high performance computing on graphics processing units: hgpu.org

hgpu.org » Python

The Astrophysical Multipurpose Software Environment

F.I. Pelupessy, A. van Elteren, N. de Vries, S.L.W. McMillan, N. Drost, S.F. Portegies Zwart

View

Download (PDF)

Source codes

Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, nVidia, Package, Python

July 21, 2013 by hgpu

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Matthias Alexander Lee

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Computational Complexity, CUDA, nVidia, Package, Python, RNA, Sequence alignment, Signal processing

May 31, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

View

Download (PDF)

Source codes

Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

GPU Scripting and Code Generation with PyCUDA

Andreas Klockner, Nicolas Pinto, Bryan Catanzaro, Yunsup Lee, Paul Ivanov, Ahmed Fasih

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

CMCpy: Genetic Code-Message Coevolution Models in Python

Peter J. Becich, Brian P. Stark, Harish S. Bhat, David H. Ardell

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 460, Package, Python

March 31, 2013 by hgpu

OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU

Cornelius Wefelscheid, Olaf Hellwich

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 570, Optimization, Package, Python

March 2, 2013 by hgpu

MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

View

Download (PDF)

Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

A multi-lane traffic simulation model via continuous cellular automata

Emanuele Rodaro, Oznur Yeldan

View

Download (PDF)

Source codes

Tags: Cellular automata, Computer science, CUDA, nVidia, nVidia GeForce GT 555 M, Package, Python

February 9, 2013 by hgpu

Enabling Inter-Machine Parallelism in High-Level Languages with SEJITS and MapReduce

Michael Driscoll, Evangelos Georganas, Penporn Koanantakool

View

Download (PDF)

Tags: Computer science, CUDA, MapReduce, nVidia, Programming techniques, Python, Tesla M2050

February 9, 2013 by hgpu

Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods

Christopher Cooper, Lorena A. Barba

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biophysics, Boltzmann equation, Computational Physics, Computer science, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

January 31, 2013 by hgpu

Particle method on GPU

Jean-Matthieu Etancelin, Georges-Henri Cottet, Christophe Picard, Franck Perignon

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 6770 M, Computer science, OpenCL, Python

January 31, 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

* * *

high performance computing on graphics processing units: hgpu.org

The Astrophysical Multipurpose Software Environment

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Directive-based Approach to Heterogeneous Computing

Solving Wave Equations on Unstructured Geometries

GPU Scripting and Code Generation with PyCUDA

CMCpy: Genetic Code-Message Coevolution Models in Python

OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU

MATLAB and Python for GPU Computing

A multi-lane traffic simulation model via continuous cellular automata

Enabling Inter-Machine Parallelism in High-Level Languages with SEJITS and MapReduce

Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods

Particle method on GPU

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)