high performance computing on graphics processing units: hgpu.org

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Numerical computations in Java with CUDA

Bogdan Oancea, Tudorel Andrei, Andreea Iluzia Iacob

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Tags: Computer science, CUBLAS, CUDA, Java, Linear Algebra, nVidia, nVidia GeForce 9500 GT

January 7, 2013 by hgpu

Interactive Refactoring for GPU Parallelization of Affine Loops

Kostadin Damevski, Madhan Muralimanohar

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 2000

January 7, 2013 by hgpu

Approximate Subdivision Surface Evaluation in the Language of Linear Algebra

Michael Driscoll

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Tags: 3D Graphics and Realism, Computer science, CUDA, Image generation, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

January 5, 2013 by hgpu

Graphic-Processing-Units Based Adaptive Parameter Estimation of a Visual Psychophysical Model

Hairong Gu

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

January 4, 2013 by hgpu

Parallel one-versus-rest SVM training on the GPU

Sander Dieleman, Aaron van den Oord, Benjamin Schrauwen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 540 M, nVidia GeForce GTX 560 Ti, Search strategies, Tesla C1060

January 4, 2013 by hgpu

Fast Global Illumination for Interactive Volume Visualization

Yubo Zhang, Kwan-Liu Ma

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Tags: 3D Graphics and Realism, Computer science, CUDA, Differential equations, Diffusion equation, nVidia, nVidia GeForce GTX 460, Visualization

January 4, 2013 by hgpu

Automatic Code Generation for Stencil Computations on GPU Architectures

Justin Andrew Holewinski

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Tesla K10, Thesis

January 4, 2013 by hgpu

uBench: Performance Impact of CUDA Block Geometry

Yuri Torres, Arturo Gonzalez, Diego R. Llanos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

January 3, 2013 by hgpu

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Denis Demidov, Karsten Ahnert, Karl Rupp, Peter Gottschling

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Source codes

Tags: ATI, ATI Radeon HD 7970, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, OpenCL, Ordinary differential equations, Package, Tesla C2070

January 2, 2013 by hgpu

Using P System with GPU Model to Design and Implement a Public Key Cryptography

Salah Zaher, Amr Badr, Ibrahim Farag, Tarek AbdElmaged

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Tags: Algorithms, ATI, ATI Radeon HD 4650, Computer science, Membrane computing, P systems, RSA, Security

January 2, 2013 by hgpu

The Geant4 Visualisation System – a multi-driver graphics system

John Allison, Laurent Garnier, Akinori Kimura, Joseph Perl

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Tags: Algorithms, Computer science, High Energy Physics - Experiment, OpenGL, Visualization

January 2, 2013 by hgpu

Floating Point Arithmetic for Transport Triggered Architectures

Timo Tapani Viitanen

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Tags: Algorithms, Benchmarking, Computer science, FPGA, OpenCL, Thesis

December 30, 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

Applications

Numerical computations in Java with CUDA

Interactive Refactoring for GPU Parallelization of Affine Loops

Approximate Subdivision Surface Evaluation in the Language of Linear Algebra

Graphic-Processing-Units Based Adaptive Parameter Estimation of a Visual Psychophysical Model

Parallel one-versus-rest SVM training on the GPU

Fast Global Illumination for Interactive Volume Visualization

Automatic Code Generation for Stencil Computations on GPU Architectures

uBench: Performance Impact of CUDA Block Geometry

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Using P System with GPU Model to Design and Implement a Public Key Cryptography

The Geant4 Visualisation System – a multi-driver graphics system

Floating Point Arithmetic for Transport Triggered Architectures

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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