time-of-flight PET image reconstruction on GPUs using CUDA

Pyramidal Image Blending Using CUDA Framework

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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