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Constraint Fluids on GPU

Martin Nilsson

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Tags: Algorithms, Collision detection, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Thesis

February 1, 2011 by hgpu

GPU as a Parallel Machine: Sorting on the GPU

Joseph T. Kider Jr.

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 6800 Ultra, Sorting

February 1, 2011 by hgpu

Introduction to GPU programming for EDA

John F. Croix, Sunil P. Khatri

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Tags: Computational Engineering, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro FX 5800, OpenCL, Presentation, Review

February 1, 2011 by hgpu

Towards Automated Learning of Object Detectors

Marc Ebner

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Tags: Algorithms, Computer vision, Image processing, OpenGL

January 31, 2011 by hgpu

Batched Multi Triangulation

Paolo Cignoni, Fabio Ganovelli, Enrico Gobbetti, Fabio Marton

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Tags: Computer science, nVidia, nVidia GeForce 6800 GT, nVidia GeForce FX 5800 Ultra, nVidia GeForce FX 5950 Ultra, Rendering

January 31, 2011 by hgpu

Advanced Multi-Frame Rate Rendering Techniques

Jan P. Springer, Christopher Lux, Dirk Reiners, Bernd Froehlich

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Tags: 3D Graphics and Realism, Computer science, Image generation, nVidia, nVidia Quadro FX 5600, OpenGL

January 31, 2011 by hgpu

Isosurface Extraction and View-Dependent Filtering from Time-Varying Fields Using Persistent Time-Octree (PTOT)

Cong Wang, Yi-Jen Chiang

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce 9800 GTX

January 31, 2011 by hgpu

Scientific Computing on Heterogeneous Architectures

A. R. Brodtkorb

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Review, Thesis

January 31, 2011 by hgpu

OpenRCL: Low-Power High-Performance Computing with Reconfigurable Devices

Mingjie Lin, Ilia Lebedev, John Wawrzynek

Tags: Compilers, Computer science, FPGA, nVidia, nVidia GeForce 9400 M, OpenCL

January 31, 2011 by hgpu

Simulation and visualization of the Saint-Venant system using GPUs

Andre Brodtkorb, Trond Hagen, Knut-Andreas Lie, Jostein Natvig

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Rendering, Visualization

January 31, 2011 by hgpu

Top-Performance Tokenization and Small-Ruleset Regular Expression Matching: A Quantitative Performance Analysis and Optimization Study on the Cell/B.E. Processor

Daniele Paolo Scarpazza

Tags: Algorithms, Cell processor, Computer science, Pattern Search

January 31, 2011 by hgpu

Small-ruleset regular expression matching on GPGPUs: quantitative performance analysis and optimization

Jamin Naghmouchi, Daniele P. Scarpazza, Mladen Berekovic

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, nVidia GeForce GTX 280, Pattern Search, Programming techniques

January 31, 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

Applications

Constraint Fluids on GPU

GPU as a Parallel Machine: Sorting on the GPU

Introduction to GPU programming for EDA

Towards Automated Learning of Object Detectors

Batched Multi Triangulation

Advanced Multi-Frame Rate Rendering Techniques

Isosurface Extraction and View-Dependent Filtering from Time-Varying Fields Using Persistent Time-Octree (PTOT)

Scientific Computing on Heterogeneous Architectures

OpenRCL: Low-Power High-Performance Computing with Reconfigurable Devices

Simulation and visualization of the Saint-Venant system using GPUs

Top-Performance Tokenization and Small-Ruleset Regular Expression Matching: A Quantitative Performance Analysis and Optimization Study on the Cell/B.E. Processor

Small-ruleset regular expression matching on GPGPUs: quantitative performance analysis and optimization

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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