This school is normally done in-person over 3.5 days. We have converted it to an online format that will take place twice a week for two hours each over the course of six weeks, as follows:
The school seeks to educate participants in some tools and techniques used in high-performance computing and scientific computation. Topics will include general parallel computing, Dask, Machine Learning by example, OpenMP, GPGPU, and Message Passing Interface (MPI).
Each two-hour session will include a lecture and learning exercises. Participants will be provided take-home exercises to prepare for the next session. These will be oriented to those learners seeking a more advanced experience. There will be online office hours between each session so participants can ask questions about the content or the exercises.
The course is aimed at researchers and innovators, both academic and industrial. The background expected is typically that of a graduate student, although both advanced undergraduates and those who have finished (or never been to) graduate school may expect to benefit. Participants must have familiarity with the Unix command line, such as one might have upon completion of the ACENET Basics Series, and have some level of programming experience.
Participants must have a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.)