High Performance Computing
|Title||High Performance Computing (51087)|
|Instructor||Ronald Rahaman (email@example.com)|
Parallel programming is ubiquitous in both the largest, power-intensive data centers and the smallest, low-power embedded devices. Though this has been the status quo for many years, achieving optimal parallel performance can still be a challenging, multi-disciplinary effort.
In this course, we will implement and optimize C applications on large-scale, multicore CPU and GPU compute clusters. We will cover details about widely-used parallel programming APIs (OpenMP, CUDA, and MPI). Computer architecture will be a pervasive theme, and we will discuss how the C language and parallel APIs map to the underlying hardware.
We will be programming exclusively in C, and no other knowledge is assumed. Previous MPCS courses in computer architecture, compilers, or algorithms can be very helpful but are absolutely not required.
Throughout the course, will draw on examples from linear algebra, Monte Carlo simulations, discretized partial differential equations, and machine learning.
This class is primarily project-based. We will have 4-5 bi-weekly homework assignments and 2 brief concept-based exams.
We will draw on material from the following texts. None are required, but they can be helpful resources throughout your career.
MPCS 51040 - C Programming or MPCS 51100 Advanced Programming or instructor consent.