high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

Collision-streams: fast GPU-based collision detection for deformable models

Min Tang, Dinesh Manocha, Jiang Lin, Ruofeng Tong

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL

September 11, 2011 by hgpu

Texture compression of light maps using smooth profile functions

Jim Rasmusson, Jacob Strom, Per Wennersten, Michael Doggett, Tomas Akenine-Moller

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Tags: Algorithms, Compression, Computer science, nVidia, OpenCL, Rendering

September 11, 2011 by hgpu

A design pattern language for engineering (parallel) software: merging the PLPP and OPL projects

Kurt Keutzer, Berna L. Massingill, Timothy G. Mattson, Beverly A. Sanders

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Tags: Algorithms, Computer science, High-level Languages, Performance, Programming techniques

September 11, 2011 by hgpu

Early experiences with the intel many integrated cores accelerated computing technology

L. Koesterke, J. Boisseau, J. Cazes, K. Milfeld, D. Stanzione

Tags: Algorithms, Computer science, Intel, OpenMP, Performance

September 11, 2011 by hgpu

Parallel programming with NVIDIA CUDA

Alejandro Segovia

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, Package, Tutorial

September 11, 2011 by hgpu

Challenges of medical image processing

Ingrid Scholl, Til Aach, Thomas M. Deserno, Torsten Kuhlen

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Tags: Algorithms, Data mining, Grid, Image processing, Medicine, Review, Virtual reality, Visualization

September 11, 2011 by hgpu

High-performance SIMT code generation in an active visual effects library

Jay L.T. Cornwall, Lee Howes, Paul H.J. Kelly, Phil Parsonage, Bruno Nicoletti

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Tags: Algorithms, Code generation, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Performance, Software Engineering, Visualization

September 11, 2011 by hgpu

Solving diffractive optics problems using graphics processing units

D. L. Golovashkin, N. L. Kasanskiy

Tags: Algorithms, ATI, ATI FireStream, Brook, Cg, CUDA, FDTD, Finite-difference time-domain, nVidia, OpenGL, Optics, Overview, Physics, Raytracing, Review

September 11, 2011 by hgpu

Beyond programmable shading (parts I and II)

Aaron Lefohn, Mike Houston, Johan Andersson, Ulf Assarsson, Cass Everitt, Kayvon Fatahalian, Tim Foley, Justin Hensley, Paul Lalonde, David Luebke

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Tags: 3D Graphics and Realism, Algorithms, Computer science, DirectX, Image processing, OpenGL, Presentation, Programming techniques, Rasterization, Raytracing, Rendering

September 9, 2011 by hgpu

Piccolo: building fast, distributed programs with partitioned tables

Russell Power, Jinyang Li

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Tags: Algorithms, Clustering, Computer science, Programming techniques

September 9, 2011 by hgpu

Parallel Programming on a Soft-Core Based Multi-core System

Liang-Teh Lee, Shin-Tsung Lee, Ching-Wei Chen

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Tags: Algorithms, Computer science, FPGA, Programming techniques

September 8, 2011 by hgpu

GPU Computation in Bioinspired Algorithms: A Review

M. G. Arenas, A. M. Mora, G. Romero and P. A. Castillo

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Tags: Algorithms, ATI, Bioinformatics, Biology, Computational biology, CUDA, nVidia, OpenCL, Overview, Review

September 8, 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

Collision-streams: fast GPU-based collision detection for deformable models

Texture compression of light maps using smooth profile functions

A design pattern language for engineering (parallel) software: merging the PLPP and OPL projects

Early experiences with the intel many integrated cores accelerated computing technology

Parallel programming with NVIDIA CUDA

Challenges of medical image processing

High-performance SIMT code generation in an active visual effects library

Solving diffractive optics problems using graphics processing units

Beyond programmable shading (parts I and II)

Piccolo: building fast, distributed programs with partitioned tables

Parallel Programming on a Soft-Core Based Multi-core System

GPU Computation in Bioinspired Algorithms: A Review

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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