high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Floating-point data compression at 75 Gb/s on a GPU

Molly A. O'Neil, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce FX 5600, Package, Performance, Programming techniques

August 22, 2011 by hgpu

Towards metaprogramming for parallel systems on a chip

Lee Howes, Anton Lokhmotov, Alastair F. Donaldson, Paul H.J. Kell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

August 22, 2011 by hgpu

Load Balancing versus Occupancy Maximization on Graphics Processing Units: The Generalized Hough Transform as a Case Study

Juan Gomez-Luna, Jose Maria Gonzalez-Linares, Jose Ignacio Benavides, Emilio L. Zapata, Nicolas Guil

Tags: Computer science, CUDA, Image processing, nVidia, Programming techniques

August 22, 2011 by hgpu

Top ten ways to make formal methods for HPC practical

Ganesh Gopalakrishnan, Robert M. Kirby

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Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Performance

August 22, 2011 by hgpu

Compiler and runtime support for enabling generalized reduction computations on heterogeneous parallel configurations

Vignesh T. Ravi, Wenjing Ma, David Chiu, Gagan Agrawal

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX

August 22, 2011 by hgpu

Reusable software components for accelerator-based clusters

M. Mustafa Rafique, Ali R. Butt, Eli Tilevich

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9600 M GT, Performance, Playstation

August 22, 2011 by hgpu

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Martin Sandrieser, Siegfried Benkner, Sabri Pllana

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, OpenMP, Presentation

August 22, 2011 by hgpu

Accelerating Haskell array codes with multicore GPUs

Manuel M.T. Chakravarty, Gabriele Keller, Sean Lee, Trevor L. McDonell, Vinod Grover

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Tags: Code generation, Computer science, CUBLAS, CUDA, Data parallelism, nVidia, Performance, Programming Languages, Tesla T10

August 22, 2011 by hgpu

A programming model for GPU-based parallel computing with scalability and abstraction

Balazs Domonkos, Gabor Jakab

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Tags: 3D Graphics and Realism, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenMP, Programming techniques

August 22, 2011 by hgpu

Compiling Python to a hybrid execution environment

Rahul Garg, Jose Nelson Amaral

Tags: ATI, ATI CAL, BLAS, Compilers, Computer science, OpenCL, Python

August 21, 2011 by hgpu

A declarative API for particle systems

Pavel Krajcevski, John Reppy

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Tags: 3D Graphics and Realism, Computer science, GLSL, OpenCL

August 21, 2011 by hgpu

Software architecture and system validation of an open, unified model for accelerated multicore computing

C. H. Crawford, D. J. Burdick, J. N. Dale, E. F. Ford, R. A. Mikosh, A. Nobles, V. To

Tags: Computer science, Heterogeneous systems, OpenCL

August 21, 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

Floating-point data compression at 75 Gb/s on a GPU

Towards metaprogramming for parallel systems on a chip

Load Balancing versus Occupancy Maximization on Graphics Processing Units: The Generalized Hough Transform as a Case Study

Top ten ways to make formal methods for HPC practical

Compiler and runtime support for enabling generalized reduction computations on heterogeneous parallel configurations

Reusable software components for accelerator-based clusters

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Accelerating Haskell array codes with multicore GPUs

A programming model for GPU-based parallel computing with scalability and abstraction

Compiling Python to a hybrid execution environment

A declarative API for particle systems

Software architecture and system validation of an open, unified model for accelerated multicore computing

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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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