high performance computing on graphics processing units: hgpu.org

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Fast Virus Signature Matching Based on the High Performance Computing of GPU

Yang Wan Cheng

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Tags: Algorithms, Computer science, Security

March 25, 2011 by hgpu

A Data Communication Scheduler for Stream Programs on CPU-GPU Platform

Tao Tang, Xinhai Xu, Yisong Lin

Tags: ATI, Computer science, Heterogeneous systems, Task scheduling

March 25, 2011 by hgpu

Implementation of Kernel Methods on the GPU

Julius Ohmer, Frederic Maire, Ross Brown

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Tags: Cg, Computer vision, Image processing, Image recognition, nVidia, nVidia GeForce 6800, OpenGL

March 24, 2011 by hgpu

Optimizing GPU Volume Rendering

Daniel Ruijters, Anna Vilanova

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Tags: ATI, ATI FireGL X1, Computer science, nVidia, nVidia Quadro FX 3400, OpenGL, Rendering, Visualization

March 24, 2011 by hgpu

A realtime GPU subdivision kernel

Le-Jeng Shiue, Ian Jones, Jorg Peters

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Tags: 3D Graphics and Realism, ATI, ATI Radeon 9700, Computer science, OpenGL, Rendering

March 24, 2011 by hgpu

General-purpose GPU computing: practice and experience

Bartlett S. H. (Scott) Michel

Tags: Computer science, Programming techniques, Review

March 24, 2011 by hgpu

Fast in-place sorting with CUDA based on bitonic sort

Hagen Peters, Ole Schulz-Hildebrandt, and Norbert Luttenberger

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sorting

March 24, 2011 by hgpu

Modeling GPU-CPU Workloads and Systems

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8600 GS, nVidia GeForce GTX 280, Performance, Task scheduling, Tesla C1060

March 23, 2011 by hgpu

Gvim: Gpu-accelerated virtual machines

Vishakha Gupta, Ada Gavrilovska, K. Schwan, Harshvardhan Kharche, Niraj Tolia, Vanish Talwar, Parthasarathy Ranganathan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTX, Virtualization

March 23, 2011 by hgpu

GPU-Assisted Computation of Centroidal Voronoi Tessellation

Guodong Rong, Yang Liu, Wenping Wang, Xiaotian Yin, David Gu, Xiaohu Guo

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Tags: Cg, Computer science, nVidia, nVidia GeForce GTX 280, Visualization, Voronoi diagram

March 23, 2011 by hgpu

GPU Random Numbers via the Tiny Encryption Algorithm

Fahad Zafar, Marc Olano, Aaron Curtis

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 9800 GT, Pseudo-random number generators

March 23, 2011 by hgpu

Aspects of GPU for general purpose high performance computing

Takayuki Aoki, Shoichi Hirasawa, Akira Nukada, Hiroki Honda, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques, Task scheduling

March 23, 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

Fast Virus Signature Matching Based on the High Performance Computing of GPU

A Data Communication Scheduler for Stream Programs on CPU-GPU Platform

Implementation of Kernel Methods on the GPU

Optimizing GPU Volume Rendering

A realtime GPU subdivision kernel

General-purpose GPU computing: practice and experience

Fast in-place sorting with CUDA based on bitonic sort

Modeling GPU-CPU Workloads and Systems

Gvim: Gpu-accelerated virtual machines

GPU-Assisted Computation of Centroidal Voronoi Tessellation

GPU Random Numbers via the Tiny Encryption Algorithm

Aspects of GPU for general purpose high performance computing

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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