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<p class="" style="font-family: GillSans;">Call for Papers: <a href="https://dapper18.github.io/" class="">https://dapper18.github.io</a><br class="">
International Workshop on Data Analytics and Parallel Performance (DAPPER '18)<br class="">
Held in conjunction with ISPASS 2018: IEEE International Symposium on Performance Analysis of Systems and Software<br class="">
April 2-4, 2018<br class="">
Belfast, Northern Ireland, UK</p>
<p class="" style="font-family: GillSans;"><font color="#ff2600" class="">Submission deadline: February 15, 2018 (AoE)</font><br class="">
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<div class="" style="font-family: GillSans;"></div>
<div class="">
<div class="">Optimizing high performance computing (HPC)/data centers, and applications</div>
<div class="">running at these centers presents a unique set of challenges, and an</div>
<div class="">opportunity to automate complex optimization tasks. The use of machine learning</div>
<div class="">and statistical techniques to model and characterize performance data is</div>
<div class="">gaining traction in the parallel community. The International Workshop on Data</div>
<div class="">Analytics and Parallel Performance provides a forum for sharing academic and</div>
<div class="">industrial research work focused on applying data analytics to performance</div>
<div class="">analysis, debugging and optimization/tuning of parallel software and systems.</div>
<div class=""><br class="">
</div>
<div class=""># Workshop Topics</div>
<div class=""><br class="">
</div>
<div class="">Authors are invited to submit novel research as well as ongoing work pertaining to:</div>
<div class=""><br class="">
</div>
<div class="">- Deep learning, neural networks</div>
<div class="">- Supervised/unsupervised machine learning</div>
<div class="">- Classification, regression, clustering</div>
<div class="">- Dimensionality reduction</div>
<div class="">- Data-driven modeling</div>
<div class=""><br class="">
</div>
<div class="">applied to</div>
<div class=""><br class="">
</div>
<div class="">- Performance analysis</div>
<div class="">- Debugging, performance debugging</div>
<div class="">- Performance optimization, auto-tuning</div>
<div class=""><br class="">
</div>
<div class="">of/for</div>
<div class=""><br class="">
</div>
<div class="">- Parallel benchmarks, proxy applications, and production codes</div>
<div class="">- Scientific workflows</div>
<div class="">- HPC workloads/Full system</div>
<div class="">- HPC/Data center facilities</div>
<div class=""><br class="">
</div>
<div class="">
<div class=""># Submissions</div>
<div class=""><br class="">
</div>
<div class="">We solicit 8-page full papers as well as 4-page short papers that focus on</div>
<div class="">techniques at the intersection of parallel performance and data analytics. The</div>
<div class="">
<div style="margin: 0px; line-height: normal; background-color: rgb(255, 255, 255);" class="">
<span style="font-variant-ligatures: no-common-ligatures;" class="">8-page full papers should describe original unpublished </span><span style="font-variant-ligatures: no-common-ligatures;" class="">work, while 4-page short </span></div>
<div style="margin: 0px; line-height: normal; background-color: rgb(255, 255, 255);" class="">
papers can be original unpublished work or ongoing work. </div>
</div>
<div class=""><br class="">
</div>
<div class="">Papers must be submitted in PDF format (readable by Adobe Acrobat Reader 5.0</div>
<div class="">and higher) and formatted for 8.5" x 11" (U.S. Letter). Submissions are limited</div>
<div class="">to 8 pages in the IEEE format: <a href="https://www.ieee.org/conferences_events/conferences/publishing/templates.html" class="">https://www.ieee.org/conferences_events/conferences/publishing/templates.html</a>,</div>
<div class="">using the conference option. The 8-page limit includes figures, tables, and</div>
<div class="">references.</div>
<div class=""><br class="">
</div>
<div class="">All papers must be submitted through Easychair at:</div>
<div class=""><a href="https://easychair.org/conferences/?conf=dapper18" class="">https://easychair.org/conferences/?conf=dapper18</a></div>
<div class=""><br class="">
</div>
<div class="">Accepted submissions will be invited to present a talk at the workshop, and a<span style="background-color: rgb(255, 255, 255); font-variant-ligatures: no-common-ligatures;" class=""> few </span></div>
<div class=""><span style="background-color: rgb(255, 255, 255); font-variant-ligatures: no-common-ligatures;" class="">selected accepted papers that describe unpublished work will be invited to </span></div>
<div class=""><span style="background-color: rgb(255, 255, 255); font-variant-ligatures: no-common-ligatures;" class="">submit to a special issue of The International Journal of High Performance </span></div>
<div class=""><span style="background-color: rgb(255, 255, 255); font-variant-ligatures: no-common-ligatures;" class="">Computing Applications.</span></div>
<div class=""><br class="">
</div>
<div class="">
<div class=""># Important Dates</div>
<div class=""><br class="">
</div>
<div class="">- Submission deadline: February 15, 2018 (AoE)</div>
<div class="">- Notification of acceptance: March 5, 2018 (AoE)</div>
<div class=""><br class="">
</div>
<div class="">
<div class="">## Workshop Chairs</div>
<div class=""><br class="">
</div>
<div class="">Abhinav Bhatele, Lawrence Livermore National Laboratory</div>
<div class="">Marc Casas, Barcelona Supercomputing Center</div>
<div class="">Nikhil Jain, Lawrence Livermore National Laboratory</div>
<div class=""><br class="">
</div>
</div>
</div>
</div>
</div>
<div class="">
<div class=""></div>
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<div class="">
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---</div>
<div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">
Nikhil Jain<br class="">
Postdoctoral Fellow, Lawrence Livermore National Laboratory<br class="">
<a href="mailto:nikhil.jain@acm.org" class="">nikhil.jain@acm.org</a>, <a href="http://nikhil-jain.github.io/" class="">
http://nikhil-jain.github.io/</a></div>
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