Here are some suggestions for this year's Google Summer of Code. This list is not definitive and students may propose their own projects by creating a new topic on the <a href="https://groups.google.com/forum/#!forum/arrayfire-users">ArrayFire-User Google Group</a> with "[GSOC]" in the subject line.

<b>New features</b>
<ul>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement a new feature in ArrayFire for multiple backends. This will require cooperation with different developers to optimize performance over the different architectures ArrayFire targets.</span></li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement new computer vision functions/features, such as:</span>
<ul>
 	<li style="font-weight: 400;">SURF</li>
 	<li style="font-weight: 400;">AKAZE</li>
</ul>
</li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement CPU backend parallelization using OpenCL or OpenMP</span></li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement Eigensolvers</span></li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement linear solvers</span></li>
 	<li style="font-weight: 400;">Implement PDE solvers</li>
 	<li style="font-weight: 400;">Implement non-uniform FFT</li>
 	<li style="font-weight: 400;">Write new examples for ArrayFire</li>
</ul>
<b>Wrappers</b>
<ul>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement .NET wrapper</span></li>
 	<li style="font-weight: 400;">Improve R wrapper</li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Implement Java wrapper (targeting Android platform)</span></li>
</ul>
<b>Architecture and build systems</b>
<ul>
 	<li>Modularize ArrayFire</li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Document internal ArrayFire API</span></li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Improve testing</span></li>
</ul>
<b>Display and user interaction:</b>
<ul>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Helper functions for loading video and processing video frames - imgload(), show()</span></li>
 	<li style="font-weight: 400;"><span style="font-weight: 400;">Integrate other plotting library backends - matplotlib, gnuplot, etc</span></li>
</ul>
<b>Machine Learning</b>
<ul>
 	<li style="font-weight: 400;">Implement machine learning functions such as PCA</li>
</ul>