high performance computing on graphics processing units: hgpu.org

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Parallel kinetic Monte Carlo simulation of Coulomb glasses

Ezequiel E. Ferrero, Alejandro B. Kolton, Matteo Palassini

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Tags: Algorithms, Condensed matter, CUDA, Disordered Systems and Neural Networks, Monte Carlo simulation, nVidia, nVidia GeForce GTX 470, Package, Tesla C2075, Tesla K20

July 24, 2014 by hgpu

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Koushik Mandal

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2075, Thesis

July 23, 2014 by hgpu

Accelerating Volume Image Registration through Correlation Ratio based Methods on GPUs

Ang Li, Akash Kumar

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Tags: CUDA, Image processing, Image registration, nVidia, Tesla C2075

July 23, 2014 by hgpu

CUD@SAT: SAT Solving on GPUs

Alessandro Dal Pal'u, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, Numerical simulation, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Package, SAT, Tesla C2075

July 15, 2014 by hgpu

High performance MRI simulations of motion on multi-GPU systems

Christos G Xanthis, Ioannis E Venetis, Anthony H Aletras

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Tags: CUDA, Magnetic resonance imaging, Medicine, MRI, nVidia, Physics, Tesla C2070, Tesla C2075

July 6, 2014 by hgpu

The Fast and Wideband MoM Based on GPU and Two-Path AFS Acceleration

Lan Li, Jundong Tan, Zhuo Su, Yunliang Lon

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Tags: CUDA, Integral equations, nVidia, Signal processing, Tesla C2075

June 22, 2014 by hgpu

Enabling High Performance Computing in Cloud Infrastructure using rCUDA

Yousuf Sait I, Vijayalakshmi R

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

June 11, 2014 by hgpu

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 560, Tesla C2075

June 3, 2014 by hgpu

Evaluating GPU Passthrough in Xen for High Performance Cloud Computing

Andrew J. Younge, John Paul Walters, Stephen Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

June 1, 2014 by hgpu

Parallel Distance Threshold Query Processing for Spatiotemporal Trajectory Databases on the GPU

Michael G. Gowanlock, Henri Casanova

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Tags: Algorithms, Computer science, Databases, nVidia, OpenCL, Tesla C2075

May 30, 2014 by hgpu

GPU Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications

John Paul Walters, Andrew J. Younge, Dong-In Kang, Ke-Thia Yao, Mikyung Kang, Stephen P. Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, OpenCL, Tesla C2075, Tesla K20, Virtualization

May 26, 2014 by hgpu

A combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation

Jose Colmenares, Antonella Galizia, Jesus Ortiz, Andrea Clematis, Walter Rocchia

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Tags: Algorithms, Biology, Boltzmann equation, CUDA, Electrostatic potential, Electrostatics, Heterogeneous systems, Macromolecule, MPI, nVidia, nVidia GeForce GTX 580, Poisson Boltzmann, Tesla C2075

May 21, 2014 by hgpu

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

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

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

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

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high performance computing on graphics processing units: hgpu.org

Parallel kinetic Monte Carlo simulation of Coulomb glasses

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

Accelerating Volume Image Registration through Correlation Ratio based Methods on GPUs

CUD@SAT: SAT Solving on GPUs

High performance MRI simulations of motion on multi-GPU systems

The Fast and Wideband MoM Based on GPU and Two-Path AFS Acceleration

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Parallel Distance Threshold Query Processing for Spatiotemporal Trajectory Databases on the GPU

A combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation

Recent source codes

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

ROCm's implementation of Gromacs

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

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