Add Chapel talk

Author: diehlpk

index.html

@@ -53,6 +53,11 @@ <h2>Overview</h2>
       <td><a href="#fy262">Shedding Light on Interaction Binaries: Radiation Hydrodynamics with Octo-Tiger</a></td>
       <td>06/25/2025</td>
   </tr>
+  <tr>
+      <td>Engin Kayraklioglu</td>
+      <td><a href="#fy264">Chapel's Batteries-Included Approach for Portable Parallel Programming</a></td>
+      <td>06/18/2025</td>
+  </tr>
   <tr>
       <td>Jiakun Yan</td>
       <td><a href="#fy258">LCI: a Lightweight Communication Interface for Asynchronous Multithreaded Communication</a></td>
@@ -132,6 +137,21 @@ <h2>Overview</h2>
 
 <h2>Talks</h2>
 
+<div id="fy264"></div>
+<h3>Chapel's Batteries-Included Approach for Portable Parallel Programming</h3>
+Speaker: Engin Kayraklioglu<br>
+Hewlett Packard Enterprise (HPE)<br><br>
+
+Abstract:
+<p>
+Virtually all modern processors, including GPUs, from the consumer-grade to the highest-end are parallel. However, none of the mainstream programming languages support different flavors of hardware parallelism as a first-class concept. Capability to exploit parallelism in the hardware is typically achieved by augmenting inherently sequential programming languages like C, C++, or Fortran with add-ons like OpenMP, MPI, CUDA, OpenCL, or Kokkos.<br><br>
+Chapel stands out as a programming language designed with parallelism and locality as first-class concepts in the programming language itself. That, and other modern programming features, have enabled Chapel users to overcome the barriers to parallel programming and HPC. In this talk, I will go over how parallelism and locality are expressed in Chapel, and how they can be used to target GPUs in a vendor-neutral manner. I will also refer to several success stories from the Chapel community.
+</p>
+
+Bio:
+<p>
+Engin Kayraklioglu is a Principal Engineer at Hewlett Packard Enterprise (HPE), where he is a member of the Chapel team. His duties include leading GPU support effort, as well as the Arkouda project (<a href="https://arkouda-www.github.io/">https://ark    ouda-www.github.io/</a>). Before joining HPE (formerly Cray Inc.), Engin received his Ph.D. from The George Washington University in 2019. His interests are high-performance computing, programmer productivity and performance optimizations.
+</p>
 
 <div id="fy263"></div>
 <h3>Accelerated Quantum Supercomputing with CUDA-Q</h3>