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Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

Carolin Wolf

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Tags: Computer science, CUDA, Java, nVidia, OpenMP, Tesla M1060, Thesis

February 12, 2014 by hgpu

Object support for OpenMP-style programming of GPU clusters in Java

Carolin Wolf, Georg Dotzler, Ronald Veldema, Michael Philippsen

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Tags: Computer science, CUDA, GPU cluster, Java, nVidia, PC cluster, Tesla M1060

July 16, 2013 by hgpu

Platform-independent parallelization of the Lattice Boltzmann method with OpenCL

Carolin Wolf

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5470, ATI Radeon HD 4870, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenCL, Tesla M1060, Thesis

October 17, 2012 by hgpu

GPU Accelerated Nonlinear Optimization in Radio Interferometric Calibration

Sarod Yatawatta, Sanaz Kazemi, Saleem Zaroubi

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Tags: Algorithms, Astrophysics, CUBLAS, CUDA, Linear Algebra, Nonlinear optimization, nVidia, Optimization, Tesla M1060

August 26, 2012 by hgpu

Towards user transparent parallel multimedia computing on GPU-clusters

Ben van Werkhoven, Jason Maassen, Frank J. Seinstra

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Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla M1060

March 18, 2012 by hgpu

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

Decreasing NAME III Solution Time Using GP-GPU

Kingsley Gale-Sides

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Tags: Benchmarking, Cloud, Computer science, CUDA, Fortran, MPI, nVidia, Tesla C2050, Tesla M1060, Thesis

January 1, 2012 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Grids, Clouds and Virtualization

Massimo Cafaro, Giovanni Aloisio (Eds.)

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Tags: Book, Cloud, Computer science, CUDA, Grid, nVidia, Review, Tesla M1060, Virtualization

November 16, 2011 by hgpu

Solving Incompressible Two-Phase Flows on Massively Parallel Multi-GPU Clusters

P. Zaspel, M. Griebel

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Tags: Compression, CUDA, Finite difference, Fluid dynamics, GPU cluster, Navier-Stokes equations, NSEs, nVidia, Tesla M1060, Tesla S1070

November 14, 2011 by hgpu

GPU Acceleration of Matrix-based Methods in Computational Electromagnetics

Evan Lezar

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Tags: CUDA, Electrodynamics, FEM, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 465, OpenCL, Tesla M1060, Thesis

November 10, 2011 by hgpu

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Alejandro C. Crespo, Jose M. Dominguez, Anxo Barreiro, Moncho Gomez-Gesteira, Benedict D. Rogers

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Source codes

Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla M1060, Visualization

October 10, 2011 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

Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

Object support for OpenMP-style programming of GPU clusters in Java

Platform-independent parallelization of the Lattice Boltzmann method with OpenCL

GPU Accelerated Nonlinear Optimization in Radio Interferometric Calibration

Towards user transparent parallel multimedia computing on GPU-clusters

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Applications Performance on GPGPUs with the Fermi Architecture

Solving Incompressible Two-Phase Flows on Massively Parallel Multi-GPU Clusters

GPU Acceleration of Matrix-based Methods in Computational Electromagnetics

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

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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