6 Şubat 2020 Dergi makalesi Açık Erişim

Cini, Nevin; Yalcin, Gülay

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    <subfield code="p">ACM Computing Surveys</subfield>
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    <subfield code="a">&lt;p&gt;Today, GPUs are widely used as coprocessors/accelerators in High-Performance Heterogeneous Computing&lt;br&gt;
due to their many advantages. However, many researches emphasize that GPUs are not as reliable as desired&lt;br&gt;
yet. Despite the fact that GPUs are more vulnerable to hardware errors than CPUs, the use of GPUs in HPCs&lt;br&gt;
is increasing more and more. Moreover, due to native reliability problems of GPUs, combining a great number&lt;br&gt;
of GPUs with CPUs can significantly increase HPCs&amp;rsquo; failure rates. For this reason, analyzing the reliability&lt;br&gt;
characteristics of GPU-based HPCs has become a very important issue. Therefore, in this study we evaluate&lt;br&gt;
the reliability of GPU-based HPCs. For this purpose, we first examined field data analysis studies for GPU-&lt;br&gt;
based and CPU-based HPCs and identified factors that could increase systems failure/error rates. We then&lt;br&gt;
compared GPU-based HPCs with CPU-based HPCs in terms of reliability with the help of these factors in&lt;br&gt;
order to point out reliability challenges of GPU-based HPCs. Our primary goal is to present a study that can&lt;br&gt;
guide the researchers in this field by indicating the current state of GPU-based heterogeneous HPCs and&lt;br&gt;
requirements for the future, in terms of reliability. Our second goal is to offer a methodology to compare the&lt;br&gt;
reliability of GPU-based HPCs and CPU-based HPCs. To the best of our knowledge, this is the first survey&lt;br&gt;
study to compare the reliability of GPU-based and CPU-based HPCs in a systematic manner.&lt;/p&gt;</subfield>
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    <subfield code="a">A Methodology for Comparing the Reliability of GPU-Based and CPU-Based HPCs</subfield>
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    <subfield code="c">2020-02-06</subfield>
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