New MOOC on Programming for High Performance

[Robert van de Geijn]

We are excited to announce that edX has opened registration for
"LAFF-On Programming for High Performance" [1].  This free-to-audit,
four-week, self-paced course developed by UT-Austin faculty Robert van
de Geijn, Maggie Myers, and Devangi Parikh starts on June 4, 2019.

The course uses the simple but important example of matrix-matrix
multiplication to illustrate fundamental techniques for attaining
high-performance on modern CPUs. A carefully designed sequence of
exercises leads the learner from a naive implementation to one that
effectively utilizes instruction level parallelism and culminates in a
high-performance, multithreaded implementation. Along the way, it is
discovered that careful attention to data movement is key to efficient
computing.  In other words, learners are exposed to techniques for
attaining high performance through carefully scaffolded exercises that
illustrate how the BLAS-like Library Instantiation Software (BLIS) [2]
implements dgemm, which is itself based on Goto's algorithm [3].

We believe this course is appropriate for a novice yet of interest to an
expert.  It may be, for example, a great way to get a summer intern
quite literally up to speed.  Others may want to use it as a component
in a class they teach.  Some learners may merely come to the
conclusion that they should be using high-performance libraries.
Others may find they enjoy low level optimization.

Please help us spread the word!

[1] https://www.edx.org/course/laff-on-programming-for-high-performance

[2] Field G. Van Zee, Robert A. van de Geijn. BLIS: A Framework for
Rapidly Instantiating BLAS Functionality.  ACM TOMS, 2015.

[3] Kazushige Goto, Robert A. van de Geijn. Anatomy of
high-performance matrix multiplication. ACM TOMS, 2008.