high performance computing on graphics processing units: hgpu.org

Applications

Fast computation of MadGraph amplitudes on graphics processing unit (GPU)

K. Hagiwara, J. Kanzaki, Q. Li, N. Okamura, T. Stelzer

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Tags: Computational Physics, CUDA, Fortran, Monte Carlo integration, nVidia, Physics, Pseudo-random number generators, QCD, Tesla C2075

May 6, 2013 by hgpu

Data-rich astronomy: mining synoptic sky surveys

Stefano Cavuoti

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GT 540 M, Thesis

May 3, 2013 by hgpu

GPU accelerated Trotter-Suzuki solver for quantum spin dynamics

Axel D. Dente, Carlos S. Bederian, Pablo R. Zangara, Horacio M. Pastawski

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Tags: Algorithms, Computational Physics, CUDA, nVidia, Physics, Quantum Physics, Spin Systems, Statistical Mechanics, Tesla C2070

May 2, 2013 by hgpu

GPU Acceleration of the Variational Monte Carlo Method for Many Body Physics

Rajagopalan Kaushik Ragavan

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Tags: CUDA, Data parallelism, Heterogeneous systems, Monte Carlo simulation, MPI, nVidia, Physics, Tesla M2070, Thesis

May 1, 2013 by hgpu

Analysis of Multicore CPU and GPU Toward Parallelization of Total Focusing Method Ultrasound Reconstruction

Jason Lambert, Antoine Pedron, Guillaume Gens, Franck Bimbard, Lionel Lacassagne, Ekaterina Iakovleva, Stephane Le Berre

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Physics, Ultrasound

April 29, 2013 by hgpu

Computer Simulation of Saturn’s Ring Structure

Cole Kendrick

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Tags: Astrophysics, ATI, ATI Radeon HD 5850, Gravitation, MPI, N-body simulation, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Tesla S2050

April 21, 2013 by hgpu

Accelerating Image Reconstruction in Three-Dimensional Optoacoustic Tomography on Graphics Processing Units

Kun Wang, Chao Huang, Yu-Jiun Kao, Cheng-Ying Chou, Alexander A. Oraevsky, Mark A. Anastasio

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Tags: CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060, Tesla C2050, Tomography

April 9, 2013 by hgpu

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

R. Capuzzo-Dolcettaa, M. Spera

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7870, ATI Radeon HD 7970, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Tesla C1060, Tesla C2050, Tesla K20

April 9, 2013 by hgpu

Exploring complex quantum systems with a hybrid CPU-GPU computing platform

A. Yu. Polyakov, S. Denisov, P. Hanggi

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Tags: CUDA, Differential equations, nVidia, Physics, Quantum Physics, Tesla M2050

April 7, 2013 by hgpu

Astrophysical data mining with GPU. A case study: genetic classification of globular clusters

Stefano Cavuoti, Mauro Garofalo, Massimo Brescia, Maurizio Paolillo, Antonio Pescape', Giuseppe Longo, Giorgio Ventre

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Tags: Algorithms, Astrophysics, CUDA, Data mining, Globular clusters, nVidia, nVidia GeForce GT 540 M

April 3, 2013 by hgpu

GRay: a Massively Parallel GPU-Based Code for Ray Tracing in Relativistic Spacetimes

Chi-Kwan Chan, Dimitrios Psaltis, Feryal Ozel

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GT 650 M, Package, Raytracing, Tesla M2090

March 23, 2013 by hgpu

Parallelization with Different API on Multicore Architecture

Georg Rempfer

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Tags: Chemistry, CUDA, Liquid crystals, nVidia, nVidia GeForce GTX 680, Physics, Statistical Mechanics, Thesis

March 18, 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

Fast computation of MadGraph amplitudes on graphics processing unit (GPU)

Data-rich astronomy: mining synoptic sky surveys

GPU accelerated Trotter-Suzuki solver for quantum spin dynamics

GPU Acceleration of the Variational Monte Carlo Method for Many Body Physics

Analysis of Multicore CPU and GPU Toward Parallelization of Total Focusing Method Ultrasound Reconstruction

Computer Simulation of Saturn’s Ring Structure

Accelerating Image Reconstruction in Three-Dimensional Optoacoustic Tomography on Graphics Processing Units

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

Exploring complex quantum systems with a hybrid CPU-GPU computing platform

Astrophysical data mining with GPU. A case study: genetic classification of globular clusters

GRay: a Massively Parallel GPU-Based Code for Ray Tracing in Relativistic Spacetimes

Parallelization with Different API on Multicore Architecture

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

Most viewed papers (last 30 days)