high performance computing on graphics processing units: hgpu.org

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Direct N-body simulations of globular clusters: (I) Palomar 14

Akram Hasani Zonoozi, Andreas H.W. Kuepper, Holger Baumgardt, Hosein Haghi, Pavel Kroupa, Michael Hilker

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Tags: Astrophysics, Galaxy Astrophysics, Globular clusters, GPU cluster, N-body simulation, nVidia, nVidia GeForce GTX 280

November 9, 2010 by hgpu

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarch, Yvonnick Le Menach, Jean-Luc Dekeyser

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla C870

November 9, 2010 by hgpu

An Exploration of OpenCL for a Numerical Relativity Application

Niket K. Choudhary, Rakesh Ginjupalli, Sandeep Navada, Gaurav Khanna

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Tags: Astrophysics, ATI, ATI Radeon HD 5870, Computational Physics, General Relativity and Quantum Cosmology, nVidia, OpenCL, OpenMP, Tesla C2050

November 9, 2010 by hgpu

Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

Hyung-Jin Kim, Weonjong Lee

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Physics, QCD, Tesla C2050

November 9, 2010 by hgpu

SU(2) Lattice QCD Simulations on Fermi GPUs

Nuno Cardoso, Pedro Bicudo

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Package, Physics

November 9, 2010 by hgpu

Implementation of the Neuberger-Dirac operator on GPUs

Bjoern Walk, Hartmut Wittig, Egor Dranischnikow, Elmar Schomer

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Physics, QCD, Tesla C2050

November 9, 2010 by hgpu

Staggered fermions simulations on GPUs

Claudio Bonati, Guido Cossu, Massimo D'Elia, Adriano Di Giacomo

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, Physics, QCD, Tesla C1060, Tesla C2050

November 9, 2010 by hgpu

Parallelizing the QUDA Library for Multi-GPU Calculations in Lattice Quantum Chromodynamics

Ronald Babich, Michael A. Clark, Balint Joo

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Physics, QCD, Tesla C1060, Tesla C2050, Tesla C870

November 9, 2010 by hgpu

Fast Histograms using Adaptive CUDA Streams

Sisir Koppaka, Dheevatsa Mudigere, Srihari Narasimhan, Babu Narayanan

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Tags: Computer science, CUDA, nVidia, Performance

November 9, 2010 by hgpu

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Christian Walder

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Tesla C2050

November 9, 2010 by hgpu

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Imran S. Haque, Vijay S. Pande

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9500 GT, Package, Tesla C870

November 9, 2010 by hgpu

Numerical modeling of gravitational wave sources accelerated by OpenCL

Gaurav Khanna, Justin McKennon

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Tags: Cell processor, Computational Physics, General Relativity and Quantum Cosmology, Gravitation, nVidia, OpenCL, Physics, Tesla C1060

November 9, 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

Direct N-body simulations of globular clusters: (I) Palomar 14

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

An Exploration of OpenCL for a Numerical Relativity Application

Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

SU(2) Lattice QCD Simulations on Fermi GPUs

Implementation of the Neuberger-Dirac operator on GPUs

Staggered fermions simulations on GPUs

Parallelizing the QUDA Library for Multi-GPU Calculations in Lattice Quantum Chromodynamics

Fast Histograms using Adaptive CUDA Streams

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Numerical modeling of gravitational wave sources accelerated by OpenCL

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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