high performance computing on graphics processing units: hgpu.org

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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

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

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

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

Marius Buibas, Gabriel A. Silva

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Tags: Biological Physics, Condensed matter, CUDA, Disordered Systems and Neural Networks, Mathematical Physics, Neurons and Cognition, nVidia, Package, Physics, Tesla C1060

November 9, 2010 by hgpu

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

Danny van Dyk, Markus Geveler, Sven Mallach, Dirk Ribbrock, Dominik Goeddeke, Carsten Gutwenger

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Tags: Cell processor, Computer science, CUDA, Mathematical Software, Mixed precision, nVidia, nVidia GeForce 8800 GTX, Package

November 9, 2010 by hgpu

Fast Calculation of the Lomb-Scargle Periodogram Using Graphics Processing Units

R. H. D. Townsend

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Solar and Stellar Astrophysics, Tesla C1060

November 9, 2010 by hgpu

SIML: A Fast SIMD Algorithm for Calculating LINGO Chemical Similarities on GPUs and CPUs

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Tags: Chemistry, CUDA, nVidia, nVidia GeForce GTS 250, OpenMP, Package, Tesla T10

November 9, 2010 by hgpu

High Performance Direct Gravitational N-body Simulations on Graphics Processing Units: An implementation in CUDA (thesis)

Jeroen Bedorf

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Tags: Astrophysics, CUDA, Gravitation, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Package, Stellar dynamics

November 9, 2010 by hgpu

High Performance Direct Gravitational N-body Simulations on Graphics Processing Units

Simon P. Zwart, Robert Belleman, Peter Geldof

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Tags: Astrophysics, Cg, Gravitation, N-body simulation, nVidia, nVidia GeForce 8800 GTX, nVidia Quadro FX 1400, OpenGL, Package, Stellar dynamics

November 9, 2010 by hgpu

Gravitational tree-code on graphics processing units: implementation in CUDA

Evghenii Gaburov, Jeroen Bedorf, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 Ultra, Package, Physics

November 9, 2010 by hgpu

ABC-SysBio–approximate Bayesian computation in Python with GPU support

Juliane Liepe, Chris Barnes, Erika Cule, Kamil Erguler, Paul Kirk, Tina Toni, Michael P. H. Stumpf

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Python

November 9, 2010 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

SU(2) Lattice QCD Simulations on Fermi GPUs

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

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

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

Fast Calculation of the Lomb-Scargle Periodogram Using Graphics Processing Units

SIML: A Fast SIMD Algorithm for Calculating LINGO Chemical Similarities on GPUs and CPUs

High Performance Direct Gravitational N-body Simulations on Graphics Processing Units: An implementation in CUDA (thesis)

High Performance Direct Gravitational N-body Simulations on Graphics Processing Units

Gravitational tree-code on graphics processing units: implementation in CUDA

ABC-SysBio–approximate Bayesian computation in Python with GPU support

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

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