high performance computing on graphics processing units: hgpu.org

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Playdoh: A lightweight Python library for distributed computing and optimisation

Cyrille Rossant, Bertrand Fontaine, Dan F.M. Goodman

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Tags: Computer science, CUDA, Differential equations, Distributed computing, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Package, Partial differential equations, PDEs, Python

December 10, 2011 by hgpu

High Performance Multi-agent System based Simulations

Prashant Sethia

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Tags: Algorithms, Cloud, Computer science, CUDA, Distributed computing, MapReduce, nVidia, Package, Tesla T10

December 8, 2011 by hgpu

Three-Dimensional Modeling of Long-Wave Runup: Simulation of Tsunami Inundation with GPU-SPHysics

Robert Weiss, Andrew James Munoz, Robert A. Dalrymple, Alexis Herault, Giuseppe Bilotta

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Tags: Algorithms, CUDA, Earth and Space Sciences, nVidia, Package, Tesla C1060

December 8, 2011 by hgpu

Speeding up the evaluation phase of GP classification algorithms on GPUs

Alberto Cano, Amelia Zafra, Sebastian Ventura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package

December 8, 2011 by hgpu

GPU Implementation of the Keccak Hash Function Family

Pierre-Louis Cayrel, Gerhard Hoffmann, Michael Schneider

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 295, Package, Security, Tesla C2050

December 7, 2011 by hgpu

GMM based Fisher vector calculation on GPGPU

Erik Bodzsar, Balint Daroczy, Istvan Petras, Andras A. Benczur

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Tags: Clustering, CUDA, Databases, Image processing, nVidia, nVidia GeForce GTX 285, Package, Performance, SIFT

December 5, 2011 by hgpu

Implementing CFD (Computational Fluid Dynamics) in OpenCL for Building Simulation

Yue Wang, Ali Malkawi, Yun Yi

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Tags: Fluid dynamics, nVidia, nVidia GeForce 9400 M, nVidia GeForce 9800 GTX, OpenCL, Package

December 4, 2011 by hgpu

Programming hybrid systems with implicit memory based synchronization

Jens Breitbart

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Tags: Algorithms, Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 480, Package, Tesla C2050

December 3, 2011 by hgpu

On the design of architecture-aware algorithms for emerging applications

Seunghwa Kang

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Tags: Algorithms, Benchmarking, Biology, Cell processor, Computational biology, CUDA, Image processing, MapReduce, nVidia, Package, Tesla C1060, Thesis

December 2, 2011 by hgpu

Efficient Cubic B-spline Image Interpolation on a GPU

Frederic Champagnat, Yves Le Sant

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 260 M, Package, Tesla C2050

December 2, 2011 by hgpu

Using CUDA for Exhaustive Password Recovery

Tore Kasper Frederiksen

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTX 480, Package, Security

November 30, 2011 by hgpu

GPU-Accelerated SPH Model for Water Waves and Other Free Surface Flows

Robert Anthony Dalrymple, Alexis Herault, Giuseppe Bilotta, Rozita Jalali Farahani

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Tags: CUDA, Fluid dynamics, nVidia, OpenGL, Package, Visualization

November 30, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Playdoh: A lightweight Python library for distributed computing and optimisation

Three-Dimensional Modeling of Long-Wave Runup: Simulation of Tsunami Inundation with GPU-SPHysics

Speeding up the evaluation phase of GP classification algorithms on GPUs

GPU Implementation of the Keccak Hash Function Family

GMM based Fisher vector calculation on GPGPU

Implementing CFD (Computational Fluid Dynamics) in OpenCL for Building Simulation

Programming hybrid systems with implicit memory based synchronization

On the design of architecture-aware algorithms for emerging applications

Efficient Cubic B-spline Image Interpolation on a GPU

Using CUDA for Exhaustive Password Recovery

GPU-Accelerated SPH Model for Water Waves and Other Free Surface Flows

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

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