high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming » CUDA

A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

Nathan Schmid, Mathias Botschi, Wilfred F. Van Gunsteren

Tags: Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, nVidia Quadro FX 5800, Solvent effects

December 17, 2010 by hgpu

Accelerating Monte Carlo simulations with an NVIDIA graphics processor

Paul Martinsen, Johannes Blaschke, Rainer Kunnemeyer and Robert Jordan

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Tags: CUDA, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, Physics

December 16, 2010 by hgpu

Real-time optical micro-manipulation using optimized holograms generated on the GPU

S. Bianchi, R. Di Leonardo

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Tags: Computer holography, CUDA, nVidia, nVidia GeForce GTX 260, Optics, Physics

December 16, 2010 by hgpu

GPU Acceleration of an Unmodified Parallel Finite Element Navier-Stokes Solver

Dominik Goddeke, Sven H.M. Buijssen, Hilmar Wobker and Stefan Turek

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Tags: CUDA, Finite element method, Fluid dynamics, GPU cluster, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX

December 16, 2010 by hgpu

Fast and Accurate Finite-Element Multigrid Solvers for PDE Simulations on GPU Clusters

Dominik Goddeke

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Tags: CUDA, Finite element method, Fluid dynamics, GPU cluster, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 6800, nVidia GeForce 7600 GT, nVidia GeForce 7900 GT, nVidia GeForce 8600 GT, nVidia GeForce 8800 GTX, nVidia GeForce 9600 GT, nVidia GeForce GTX 280, OpenGL, Review, Thesis

December 16, 2010 by hgpu

High-throughput Bayesian network learning using heterogeneous multicore computers

Michael D. Linderman, Robert Bruggner, Vivek Athalye, Teresa H. Meng, Narges B. Asadi, Garry P. Nolan

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Tags: Algorithms, CUDA, GPU cluster, Mathematics, nVidia, nVidia GeForce GTX 285, Statistics, Tesla C1060, Tesla S1070

December 15, 2010 by hgpu

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

Scott Christley, Briana Lee, Xing Dai, Qing Nie

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Tags: Biology, CUDA, nVidia, nVidia GeForce GTX 285

December 15, 2010 by hgpu

Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, Kiyoshi Akama

Tags: Algorithms, Computer science, CUDA, nVidia, Search, Tesla C1060

December 15, 2010 by hgpu

Genetic programming on graphics processing units

Denis Robilliard, Virginie Marion-Poty, Cyril Fonlupt

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package

December 15, 2010 by hgpu

Acceleration of cardiac tissue simulation with graphic processing units

Daisuke Sato, Yuanfang Xie, James Weiss, Zhilin Qu, Alan Garfinkel, Allen Sanderson

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 9800 GX2, ODEs, Ordinary differential equations, Partial differential equations, PDEs

December 15, 2010 by hgpu

Optimizing Monte Carlo radiosity on graphics hardware

J. Sanjurjo, M. Amor, M. Boo, R. Doallo, J. Casares

Tags: Computer science, CUDA, Monte Carlo simulation, nVidia, Optimization, Rendering

December 15, 2010 by hgpu

Scalable and highly parallel implementation of Smith-Waterman on graphics processing unit using CUDA

Ali Akoglu, Gregory Striemer

Tags: Bioinformatics, Biology, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C870

December 15, 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

Programming

A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

Accelerating Monte Carlo simulations with an NVIDIA graphics processor

Real-time optical micro-manipulation using optimized holograms generated on the GPU

GPU Acceleration of an Unmodified Parallel Finite Element Navier-Stokes Solver

Fast and Accurate Finite-Element Multigrid Solvers for PDE Simulations on GPU Clusters

High-throughput Bayesian network learning using heterogeneous multicore computers

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

Genetic programming on graphics processing units

Acceleration of cardiac tissue simulation with graphic processing units

Optimizing Monte Carlo radiosity on graphics hardware

Scalable and highly parallel implementation of Smith-Waterman on graphics processing unit using CUDA

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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