high performance computing on graphics processing units: hgpu.org

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Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Michael Boyer, Kevin Skadron, Shuai Che, Nuwan Jayasena

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 6670, Computer science, Heterogeneous systems, OpenCL, Performance, Task scheduling

April 8, 2013 by hgpu

Adapting Particle Filter Algorithms to Many-Core Architectures

Mehdi Chitchian, Alexander S. van Amesfoort, Andrea Simonetto, Tamas Keviczky, Henk J. Sips

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Tags: Algorithms, ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, Bayesian, Computer science, Computer vision, CUDA, Filtering, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Particle filtering

April 4, 2013 by hgpu

OpenCL parallel Processing using General Purpose Graphical Processing units – TiViPE software development

Tino Lourens

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Tags: ATI, ATI Radeon HD 6310, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 560, OpenCL

April 1, 2013 by hgpu

A Discussion of Selected Vienna-Libraries for Computational Science

Karl Rupp, Florian Rudolf, Josef Weinbub

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, OpenCL, Programming techniques, Review

April 1, 2013 by hgpu

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

Michael Christopher Delorme

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Tags: APU, ATI, ATI Radeon HD 5870, ATI Radeon HD 6530, ATI Radeon HD 6550, Computer science, Heterogeneous systems, nVidia, OpenCL, Sorting, Thesis, Tutorial

March 26, 2013 by hgpu

Improving Performance Portability in OpenCL Programs

Yao Zhang, Mark Sinclair II, Andrew A. Chien

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Tags: APU, ATI, Benchmarking, Computer science, FFT, nVidia, OpenCL, Tesla C2050

March 26, 2013 by hgpu

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Thibault Person, Francois Bodin

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel, Intel Phi, nVidia, OpenCL, Package, Performance, Portability, Tesla K20

March 24, 2013 by hgpu

GPGPU Test Suite Minimisation: Search Based Software Engineering Performance Improvement Using Graphics Cards

Shin Yoo, Mark Harman, Shmuel Ur

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Tags: Algorithms, ATI, ATI Radeon HD 4850, Computer science, Java, OpenCL, Software Engineering

March 21, 2013 by hgpu

Stream Join Processing on Heterogeneous Processors

Tomas Karnagel, Benjamin Schlegel, Dirk Habich, Wolfgang Lehner

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Tags: ATI, ATI Radeon HD 7660, Computer science, Heterogeneous systems, OpenCL

March 21, 2013 by hgpu

clMAGMA: High Performance Dense Linear Algebra with OpenCL

Chongxiao Cao, Jack Dongarra, Peng Du, Mark Gates, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Package, Tesla S2050

March 18, 2013 by hgpu

Volume Raycasting Performance Using DirectCompute

Hakan Johansson

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, DirectCompute, DirectX, Medicine, Rendering, Thesis, Tomography

March 18, 2013 by hgpu

Exploring power efficiency and optimizations targeting heterogeneous applications

Yash Sanjeev Ukidave

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Tags: AMD Fusion, ATI, ATI Radeon HD 7770, Computer science, Energy-efficient computing, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, Thesis

March 16, 2013 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

Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Adapting Particle Filter Algorithms to Many-Core Architectures

OpenCL parallel Processing using General Purpose Graphical Processing units – TiViPE software development

A Discussion of Selected Vienna-Libraries for Computational Science

Parallel Sorting on the Heterogeneous AMD Fusion Accelerated Processing Unit

Improving Performance Portability in OpenCL Programs

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

GPGPU Test Suite Minimisation: Search Based Software Engineering Performance Improvement Using Graphics Cards

Stream Join Processing on Heterogeneous Processors

clMAGMA: High Performance Dense Linear Algebra with OpenCL

Volume Raycasting Performance Using DirectCompute

Exploring power efficiency and optimizations targeting heterogeneous applications

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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