Dissertation/Thesis Abstract

.NET High Performance Computing
by Ou, Hsuan-Hsiu, M.S., Arkansas State University, 2012, 128; 1516485
Abstract (Summary)

Graphics Processing Units (GPUs) have been extensively applied in the High Performance Computing (HPC) community. HPC applications require additional special programming environments to improve the utilization of GPUs, for example, NVIDIA's CUDA and Khronos group's OpenCL. This thesis will introduce a preprocessor framework called HPC.NET, which is deployed on the Microsoft .NET platform to meet demands of GPU programmers while utilizing familiar languages. Multiple .NET languages are supported as well as detected loops and .NET TPL methods are converted into NVIDIA CUDA code automatically using common language processing techniques.

Moreover, HPC.NET is able to scale to utilize multiple GPUs in multiple machines based on Windows HPC Server 2008 R2. This framework takes care of all task scheduling and communication in order to achieve better programmability and high performance in .NET platform.

Indexing (document details)
Advisor: Jiang, Hai
Commitee: Huang, Xiuzhen, Jenness, Jeff
School: Arkansas State University
Department: Computer Science
School Location: United States -- Arkansas
Source: MAI 51/02M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Computer science
Keywords: Automatic translation, Compiler optimization, Graphics processing units, Heterogeneous cluster
Publication Number: 1516485
ISBN: 9781267545510
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