high performance computing on graphics processing units: hgpu.org

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Locality Analysis for Characterizing Applications Based on Sparse Matrices

Noboru Tanabe, Sonoko Tomimori, Masami Takata, Kazuki Joe

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

December 9, 2013 by hgpu

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Enes Bajrovic, Siegfried Benkner, Jiri Dokulil, Martin Sandrieser

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C1060, Tesla C2050

November 27, 2013 by hgpu

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

Achille Peternier, Marco Defilippi, Paolo Pasquali, Alessio Cantone, Rolf Krause, Raffaele Vitulli, Fumitaka Ogushi, Alberto Meroni

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenCL, Tesla C2050

November 27, 2013 by hgpu

PG-PuReMD: A Parallel-GPU Reactive Molecular Dynamics Package

Sudhir B Kylasa, Hasan Metin Aktulga, Ananth Grama

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Tags: Algorithms, Chemistry, CUDA, Molecular dynamics, nVidia, Tesla C2050

November 26, 2013 by hgpu

Diagrammatic Determinantal Quantum Monte Carlo Calculations on GPUs

Markus Schmitt

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Tags: Algorithms, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 480, Physics, QMC, Tesla C2050, Thesis

November 25, 2013 by hgpu

Investigating the use of GPUs with a Monte Carlo Astrophysical Simulation

James S. Willis

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Tags: Astrophysics, CUDA, Fortran, GPU cluster, nVidia, Tesla C2050, Thesis

November 25, 2013 by hgpu

Pseudo Random Number Generators on Graphics Processing Units, with Applications in Finance

Matthew Anker

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, Pseudo-random number generators, Tesla C2050, Thesis

November 25, 2013 by hgpu

Fast approximate k-nearest neighbours search using GPGPU

Niko Lukac, Borut Zalik

Tags: Computer science, CUDA, Hashing, Nearest neighbour, nVidia, Tesla C2050

November 24, 2013 by hgpu

Adaptive implementation selection in the SkePU skeleton programming library

Usman Dastgeer, Lu Li, Christoph Kessler

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Tags: Computer science, CUDA, Machine learning, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

November 19, 2013 by hgpu

Graphics Processing Unit-Accelerated Quantitative Trait Loci Detection

Guillaume Chapuis, Olivier Filangi, Dominique Lavenier, Jean Michel J. M. Elsen, Pascale Leroy

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Tags: Bioinformatics, Biology, CUDA, nVidia, Tesla C2050

November 16, 2013 by hgpu

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

Michal Januszewski, Marcin Kostur

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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

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Locality Analysis for Characterizing Applications Based on Sparse Matrices

Autotuning of Pattern Runtimes for Accelerated Parallel Systems

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

PG-PuReMD: A Parallel-GPU Reactive Molecular Dynamics Package

Diagrammatic Determinantal Quantum Monte Carlo Calculations on GPUs

Investigating the use of GPUs with a Monte Carlo Astrophysical Simulation

Pseudo Random Number Generators on Graphics Processing Units, with Applications in Finance

Fast approximate k-nearest neighbours search using GPGPU

Adaptive implementation selection in the SkePU skeleton programming library

Graphics Processing Unit-Accelerated Quantitative Trait Loci Detection

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

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

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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