high performance computing on graphics processing units: hgpu.org

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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

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

A. Zhmurov, K. Rybnikov, Y. Kholodov, V. Barsegov

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Tags: Biological Physics, Chemical Physics, CUDA, nVidia, nVidia GeForce GTX 295, Physics, Pseudo-random number generators

November 9, 2010 by hgpu

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Casey S. Greene, Nicholas A. Sinnott-Armstrong, Daniel S. Himmelstein, Paul J. Park, Jason H. Moore, Brent T. Harris

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

Rio Yokota, Jaydeep P. Bardhan, Matthew G. Knepley, L. A. Barba, Tsuyoshi Hamada

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Tags: Chemistry, CUDA, GPU cluster, Molecular modeling, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Yongchao Liu, Bertil Schmidt, Douglas Maskell

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 6, 2010 by hgpu

Automatic fitting of spiking neuron models to electrophysiological recordings

Cyrille Rossant, Dan F. Goodman, Jonathan Platkiewicz, Romain Brette

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Tags: Adaptive threshold, Biology, CUDA, Distributed computing, Neuroscience, nVidia, nVidia GeForce GTX 295, Optimization, Package

November 6, 2010 by hgpu

Magnetohydrodynamics simulations on graphics processing units

Hon-Cheng Wong, Un-Hong Wong, Xueshang Feng, Zesheng Tang

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Tags: Computational Physics, CUDA, Electrodynamics, Magnetohydrodynamics, nVidia, nVidia GeForce GTX 295, Physics

November 6, 2010 by hgpu

GPU-Accelerated Nearest Neighbor Search for 3D Registration

Deyuan Qiu,Stefan May,Andreas Nuchter

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Tags: Computer science, Computer vision, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295

November 5, 2010 by hgpu

Lattice SU(2) on GPU’s

Nuno Cardoso, Pedro Bicudo

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

November 5, 2010 by hgpu

ECM on Graphics Cards

Daniel Bernstein, Tien-Ren Chen, Chen-Mou Cheng, Tanja Lange, Bo-Yin Yang

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Tags: Computer science, CUDA, Edwards curves, Elliptic curves, Elliptic-curve method of factorization, Factorization, Modular arithmetic, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Security

November 5, 2010 by hgpu

Treecode and fast multipole method for N-body simulation with CUDA

Rio Yokota, Lorena Barba

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Tags: Computational Physics, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 295, Package, Physics

November 4, 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

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high performance computing on graphics processing units: hgpu.org

Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

SU(2) Lattice QCD Simulations on Fermi GPUs

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Automatic fitting of spiking neuron models to electrophysiological recordings

Magnetohydrodynamics simulations on graphics processing units

GPU-Accelerated Nearest Neighbor Search for 3D Registration

Lattice SU(2) on GPU’s

ECM on Graphics Cards

Treecode and fast multipole method for N-body simulation with CUDA

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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