high performance computing on graphics processing units: hgpu.org

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Symbolic Crosschecking of Data-Parallel Floating Point Code

Peter Cyrus Collingbourne

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Tags: Algorithms, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C1060, Thesis

March 20, 2013 by hgpu

Automated and interactive approaches for optimal surface finding based segmentation of medical image data

Shanhui Sun

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Tags: CUDA, Image processing, Medicine, nVidia, Tesla C1060, Thesis, Ultrasound, Visualization

March 14, 2013 by hgpu

Just-in-time Acceleration of JavaScript

Uday Pitambare, Arun Chauhan, Saurabh Malviya

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Tags: Computer science, Java, nVidia, Performance, PTX, Tesla C1060

March 12, 2013 by hgpu

CU2rCU: A CUDA-to-rCUDA Converter

Carlos Reano Gonzalez

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Tesla C1060, Tesla C2050, Thesis

March 9, 2013 by hgpu

Multi-GPU based on multicriteria optimization for motion estimation system

Carlos Garcia, Guillermo Botella, Fermin Ayuso, Manuel Prieto, Francisco Tirado

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Tags: Algorithms, Computer vision, CUDA, Data parallelism, nVidia, Optical flow, Signal processing, Tesla C1060, Tesla M2070

February 27, 2013 by hgpu

A Wrapper of OpenCL library for gVirtus Framework

Roberto Di Lauro

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Tags: Cloud, Computer science, nVidia, nVidia Quadro FX 5800, OpenCL, Tesla C1060

February 25, 2013 by hgpu

Ray Tracing on GPUs

Tom Morris Feist, Florian Wende

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, Raytracing, Tesla C1060, Tesla M2090, Tutorial

February 21, 2013 by hgpu

Complexity Analysis and Algorithm Design for Reorganizing Data to Minimize Non-Coalesced Memory Accesses on GPU

Bo Wu, Zhijia Zhao, Eddy Z. Zhang, Yunlian Jiang, Xipeng Shen

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C1060

February 20, 2013 by hgpu

MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

Real-Time 3D Face Identification from a Depth Camera

Rui Min, Jongmoo Choi, Gerard Medioni, Jean-Luc Dugelay

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Tags: Computer science, Computer vision, CUDA, nVidia, Tesla C1060

February 14, 2013 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

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high performance computing on graphics processing units: hgpu.org

Symbolic Crosschecking of Data-Parallel Floating Point Code

Automated and interactive approaches for optimal surface finding based segmentation of medical image data

Just-in-time Acceleration of JavaScript

CU2rCU: A CUDA-to-rCUDA Converter

Multi-GPU based on multicriteria optimization for motion estimation system

Ray Tracing on GPUs

Complexity Analysis and Algorithm Design for Reorganizing Data to Minimize Non-Coalesced Memory Accesses on GPU

MATLAB and Python for GPU Computing

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Real-Time 3D Face Identification from a Depth Camera

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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