<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T21:12:38Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/90080" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/90080</identifier><datestamp>2021-07-05T14:03:20Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">John R. Williams.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Alhubail, Maitham Makki (Maitham Makki Hussain)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Computation for Design and Optimization Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Computation for Design and Optimization Program</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2014-09-19T21:38:32Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2014-09-19T21:38:32Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2014</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2014</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/90080</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">890141986</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2014.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (page 47).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This thesis presents a new simple lightweight C++ thread based parallelization library, intended for use in numerical algorithms. It provides simple multitasking and task synchronization functions. The library hides all internal system calls from the developer and utilizes thread pooling to provide better performance and utilization of system time and resources. The library is lightweight and platform independent, and has been tested on Linux, and Windows. Experiments were conducted to verify the proper functionality of the library and to show that parallelized algorithms on a single machine are more efficient than using the Message Passing Interface (MPI) using shared memory. In the opinion of several researchers who have used this library, the parallelized code is more easily understood and debugged than MPI. The results of initial experiments show that algorithms are as efficient or better than those using MPI.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Maitham Makki Alhubail.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">47 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Computation for Design and Optimization Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">A thread-based parallel programming library for numerical algorithms</dim:field>
   <dim:field mdschema="dc" element="type" lang="en_US">Thesis</dim:field>
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   	&lt;Title>A thread-based parallel programming library for numerical algorithms&lt;/Title>
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   	&lt;PublicationDate>2014&lt;/PublicationDate>
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        	&lt;DisplayName>Alhubail, Maitham Makki (Maitham Makki Hussain)&lt;/DisplayName>
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    &lt;Keyword>Computation for Design and Optimization Program.&lt;/Keyword>
   	&lt;Abstract>This thesis presents a new simple lightweight C++ thread based parallelization library, intended for use in numerical algorithms. It provides simple multitasking and task synchronization functions. The library hides all internal system calls from the developer and utilizes thread pooling to provide better performance and utilization of system time and resources. The library is lightweight and platform independent, and has been tested on Linux, and Windows. Experiments were conducted to verify the proper functionality of the library and to show that parallelized algorithms on a single machine are more efficient than using the Message Passing Interface (MPI) using shared memory. In the opinion of several researchers who have used this library, the parallelized code is more easily understood and debugged than MPI. The results of initial experiments show that algorithms are as efficient or better than those using MPI.&lt;/Abstract>
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