high performance computing on graphics processing units: hgpu.org

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GEMM on a GPU

Jonathan Monette

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Poster

March 12, 2011 by hgpu

To GPU Synchronize or Not GPU Synchronize?

Wu-Chun Feng, Shucai Xiao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Programming techniques, Synchronization

March 12, 2011 by hgpu

GBOOST : A GPU-based tool for detecting gene-gene interactions in genome-wide case control studies

Ling Sing S. Yung, Can Yang, Xiang Wan, Weichuan Yu

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Tags: Bioinformatics, Biology, Genetics, nVidia, nVidia GeForce GTX 285, Package

March 12, 2011 by hgpu

Fast Optimal Mass Transport for Dynamic Active Contour Tracking on the GPU

Gallagher Pryor, Tauseef U. Rehman, Shawn Lankton, Patricio A. Vela, Allen Tannenbaum

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce 8800 GTX, Optical flow, Video tracking

March 12, 2011 by hgpu

Stereo depth with a Unified Architecture GPU

Joel Gibson, Oge Marques

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Tags: Computer science, Computer vision, CUDA, Image recognition, nVidia

March 11, 2011 by hgpu

GPU-Accelerated Text Mining

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Text mining

March 11, 2011 by hgpu

The GPU as a high performance computational resource

Tor Dokken, Trond R Hagen, Jon M Hjelmervik

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Tags: Computer science, Linear Algebra, Mathematical Software, Partial differential equations, PDEs, Review

March 11, 2011 by hgpu

Interactive SPH Simulation and Rendering on the GPU

Prashant Goswami, Philipp Schlegel, Barbara Solenthaler, Renato Pajarola

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Rendering

March 11, 2011 by hgpu

Using GPU shaders for visualization

Mike Bailey

Tags: Computer science, GLSL, OpenGL, Shaders, Visualization

March 11, 2011 by hgpu

Anisotropic Kuwahara Filtering on the GPU

Jan Eric Kyprianidis, Henry Kang, Jurgen Dollner

Tags: 3D Graphics and Realism, Algorithms, Computer science, Filtering, Rendering

March 11, 2011 by hgpu

Realtime Loop Subdivision on the GPU

Minho Kim, Jorg Peters

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Tags: 3D Graphics and Realism, ATI, ATI Radeon 9700 Pro, ATI Radeon X800, Computer science, nVidia, nVidia GeForce 6200, nVidia GeForce 6800 GT, Poster

March 11, 2011 by hgpu

Pseudorandom number generation on the GPU

Myles Sussman, William Crutchfield, Matthew Papakipos

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Tags: Algorithms, ATI, ATI Radeon X1900, Computer science, DirectX, HLSL, Presentation, Pseudo-random number generators

March 11, 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

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high performance computing on graphics processing units: hgpu.org

Applications

GEMM on a GPU

To GPU Synchronize or Not GPU Synchronize?

GBOOST : A GPU-based tool for detecting gene-gene interactions in genome-wide case control studies

Fast Optimal Mass Transport for Dynamic Active Contour Tracking on the GPU

Stereo depth with a Unified Architecture GPU

GPU-Accelerated Text Mining

The GPU as a high performance computational resource

Interactive SPH Simulation and Rendering on the GPU

Using GPU shaders for visualization

Anisotropic Kuwahara Filtering on the GPU

Realtime Loop Subdivision on the GPU

Pseudorandom number generation on the 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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