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  <title><![CDATA[PhD Proposal by Ching-Kai Liang]]></title>
  <body><![CDATA[<p>Title: Model, Predict, and Mitigate Scalability Bottlenecks for Parallel Application on Many-core Processors</p>

<p><br />
Ching-Kai Liang<br />
Ph.D. Student<br />
School of Computer Science<br />
College of Computing<br />
Georgia Institute of Technology<br />
<br />
Date: Monday, November 27 2017<br />
Time: 10:00AM - 12:00PM (EDT)<br />
Location: Klaus 2100<br />
<br />
Committee:<br />
Dr. Milos Prvulovic (Advisor, School of Computer Science, Georgia Institute of Technology)<br />
Dr. Hyesoon Kim (School of Computer Science, Georgia Institute of Technology)<br />
Dr. Moinuddin Qureshi&nbsp;(School of Computer Science, Georgia Institute of Technology)<br />
Dr. Sudhakar Yalamanchili (School of Electrical and Computer Engineering, Georgia Institute of Technology)<br />
Dr. Christopher Hughes (Intel Labs, Intel)</p>

<p>&nbsp;</p>

<p><br />
Abstract:</p>

<p>In recent years, the number of processor cores on a single chip has increased rapidly, ranging from hundreds of cores in server processors to tens of cores on mobile processors.&nbsp;</p>

<p>The abundant number processing cores have led to application developers investing in parallizing applications in order to extract the maximum performance from many-core processors.&nbsp;</p>

<p>However, ensuring the continuous scaling of parallel applications is challenging on many-core processors, due to the complex relationship of available parallelism in application and the limited shared on-chip resources.</p>

<p><br />
&nbsp;</p>

<p>In this thesis, I will propose microarchitecture solutions to mitigate the scaling bottleneck as well as a new performance model to&nbsp;predict the how applications will scale on many-core processors.</p>

<p>First, I will propose MiSAR, a minimalistic synchronization accelerator that supports all three commonly used types of synchronization (locks, barriers, and condition variables),&nbsp;</p>

<p>and a novel overflow management unit that dynamically manages its (very) limited hardware synchronization resources.</p>

<p>Second, I will propose a new performance model that captures program characteristics of multi-threaded applications, allowing it to use few-threaded runs to predict performance of many-threaded runs.</p>

<p>&nbsp;</p>
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