.. title: PAR Class 14, Wed 2018-05-02
.. slug: class14
.. date: 2018-04-26
.. tags: class
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Course recap
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#. My teaching style is to work from particulars to the general.

#. You've seen **OpenMP**, a tool for shared memory parallelism.

#. You've seen the architecture of NVidia's GPU, a widely used parallel system, and **CUDA**, a tool for programming it.

#. You've seen **Thrust**, a tool on top of CUDA, built in the C++ STL style.

#. You've seen how widely used numerical tools like **BLAS** and **FFT** have versions built on CUDA.

#. You've had a chance to program in all of them on **parallel.ecse**,  with dual 14-core Xeons, **Pascal** NVidia board, and **Xeon Phi** coprocessor.

#. You seen talks by leaders in high performance computing, such as Jack Dongarra.

#. You've seen quick references to parallel programming using  Matlab, Mathematica, and the cloud.

#. Now, you can inductively reason towards general design rules for shared and non-shared parallel computers, and for the SW tools to exploit them.