high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Generating GPU Code from a High-level Representation for Image Processing Kernels

Richard Membarth, Anton Lokhmotov, Jurgen Teich

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, nVidia Quadro FX 5800, OpenCL, Optimization, Tesla C2050

September 26, 2011 by hgpu

LLVM to PTX Backend

Marco Keller

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, PTX

September 26, 2011 by hgpu

A Uniform Platform to Support Multigenerational GPUs for High Performance Stream-based Computing

Pablo Lamilla Alvarez, Shinichi Yamagiwa, Masahiro Arai, Koichi Wada

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 280, OpenCL, OpenGL, Performance

September 26, 2011 by hgpu

High-level GPU computing with jacket for MATLAB and C/C++

Gallagher Pryor, Brett Lucey, Sandeep Maddipatla, Chris McClanahan, John Melonakos, Vishwanath Venugopalakrishnan, Krunal Patel, Pavan Yalamanchili, James Malcolm

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Source codes

Tags: Computer science, CUDA, FFT, Image processing, Linear Algebra, nVidia, nVidia GeForce 9600, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package, PTX, Tesla C1060, Tesla C2070

September 26, 2011 by hgpu

From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming

Peng Du, Rick Weber, Piotr Luszczek, Stanimire Tomov, Gregory Peterson, Jack Dongarra

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Optimization, Performance, Tesla C2050

September 26, 2011 by hgpu

Identifying scalar behavior in CUDA kernels

Sylvain Collange

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Tags: Benchmarking, Code generation, Compilers, Computer science, CUDA, nVidia, PTX

September 26, 2011 by hgpu

Putting Automatic Polyhedral Compilation for GPGPU to Work

Soufiane Baghdadi, Armin Grosslinger, Albert Cohen

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Source codes

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, Package

September 26, 2011 by hgpu

Running unstructured grid-based CFD solvers on modern graphics hardware

Andrew Corrigan, Fernando F. Camelli, Rainald Lohner, John Wallin

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Tesla

September 26, 2011 by hgpu

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

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Tags: Algorithms, Code generation, Computer science, nVidia, OpenCL, Optimization, Statistics, Tesla C1060

September 25, 2011 by hgpu

Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

Thomas Grosser, Alexandros Gremm, Sebastian Veith, Gerald Heim, Wolfgang Rosenstiel, Victor Medeiros, Manoel Eusebio de Lima

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Tags: Earth and Space Sciences, FPGA, Geoscience, Heterogeneous systems, nVidia, OpenCL, Optimization, Seismic modeling, Seismology, Tesla T10P

September 25, 2011 by hgpu

Harnessing the Power of GPUs without Losing Abstractions in SaC and ArrayOL: A Comparative Study

Jing Guo, Wendell Rodrigues, Jeyarajan Thiyagalingamz, Frederic Guyomarch, Pierre Boulet, Sven-Bodo Scholz

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Video encoding

September 25, 2011 by hgpu

Accelerating image recognition on mobile devices using GPGPU

Miguel Bordallo Lopez, Henri Nykanen, Jari Hannuksela, Olli Silven, Markku Vehvilainen

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Tags: Algorithms, Computer science, Image processing, Image recognition, OpenCL, OpenGL

September 25, 2011 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

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high performance computing on graphics processing units: hgpu.org

Programming

Generating GPU Code from a High-level Representation for Image Processing Kernels

LLVM to PTX Backend

A Uniform Platform to Support Multigenerational GPUs for High Performance Stream-based Computing

High-level GPU computing with jacket for MATLAB and C/C++

From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming

Identifying scalar behavior in CUDA kernels

Putting Automatic Polyhedral Compilation for GPGPU to Work

Running unstructured grid-based CFD solvers on modern graphics hardware

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

Harnessing the Power of GPUs without Losing Abstractions in SaC and ArrayOL: A Comparative Study

Accelerating image recognition on mobile devices using GPGPU

Recent source codes

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MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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