high performance computing on graphics processing units: hgpu.org

Applications

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Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Brijmohan Singh, Nitin Gupta, Rashi Tyagi, Ankush Mitta, Debashish Ghosh

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Pattern recognition

October 24, 2011 by hgpu

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Pablo Lamilla Alvarez

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Tags: Computer science, GPU cluster, nVidia, nVidia GeForce GT 220, OpenCL, Performance, Thesis

October 24, 2011 by hgpu

Breaking DVB-CSA

Erik Tews, Julian Walde, Michael Weiner

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, Security

October 24, 2011 by hgpu

ASAMgpu V1.0-a moist fully compressible atmospheric model using graphics processing units (GPUs)

S. Horn

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Tags: Algorithms, Earth and Space Sciences, Geoscience, GLSL, OpenGL, Weather prediction

October 24, 2011 by hgpu

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

Joo Hong Lee, Mark T. Jones, Paul E. Plassmann

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Tags: ATI, ATI Radeon HD 5750, Computer science, Monte Carlo simulation, OpenCL, Pseudo-random number generators

October 24, 2011 by hgpu

APTCC: Auto Parallelizing Translator From C To CUDA

Takehiko Nawataa, Reiji Suda

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, Tesla C2050

October 24, 2011 by hgpu

Using OpenCL for Implementing Simple Parallel Graph Algorithms

Michael J. Dinneen, Masoud Khosravani, Andrew Probert

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, OpenCL, Tesla C2050

October 24, 2011 by hgpu

Democratizing General Purpose GPU Programming through OpenCL and Scala

Raider Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C870

October 24, 2011 by hgpu

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Tags: APU, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

October 24, 2011 by hgpu

Optimizing a Near-duplicate Document Detection System with SIMD Technologies

Xinpan Yuan, Jun Long, Hao Zhang, Zuping Zhang, Weihua Gui

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Tags: Algorithms, Clustering, Computer science, nVidia, nVidia GeForce 8600 GT, OpenCL, Optimization

October 24, 2011 by hgpu

A Parallel Ray Tracing Architecture Suitable for Application-Specific Hardware and GPGPU Implementations

Alexandre S. Nery, Nadia Nedjah, Felipe M.G. Franca, Lech Jozwiak

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 465, Raytracing, Rendering, Virtual reality

October 23, 2011 by hgpu

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

Roberto Roverso

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Tags: Algorithms, Computer science, Consensus, CUDA, Network communications, Networks, nVidia, nVidia GeForce GTX 295, Optimization, Thesis

October 23, 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

Applications

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Breaking DVB-CSA

ASAMgpu V1.0-a moist fully compressible atmospheric model using graphics processing units (GPUs)

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

APTCC: Auto Parallelizing Translator From C To CUDA

Using OpenCL for Implementing Simple Parallel Graph Algorithms

Democratizing General Purpose GPU Programming through OpenCL and Scala

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Optimizing a Near-duplicate Document Detection System with SIMD Technologies

A Parallel Ray Tracing Architecture Suitable for Application-Specific Hardware and GPGPU Implementations

Design and Implementation of Centrally-Coordinated Peer-to-Peer Live-streaming

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

Most viewed papers (last 30 days)