high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Depth-of-Field Blur Effects for First-Person Navigation in Virtual Environments

Sebastien Hillaire, Anatole Lecuyer, Remi Cozot, Gery Casiez

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Tags: Algorithms, Computer science, Filtering, Games, Rendering

April 9, 2011 by hgpu

Fast Motion Estimation on Graphics Hardware for H.264 Video Encoding

Martin Schwalb, Ralph Ewerth, Bernd Freisleben

Tags: Compression, Computer science, H.264/AVC, Video decoding

April 9, 2011 by hgpu

An approach of tool paths generation for CNC machining based on CUDA

Yu Wujia, Zhou Yajun

Tags: Algorithms, CAD, Computer science, CUDA, nVidia

April 9, 2011 by hgpu

Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Shivani Raghav, Martino Ruggiero, David Atienza, Christian Pinto, Andrea Marongiu, Luca Benini

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Programming techniques

April 9, 2011 by hgpu

Kernel Fusion: An Effective Method for Better Power Efficiency on Multithreaded GPU

Guibin Wang, YiSong Lin, Wei Yi

Tags: Computer science, CUDA, Energy-efficient computing, nVidia

April 9, 2011 by hgpu

A simple and efficient way to compute depth maps for multi-view videos

Gael Sourimant

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Tags: Algorithms, Computer science, Computer vision, Optical flow, Video tracking

April 9, 2011 by hgpu

Real-time parallel remote rendering for mobile devices using graphics processing units

Wucherl Yoo, Shu Shi, Won J. Jeon, Klara Nahrstedt, Roy H. Campbell

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

April 9, 2011 by hgpu

Parallel Dense Gauss-Seidel Algorithm on Many-Core Processors

H. Courtecuisse, J. Allard

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Tags: Algorithms, Computer science, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Package, Physics-based simulation, Surgical simulation

April 8, 2011 by hgpu

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Ruyman Reyes, Francisco de Sande

Tags: Computer science, CUDA, nVidia, Optimization

April 8, 2011 by hgpu

Support Vector Machines on GPU with Sparse Matrix Format

Tsung-Kai Lin, Shao-Yi Chien

Tags: Computer science, Machine learning, nVidia, nVidia GeForce GTX 470

April 8, 2011 by hgpu

High-Speed Implementations of Block Cipher ARIA Using Graphics Processing Units

Yongjin Yeom, Yongkuk Cho, Moti Yung

Tags: Block Ciphers, Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTS, OpenGL, Security

April 8, 2011 by hgpu

Record Setting Software Implementation of DES Using CUDA

G. Agosta, A. Barenghi, F. De Santis, G. Pelosi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 250, nVidia GeForce GTX 260, nVidia GeForce GTX 275, nVidia GeForce GTX 285, nVidia GeForce GTX 295, Security

April 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

Applications

Depth-of-Field Blur Effects for First-Person Navigation in Virtual Environments

Fast Motion Estimation on Graphics Hardware for H.264 Video Encoding

An approach of tool paths generation for CNC machining based on CUDA

Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Kernel Fusion: An Effective Method for Better Power Efficiency on Multithreaded GPU

A simple and efficient way to compute depth maps for multi-view videos

Real-time parallel remote rendering for mobile devices using graphics processing units

Parallel Dense Gauss-Seidel Algorithm on Many-Core Processors

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Support Vector Machines on GPU with Sparse Matrix Format

High-Speed Implementations of Block Cipher ARIA Using Graphics Processing Units

Record Setting Software Implementation of DES Using CUDA

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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