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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

Fast and accurate protein substructure searching with simulated annealing and GPUs

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

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

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

3D finite difference computation on GPUs using CUDA

Paulius Micikevicius

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Tags: Computer science, CUDA, Finite difference, nVidia, Tesla S1070, Wave equation

November 2, 2010 by hgpu

Parallel external sorting for CUDA-enabled GPUs with load balancing and low transfer overhead

Hagen Peters, Ole Schulz-Hildebrandt, Norbert Luttenberger

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Sorting

November 2, 2010 by hgpu

Improving Performance of Matrix Multiplication and FFT on GPU

Xiang Cui, Yifeng Chen, Hong Mei

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Tags: Computer science, CUDA, FFT, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280

November 2, 2010 by hgpu

A control-structure splitting optimization for GPGPU

Snaider Carrillo, Jakob Siegel, Xiaoming Li

Tags: Algorithm optimization, Computer science, CUDA, nVidia, Programming techniques

November 1, 2010 by hgpu

A GPU accelerated storage system

Abdullah Gharaibeh, Samer A. Kiswany, Sathish Gopalakrishnan, Matei Ripeanu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600, nVidia GeForce 8800 GT, nVidia GeForce 9800 GX2, Performance, Storage system

November 1, 2010 by hgpu

Fast parallel Particle-To-Grid interpolation for plasma PIC simulations on the GPU

G. Stantchev, W. Dorland, N. Gumerov

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Tags: Computer science, CUDA, Numerical simulation, nVidia, Particle-in-cell methods, Plasma physics

November 1, 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

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

Multilevel summation of electrostatic potentials using graphics processing units

Fast and accurate protein substructure searching with simulated annealing and GPUs

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

3D finite difference computation on GPUs using CUDA

Parallel external sorting for CUDA-enabled GPUs with load balancing and low transfer overhead

Improving Performance of Matrix Multiplication and FFT on GPU

A control-structure splitting optimization for GPGPU

A GPU accelerated storage system

Fast parallel Particle-To-Grid interpolation for plasma PIC simulations on the GPU

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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