high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

High throughput multiple-precision GCD on the CUDA architecture

N. Fujimoto

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Security

April 7, 2011 by hgpu

Program Optimization of Stencil Based Application on the GPU-Accelerated System

Guibin Wang, Xuejun Yang, Ying Zhang, Tao Tang, XuDong Fang

Tags: Computer science, Optimization

April 7, 2011 by hgpu

Using GPU to Accelerate Cache Simulation

Wan Han, Gao Xiaopeng, Wang Zhiqiang, Li Yi

Tags: Algorithms, Computer science, CUDA, Memory, nVidia, Optimization

April 7, 2011 by hgpu

Accelerating Phase Correlation Functions Using GPU and FPGA

Kentaro Matsuo, Tsuyoshi Hamada, Masayuki Miyoshi, Yuichiro Shibata, and Kiyoshi Oguri

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Tags: Computer science, CUDA, FFT, FPGA, Image registration, nVidia, nVidia GeForce 8800 GTS

April 7, 2011 by hgpu

A Neighborhood Grid Data Structure for Massive 3D Crowd Simulation on GPU

Mark Joselli, Erick Baptista Passos, Marcelo Zamith, Esteban Walter Gonzalez Clua, Anselmo Montenegro, Bruno Feijo

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Tags: Cellular automata, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Rendering

April 7, 2011 by hgpu

Context-aware volume navigation

Stefan Diepenbrock, Timo Ropinski, Klaus Hinrichs

Tags: Computer science, OpenCL, Rendering, Visualization

April 7, 2011 by hgpu

Practical examples of GPU computing optimization principles

Goorts, Patrik; Rogmans, Sammy; Vanden Eynde, Steven; Bekaert, Philippe;

Tags: Computer science, CUDA, DirectCompute, nVidia, OpenCL, Programming techniques

April 7, 2011 by hgpu

Toward Harnessing DOACROSS Parallelism for Multi-GPGPUs

Peng Di, Qing Wan, Xuemeng Zhang, Hui Wu, Jingling Xue

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Tags: Computer science, nVidia, Optimization, Tesla C1060

April 6, 2011 by hgpu

An algorithmic incremental and iterative development method to parallelize dusty-deck FORTRAN HPC codes in GPGPUs using CUDA

N. Ghaemian, M. Sharifi, B. Minaei,R. Orujov

Tags: Computer science, CUDA, Fortran, High-level Languages, nVidia

April 6, 2011 by hgpu

Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs

Shinichi Yamagiwa, Koichi Wada, Leonel Sousa

Tags: Computer science, Optimization, Performance

April 6, 2011 by hgpu

High Performance Hybrid Functional Petri Net Simulations of Biological Pathway Models on CUDA

Georgios Chalkidis, Masao Nagasaki, Satoru Miyano

Tags: Algorithms, Computer science, CUDA, nVidia, Path problems

April 6, 2011 by hgpu

Barnes-hut treecode on GPU

Hu Jiang, Qianni Deng

Tags: Algorithms, Computer science, CUDA, N-body simulation, nVidia

April 6, 2011 by hgpu

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

High throughput multiple-precision GCD on the CUDA architecture

Program Optimization of Stencil Based Application on the GPU-Accelerated System

Using GPU to Accelerate Cache Simulation

Accelerating Phase Correlation Functions Using GPU and FPGA

A Neighborhood Grid Data Structure for Massive 3D Crowd Simulation on GPU

Context-aware volume navigation

Practical examples of GPU computing optimization principles

Toward Harnessing DOACROSS Parallelism for Multi-GPGPUs

An algorithmic incremental and iterative development method to parallelize dusty-deck FORTRAN HPC codes in GPGPUs using CUDA

Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs

High Performance Hybrid Functional Petri Net Simulations of Biological Pathway Models on CUDA

Barnes-hut treecode on GPU

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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