high performance computing on graphics processing units: hgpu.org

Applications

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Implementation of a Lattice–Boltzmann method for numerical fluid mechanics using the nVIDIA CUDA technology

E. Riegel, T. Indinger, N. Adams

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, LBUltra, nVidia, nVidia GeForce 8800 GTS, Presentation, Tesla C1060, Tesla S1070

November 2, 2010 by hgpu

Multilevel summation of electrostatic potentials using graphics processing units

David J. Hardy, John E. Stone, Klaus Schulten

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Tags: Chemistry, CUDA, Electrostatics, Molecular dynamics, Molecular modeling, Multilevel summation, nVidia, nVidia GeForce GTX 280, Physics, Tesla C870, Tesla D870

November 2, 2010 by hgpu

Performance Predictions for General-Purpose Computation on GPUs

Weiguo Liu, Wolfgang M. Wittig, Bertil Schmidt

Tags: Computer science, Performance

November 2, 2010 by hgpu

Fast and accurate protein substructure searching with simulated annealing and GPUs

Alex D. Stivala, Peter J. Stuckey, Anthony I. Wirth

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Source codes

Tags: Bioinformatics, Biological Physics, Biology, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 285, Package, Tesla C1060

November 2, 2010 by hgpu

Wait-free programming for general purpose computations on graphics processors

Phuong H. Ha, Philippas Tsigas, Otto J. Anshus

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Tags: Computer science, Consensus, Distributed data structures, Read-modify-write objects, Synchronization

November 2, 2010 by hgpu

Multi-grain Parallel Processing of Data-Clustering on Programmable Graphics Hardware

Hiroyki Takizawa, Hiroaki Kobayashi

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Tags: Cluster analysis, Computer science, Data mining, Nearest neighbour

November 2, 2010 by hgpu

A first look at integrated GPUs for green high-performance computing

T. Scogland, H. Lin, W. Feng

Tags: Computer science, Embedded high-performance computing, Energy-efficient computing, Green, Performance

November 2, 2010 by hgpu

Algorithmic performance studies on graphics processing units

O. Schenk, M. Christen, H. Burkhart

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Tags: Computer science, Linear Algebra, Matrix decomposition, Nonlinear optimization, nVidia, nVidia GeForce 8800 GTX, Sparse direct solvers

November 2, 2010 by hgpu

On sorting and load balancing on GPUs

Daniel Cederman, Philippas Tsigas

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Sorting

November 2, 2010 by hgpu

General purpose molecular dynamics simulations fully implemented on graphics processing units

J. Anderson, C. Lorenz, A. Travesset

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Tags: Chemistry, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX, Physics, Polymer Systems

November 2, 2010 by hgpu

Thread-Scalable Evaluation of Multi-Jet Observables

Walter Giele, Gerben Stavenga, Jan-Christopher Winter

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Tags: CUDA, Hadronic Colliders, High Energy Physics - Phenomenology, Jets, LO Computations, nVidia, Package, Physics, QCD, Tesla C1060

November 2, 2010 by hgpu

Graphics processing unit implementation of lattice Boltzmann models for flowing soft systems

Massimo Bernaschi, Ludovico Rossi, Roberto Benzi, Mauro Sbragaglia, Sauro Succi

Tags: Biophysics, Computer science, Lattice Boltzmann model

November 2, 2010 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Implementation of a Lattice–Boltzmann method for numerical fluid mechanics using the nVIDIA CUDA technology

Multilevel summation of electrostatic potentials using graphics processing units

Performance Predictions for General-Purpose Computation on GPUs

Fast and accurate protein substructure searching with simulated annealing and GPUs

Wait-free programming for general purpose computations on graphics processors

Multi-grain Parallel Processing of Data-Clustering on Programmable Graphics Hardware

A first look at integrated GPUs for green high-performance computing

Algorithmic performance studies on graphics processing units

On sorting and load balancing on GPUs

General purpose molecular dynamics simulations fully implemented on graphics processing units

Thread-Scalable Evaluation of Multi-Jet Observables

Graphics processing unit implementation of lattice Boltzmann models for flowing soft systems

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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