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Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

A. Gianelle, S. Amerio, D. Bastieri, M. Corvo, W. Ketchum, T. Liu, A. Lonardo, D. Lucchesi, S. Poprocki, R. Rivera, L. Tosoratto, P. Vicini, P. Wittich

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Tags: ATI, ATI Radeon HD 7970, CUDA, High Energy Physics - Experiment, Instrumentation and Detectors, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Physics, Tesla K20, Tesla M2050

December 6, 2013 by hgpu

Fast quantum Monte Carlo on a GPU

Y. Lutsyshyn

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Tags: Computational Physics, Condensed matter, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, Physics, Tesla K20, Tesla M2090

December 6, 2013 by hgpu

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Mohamed Wahib, Naoya Maruyama

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Tags: CUDA, Earth and Space Sciences, nVidia, OpenACC, Tesla K20, Tesla M2075, Weather Prediction Model

November 29, 2013 by wahibium

Hybrid Programming using OpenSHMEM and OpenACC

Matthew Baker, Swaroop Pophale, Jean-Charles Vasnier, Haoqiang Jin, Oscar Hernandez

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Tags: Computer science, CUDA, MPI, nVidia, OpenACC, Performance, Tesla K20

November 28, 2013 by hgpu

Implementation of the twisted mass fermion operator in the QUDA library

Alexei Strelchenko, Constantia Alexandrou, Giannis Koutsou, Alejandro Vaquero Aviles-Casco

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Tags: CUDA, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla K20

November 19, 2013 by hgpu

GPU Enhancement of the Trigger to Extend Physics Reach at the Large Hadron Collider

P. Lujan, V. Halyo, A. Hunt, P. Jindal, P. LeGresley

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Tags: Algorithms, CUDA, Instrumentation and Detectors, nVidia, Physics, Tesla C2075, Tesla K20

November 13, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Source codes

Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Performance Evaluation of R with Intel Xeon Phi Coprocessor

Yaakoub El-Khamra, Niall Gaffney, David Walling, Eric Wernert, Weijia Xu, Hui Zhang

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Source codes

Tags: Computer science, CUDA, CULA, High-level Languages, Intel Phi, Intel Xeon Phi, nVidia, Package, Performance, Tesla K20

November 12, 2013 by hgpu

First Steps Towards More Numerical Reproducibility

Fabienne Jezequel, Philippe Langlois, Nathalie Revol

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, Numerical simulation, nVidia, OpenCL, Tesla K20

November 11, 2013 by hgpu

Towards a Portable and Future-proof Particle-in-Cell Plasma Physics Code

R. F. Bird, S. J. Pennycook, S. A. Wright, S. A. Jarvis

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Tags: Algorithms, Computer science, nVidia, OpenCL, Particle-in-cell methods, Physics, Plasma physics, Tesla C1060, Tesla C2050, Tesla K20

November 10, 2013 by hgpu

GPU-Based Space-Time Adaptive Processing (STAP) for Radar

Thomas M. Benson, Ryan K. Hersey, Edwin Culpepper

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia Quadro 3000 M, Tesla K20, Tesla M2090

November 8, 2013 by hgpu

A Game Architecture Based on Multiple GPUs With Energy Management

Marcelo Zamith, Luis Valente, Mark Joselli, Jose Silva Junior, Esteban Clua, Bruno Feijo

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Tags: Computer science, Energy-efficient computing, Games, nVidia, nVidia GeForce GTX 480, Tesla K20

November 8, 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

Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

Fast quantum Monte Carlo on a GPU

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Hybrid Programming using OpenSHMEM and OpenACC

Implementation of the twisted mass fermion operator in the QUDA library

GPU Enhancement of the Trigger to Extend Physics Reach at the Large Hadron Collider

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Performance Evaluation of R with Intel Xeon Phi Coprocessor

First Steps Towards More Numerical Reproducibility

Towards a Portable and Future-proof Particle-in-Cell Plasma Physics Code

GPU-Based Space-Time Adaptive Processing (STAP) for Radar

A Game Architecture Based on Multiple GPUs With Energy Management

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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