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<!DOCTYPE html>
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<h1 data-x="['left','left','left','center']" data-hoffset="['50','50','50','0']" data-y="['top','top','top','middle']" data-voffset="['239','148','175','-40']" data-transform_in="opacity:0;s:660;e:Power4.easeInOut;" data-transform_out="opacity:0;s:300;" data-start="300" data-splitin="chars" data-splitout="none" data-responsive_offset="on" data-startslide="0" data-endslide="0" data-elementdelay="0.05" data-end="9000" style="z-index: 5;" class="slider-bg tp-caption ol-title tp-resizeme tp-static-layer">GCLab</h1>
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The Global Computing Lab (GCLab), headed by Dr. Michela
Taufer, focuses on various aspects of high performance
computing (HPC) and its application to the sciences. We are
engaged in the design and testing of efficient computational
algorithms and adaptive scheduling policies for scientific
computing on GPUs, cloud computing, and volunteer
computing. Interdisciplinary research with scientists and
engineers in fields such as chemistry and chemical
engineering, pharmaceutical sciences, seismology, and
mathematics is at the core of our activities and philosophy.
</p>-->
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<!--<h1 data-x="['left','left','left','center']" data-hoffset="['50','50','50','0']" data-y="['top','top','top','middle']" data-voffset="['239','148','175','-40']" data-transform_in="opacity:0;s:660;e:Power4.easeInOut;" data-transform_out="opacity:0;s:300;" data-start="300" data-splitin="chars" data-splitout="none" data-responsive_offset="on" data-startslide="1" data-endslide="1" data-elementdelay="0.05" data-end="9000" style="z-index: 5;" class="tp-caption ol-title tp-resizeme tp-static-layer">PRIONN</h1>
<h2 data-x="['left','left','left','center']" data-hoffset="['50','50','50','0']" data-y="['top','top','top','middle']" data-voffset="['291','198','230','0']" data-transform_in="opacity:0;s:520;e:Power4.easeInOut;" data-transform_out="opacity:0;s:210;" data-start="600" data-splitin="chars" data-splitout="none" data-responsive_offset="on" data-startslide="1" data-endslide="1" data-elementdelay="0.025" style="z-index: 6;" class="tp-caption ol-subtitle tp-resizeme tp-static-layer">Predicting Runtime and IO using Neural Networks</h2>
<p data-x="['left','left','left','center']" data-hoffset="['50','50','50','-458']" data-y="['top','top','top','top']" data-voffset="['371','275','300','157']" data-width="['473','473','666','437']" data-visibility="['on','on','on','off']" data-transform_in="opacity:0;s:720;e:Power2.easeInOut;" data-transform_out="opacity:0;s:180;;" data-start="1500" data-startslide="1" data-endslide="1" class="tp-caption ol-description tp-resizeme tp-static-layer">
PRIONN automates prediction of per-job runtime and
IO resource usage, enabling IO-aware scheduling on HPC
systems. The novelty of our tool is the input of whole job
scripts into deep learning models that allow complete
automation of runtime and IO resource predictions. We
demonstrate the power of PRIONN with runtime and IO resource
predictions applied to IO-aware scheduling for real HPC data.
</p>
<a href="#" data-x="['left','left','left','center']" data-hoffset="['50','50','50','0']" data-y="['top','top','top','middle']" data-voffset="['532','426','450','110']" data-transform_in="opacity:0;s:720;e:Power2.easeOut;" data-transform_out="opacity:0;s:2;s:2;" data-start="1700" data-startslide="1" data-endslide="1" style="z-index: 8;" class="tp-caption btn btn-medium btn-wide btn-trans btn-skin-white btn-circle ol-btn tp-static-layer">Read the Paper</a>-->
<!-- Project #2 -->
<!--
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<p data-x="['left','left','left','center']" data-hoffset="['50','50','50','-458']" data-y="['top','top','top','top']" data-voffset="['371','275','300','157']" data-width="['473','473','666','437']" data-visibility="['on','on','on','off']" data-transform_in="opacity:0;s:720;e:Power2.easeInOut;" data-transform_out="opacity:0;s:180;;" data-start="1500" data-startslide="2" data-endslide="2" class="tp-caption ol-description tp-resizeme tp-static-layer">
Paper Abstract
</p>
<a href="#" data-x="['left','left','left','center']" data-hoffset="['50','50','50','0']" data-y="['top','top','top','middle']" data-voffset="['532','426','410','110']" data-transform_in="opacity:0;s:720;e:Power2.easeOut;" data-transform_out="opacity:0;s:2;s:2;" data-start="1700" data-startslide="2" data-endslide="2" style="z-index: 8;" class="tp-caption btn btn-medium btn-wide btn-trans btn-skin-white btn-circle ol-btn tp-static-layer">Read the Paper</a>
-->
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<!--<h4 class="head">GCLab</h4>-->
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<h1 class="title">Global Computing Laboratory</h1>
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<h2 class="subtitle">The Global Computing Lab (GCLab), headed by Dr. Michela
Taufer, focuses on various aspects of high performance
computing (HPC) and its application to the sciences. We are
engaged in the design and testing of efficient computational
algorithms and adaptive scheduling policies for scientific
computing on GPUs, cloud computing, and volunteer
computing. Interdisciplinary research with scientists and
engineers in fields such as chemistry and chemical
engineering, pharmaceutical sciences, seismology, and
mathematics is at the core of our activities and philosophy.</h2>
<div class="sp-blank-10"></div>
</div>
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<h3 class="title">
<font face="Courier New" size="6" color="white"><a href="./newsletters/gclab-newsletter2025.pdf">
Read our 2024-2025 newsletter and learn more about GCLab!</a></font>
</h3>
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<h2 class="title">GCLab and EECS hosted IBM PowerAI Workshop </h2>
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