high performance computing on graphics processing units: hgpu.org

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Extended-precision floating-point numbers for GPU computation

Andrew Thall

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Tags: Algorithms, Cg, Computer science, Extended precision, FFT, nVidia, nVidia GeForce 7900 GT, nVidia GeForce 8800 GT

December 3, 2010 by hgpu

Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence

R. Yokota, T. Narumi, R. Sakamaki, S. Kameoka, S. Obi, K. Yasuoka

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Tags: CUDA, Fast multipole method, Fluid dynamics, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce 8800 GT, Physics

November 28, 2010 by hgpu

hiCUDA: a high-level directive-based language for GPU programming

Tianyi D. Han, Tarek S. Abdelrahman

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GT

November 23, 2010 by hgpu

GPU implementation of a road sign detector based on particle swarm optimization

Luca Mussi, Stefano Cagnoni, Elena Cardarelli, Fabio Daolio, Paolo Medici, Pier Porta

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia Quadro FX 5800

November 22, 2010 by hgpu

Parallel latent semantic analysis using a graphics processing unit

Joseph M. Cavanagh, Thomas E. Potok, Xiaohui Cui

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Text mining

November 21, 2010 by hgpu

Evaluation of parallel particle swarm optimization algorithms within the CUDA architecture

Luca Mussi, Fabio Daolio, Stefano Cagnoni

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT

November 19, 2010 by hgpu

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

Christopher J. Fluke, David G. Barnes, Benjamin R. Barsdell, Amr H. Hassan

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Tags: Astrophysics, ATI, ATI Radeon HD 5970, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 8800 GT, OpenCL, Tesla C1060

November 10, 2010 by hgpu

Teraflop per second gravitational lensing ray-shooting using graphics processing units

Alexander C. Thompson, Christopher J. Fluke, David G. Barnes, Benjamin R. Barsdell

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 GT, Tesla S1070

November 9, 2010 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Source codes

Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

Parallelized computation for computer simulation of electrocardiograms using personal computers with multi-core CPU and general-purpose GPU

Wenfeng Shen, Daming Wei, Weimin Xu, Xin Zhu, Shizhong Yuan

Tags: CUDA, Electrocardiograms simulation, Medicine, nVidia, nVidia GeForce 8800 GT, OpenMP, Optimization

November 8, 2010 by hgpu

On Dynamic Load Balancing on Graphics Processors

Daniel Cederman, Philippas Tsigas

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 9600 GT, Optimization, Performance

November 5, 2010 by hgpu

Iterative induced dipoles computation for molecular mechanics on GPUs

Frederico Pratas,Ricardo A. Mata,Leonel Sousa

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Tags: Chemistry, Computational chemistry, Computer science, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285

November 5, 2010 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

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

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Extended-precision floating-point numbers for GPU computation

Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence

hiCUDA: a high-level directive-based language for GPU programming

GPU implementation of a road sign detector based on particle swarm optimization

Parallel latent semantic analysis using a graphics processing unit

Evaluation of parallel particle swarm optimization algorithms within the CUDA architecture

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

Teraflop per second gravitational lensing ray-shooting using graphics processing units

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Parallelized computation for computer simulation of electrocardiograms using personal computers with multi-core CPU and general-purpose GPU

On Dynamic Load Balancing on Graphics Processors

Iterative induced dipoles computation for molecular mechanics on GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

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