high performance computing on graphics processing units: hgpu.org

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A QUDA-branch to compute disconnected diagrams in GPUs

Constantia Alexandrou, Kyriacos Hadjiyiannakou, Giannis Koutsou, Alexei Strelchenko, Alejandro Vaquero

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla M2070

January 30, 2014 by hgpu

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Luiz Otavio S. Ferreira, Lucas Monteiro Volpe

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 580, Visualization

January 19, 2014 by hgpu

Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 by hgpu

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Hristo Djidjev, Sunil Thulasidasan, Guillaume Chapuis, Rumen Andonov, Dominique Lavenier

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Tags: Algorithms, Bioinformatics, Biology, CUDA, GPU cluster, nVidia, Tesla C2090

December 18, 2013 by hgpu

Development methodologies for GPU and cluster of GPUs

Sylvain Contassot-Vivier, Stephane Vialle, Jens Gustedt

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580

December 17, 2013 by hgpu

All-pairs Shortest Path Algorithm based on MPI+CUDA Distributed Parallel Programming Model

Wu Qingshuang, Tong Chunya, Wang Qiang, Cheng Xiangfu

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Tags: Algorithms, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GT 410 M, Path problems

December 13, 2013 by hgpu

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

P. Berczik, R. Spurzem, L. Wang, S. Zhong, O. Veles, I. Zinchenko, S. Huang, M. Tsai, G. Kennedy, S. Li, L. Naso, C. Li

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Source codes

Tags: Astrophysics, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Package, Tesla C2050, Tesla K20

December 9, 2013 by hgpu

Cluster-SkePU: A Multi-Backend Skeleton Programming Library for GPU Clusters

Mudassar Majeed, Usman Dastgeer, Christoph Kessler

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Tags: Algorithms, Computer science, CUDA, GPU cluster, N-body simulation, nVidia, Tesla M2090

December 4, 2013 by hgpu

American Basket Option Pricing on a multi GPU Cluster

Michael Benguigui, Francoise Baude

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Tags: Algorithms, Computer science, GPU cluster, nVidia, OpenCL, Tesla M2050, Tesla S1070

November 28, 2013 by hgpu

Efficient Multi-GPU Algorithm for All-Pairs Shortest Paths

Guillaume Chapuis, Hristo Djidjev, Rumen Andonov, Sunil Thulasidasan, Dominique Lavenier

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, GPU cluster, nVidia, Path problems, Tesla C2090

November 26, 2013 by hgpu

Investigating the use of GPUs with a Monte Carlo Astrophysical Simulation

James S. Willis

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Tags: Astrophysics, CUDA, Fortran, GPU cluster, nVidia, Tesla C2050, Thesis

November 25, 2013 by hgpu

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Mads R. B. Kristensen, Simon A. F. Lund, Troels Blum, Kenneth Skovhede, Brian Vinter

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Tags: ATI, ATI Radeon HD 7850, Benchmarking, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 680, OpenCL, Python

November 22, 2013 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

A QUDA-branch to compute disconnected diagrams in GPUs

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Resource Centered Computing delivering high parallel performance

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Development methodologies for GPU and cluster of GPUs

All-pairs Shortest Path Algorithm based on MPI+CUDA Distributed Parallel Programming Model

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

Cluster-SkePU: A Multi-Backend Skeleton Programming Library for GPU Clusters

American Basket Option Pricing on a multi GPU Cluster

Efficient Multi-GPU Algorithm for All-Pairs Shortest Paths

Investigating the use of GPUs with a Monte Carlo Astrophysical Simulation

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

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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