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hgpu.org » Applications » Physics » Astrophysics

Direct N-body code on low-power embedded ARM GPUs

David Goz, Sara Bertocco, Luca Tornatore, Giuliano Taffoni

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Tags: ARM, Astrophysics, FPGA, Heterogeneous systems, Instrumentation and Methods for Astrophysics, N-body simulation, OpenCL, OpenMPI, SoC

January 27, 2019 by hgpu

StePS: A Multi-GPU Cosmological N-body Code for Compactified Simulations

Gabor Racz, Istvan Szapudi, Laszlo Dobos, Istvan Csabai, Alexander S. Szalay

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Tags: Astrophysics, Cosmology, CUDA, MPI, N-body simulation, nVidia, OpenMP, Package, Tesla K80

November 18, 2018 by hgpu

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Daina Moise, Simon J. Pennycook, Kristyn Maschoff, Jason Sewall, Nalini Kumar, Shirley Ho, Mike Ringenburg, Prabhat, Victor Lee

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Tags: Astrophysics, Cosmology, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Package, TensorFlow, Tesla P100

August 19, 2018 by hgpu

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

Sergey Khrapov, Alexander Khoperskov

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Tags: Astrophysics, CUDA, hydrodynamics, nVidia, OpenMP, Tesla K20, Tesla K40, Tesla K80

July 28, 2018 by hgpu

ARC: Adaptive Ray-tracing with CUDA, a New Ray Tracing Code for Parallel GPUs

Blake Hartley, Massimo Ricotti

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Tags: Astrophysics, Cosmology, CUDA, MPI, nVidia, Raytracing

July 21, 2018 by hgpu

Ray-traced Radiative Transfer on Massively Threaded Architectures

Samuel Paul Thomson

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Tags: Astrophysics, CUDA, nVidia, Raytracing, Tesla M2090, Thesis

July 1, 2018 by hgpu

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

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Tags: Astrophysics, FPGA, OpenCL, Signal processing

June 17, 2018 by hgpu

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

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Tags: AMD Radeon R7 370, Astrophysics, ATI, FPGA, OpenCL

June 2, 2018 by hgpu

GAMER-2: a GPU-accelerated adaptive mesh refinement code — accuracy, performance, and scalability

Hsi-Yu Schive, John A. ZuHone, Nathan J. Goldbaum, Matthew J. Turk, Massimo Gaspari, Chin-Yu Cheng

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Tags: ARM, Astrophysics, Chemistry, CUDA, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, nVidia, OpenMP, Package, Tesla K20, Tesla P100

December 24, 2017 by hgpu

Deep learning for galaxy surface brightness profile fitting

D. Tuccillo, M. Huertas-Company, E. Decenciere, S. Velasco-Forero, H. Dominguez Sanchez, P. Dimauro

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Tags: Astrophysics, Deep learning, Keras, nVidia, nVidia GeForce GTX Titan X

November 16, 2017 by hgpu

Scalable Streaming Tools for Analyzing N-body Simulations: Finding Halos and Investigating Excursion Sets in One Pass

Nikita Ivkin, Zaoxing Liu, Lin F. Yang, Srinivas Suresh Kumar, Gerard Lemson, Mark Neyrinck, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari

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Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 1080, Tesla C2050, Tesla C2070

November 7, 2017 by hgpu

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Marco Tazzari, Frederik Beaujean, Leonardo Testi

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 1060, Package, Python, Tesla P100

September 28, 2017 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Applications

Direct N-body code on low-power embedded ARM GPUs

StePS: A Multi-GPU Cosmological N-body Code for Compactified Simulations

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

Smoothed-Particle Hydrodynamics Models: Implementation Features on GPUs

ARC: Adaptive Ray-tracing with CUDA, a New Ray Tracing Code for Parallel GPUs

Ray-traced Radiative Transfer on Massively Threaded Architectures

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

GAMER-2: a GPU-accelerated adaptive mesh refinement code — accuracy, performance, and scalability

Deep learning for galaxy surface brightness profile fitting

Scalable Streaming Tools for Analyzing N-body Simulations: Finding Halos and Investigating Excursion Sets in One Pass

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Recent source codes

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Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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