high performance computing on graphics processing units: hgpu.org

David Pierson Bradway, Michael Johannes Pihl, Andreas Krebs, Borislav Gueorguiev Tomov, Carsten Straso Kjaer, Svetoslav Ivanov Nikolov, Jorgen Arendt Jensen

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Tags: Algorithms, ATI, ATI Radeon HD 7850, Image processing, OpenCL, Ultrasound, Visualization

February 26, 2014 by hgpu

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Mads R. B. Kristensen, Simon A. F. Lund, Troels Blum, Kenneth Skovhede, Brian Vinter

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Tags: ATI, ATI Radeon HD 7850, Benchmarking, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 680, OpenCL, Python

November 22, 2013 by hgpu

Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

Perhaad Mistry, Yash Ukidave, Dana Schaa, David Kaeli

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Tags: APU, ATI, ATI Radeon HD 7850, ATI Radeon HD 7970, Benchmarking, Computer science, Computer vision, Heterogeneous systems, OpenCL, Performance

April 22, 2013 by hgpu

GPU Ray Tracing – Comparative Study of Ray-Triangle Intersection Algorithms

Vladimir Shumskiy, Alexandre Parshin

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Tags: ATI, ATI Radeon HD 6870, ATI Radeon HD 7850, Computer science, DirectX, nVidia, nVidia GeForce GT 240 M, nVidia GeForce GTX 560, Raytracing, Rendering

November 29, 2012 by hgpu

Modification of self-organizing migration algorithm for OpenCL framework

Michal Pavlech, Jan Seckar

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Tags: Algorithms, ATI, ATI Radeon HD 7850, Computer science, nVidia, OpenCL, Optimization, Tesla C2075

September 22, 2012 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

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high performance computing on graphics processing units: hgpu.org

Pragma Directed Shared Memory Centric Optimizations on GPUs

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

Solving prime-field ECDLPs on GPUs with OpenCL

Optimizing OpenCL Local Work Group Size With Machine Learning

Brute force de-shredding algorithm using the GPU

Stealing Webpages Rendered on Your Browser by Exploiting GPU Vulnerabilities

Real-Time GPU Implementation of Transverse Oscillation Vector Velocity Flow Imaging

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

GPU Ray Tracing – Comparative Study of Ray-Triangle Intersection Algorithms

Modification of self-organizing migration algorithm for OpenCL framework

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

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