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Fast Exact String Matching on the GPU

Michael C. Schatz, Cole Trapnell

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Tags: Algorithms, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Search, String matching, Suffix trees

February 20, 2011 by hgpu

Program Optimization Study on a 128-Core GPU

Shane Ryoo, Christopher I. Rodrigues, Sam S. Stone, Sara S. Baghsorkhi, Sain-Zee Ueng, and Wen-mei W. Hwu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Programming techniques

February 20, 2011 by hgpu

MCUDA: An Efficient Implementation of CUDA Kernels on Multi-cores

John A. Stratton, Sam S. Stone, and Wen-mei W. Hwu

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, Package

February 20, 2011 by hgpu

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

John A. Stratton, Vinod Grover, Jaydeep Marathe, Bastiaan Aarts, Mike Murphy, Ziang Hu, Wen-mei W. Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Programming techniques

February 20, 2011 by hgpu

XMalloc: A Scalable Lock-free Dynamic Memory Allocator for Many-core Machines

Xiaohuang Huang, Christopher I. Rodrigues, Stephen Jones, Ian Buck, Wen-mei Hwu

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Tags: Algorithms, Computer science, CUDA, Memory, Memory model, nVidia, Tesla C1060

February 20, 2011 by hgpu

Data Layout Transformation Exploiting Memory-Level Parallelism in Structured Grid Many-Core Applications

I-Jui Sung, John A. Stratton, Wen-Mei W. Hwu

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Tags: Compilers, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 280

February 20, 2011 by hgpu

Accelerating Particle Image Velocimetry Using Hybrid Architectures

Vivek Venugopal, Cameron D. Patterson, Kevin Shinpaugh

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Tags: Computer science, CUDA, FPGA, nVidia, Tesla C1060, Visualization

February 19, 2011 by hgpu

Programmability: Design Costs and Payoffs using AMD GPU Streaming Languages and Traditional Multi-Core Libraries

Rick Weber, Robert J. Harrison, Gregory D. Peterson

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Tags: ATI CAL, ATI Radeon HD 4870, ATI Stream, Brook, Computer science, Review

February 19, 2011 by hgpu

Compiler Support for High-level GPU Programming

Tianyi David Han and Tarek S. Abdelrahman

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, Package

February 19, 2011 by hgpu

High Performance Relevance Vector Machine on GPUs

Depeng Yang, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL

February 19, 2011 by hgpu

A Generic Approach for Developing Highly Scalable Particle-Mesh Codes for GPUs

W. Honig, F. Schmitt, R. Widera, H. Burau, G. Juckeland, M. S. Muller, and M. Bussmann

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Tags: ATI Radeon HD 5770, Computer science, CUDA, nVidia, OpenCL, Particle-in-cell methods, Plasma physics, Tesla C2050, Tesla S1070

February 19, 2011 by hgpu

GPU Accelerated Scalable Parallel Random Number Generators

Shuang Gao, Gregory D. Peterson

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 480, Pseudo-random number generators, Tesla S1060

February 19, 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

Applications

Fast Exact String Matching on the GPU

Program Optimization Study on a 128-Core GPU

MCUDA: An Efficient Implementation of CUDA Kernels on Multi-cores

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

XMalloc: A Scalable Lock-free Dynamic Memory Allocator for Many-core Machines

Data Layout Transformation Exploiting Memory-Level Parallelism in Structured Grid Many-Core Applications

Accelerating Particle Image Velocimetry Using Hybrid Architectures

Programmability: Design Costs and Payoffs using AMD GPU Streaming Languages and Traditional Multi-Core Libraries

Compiler Support for High-level GPU Programming

High Performance Relevance Vector Machine on GPUs

A Generic Approach for Developing Highly Scalable Particle-Mesh Codes for GPUs

GPU Accelerated Scalable Parallel Random Number Generators

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Over-synchronization in GPU Programs

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