Summit supercomputer simulations identifying approaches for SARS-CoV-2 coronavirus drug design
The greenest supercomputers in the world
We will survey the fundamentals of measuring, analyzing, and modeling computer performance. As we learn the material we will move through a set of case studies, allowing us to apply the techniques to increasingly complex problems. Case studies in Spring 2020 will include: multithreaded code; message passing (MPI code); containers and virtualized servers; and others. These case studies include hands on programming exercises that can be done on the CS Linux Lab machines. We will use a variety of performance tools through the course to learn the state of the art for performance techniques and practices. We will also learn data analysis methods for handling large data sets. We will read several research papers.
Ph.D. students are welcome, please email the instructor before the first class to discuss your additional requirements.
Prerequisites:
CS 201, CS 333, and CS 350 or equivalent. These are: Systems Programming, Introduction to Operating Systems, Introduction to Algorithms. Ability to program in C or C++ in a Linux environment.
Required textbook:
There is NO required textbook for this course. You will be using handouts provided by the instructor.
Note on prerequisites:
There is NO required textbook for this course. You will be using handouts provided by the instructor.
Additional required readings will be from freely available papers and articles.