CS 598 CM

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

Machine Learning for Compilers and Architecture This course will explore how modern machine learning techniques are used in compilers and in computer architecture for systems decision making. We will first go through the basics of modern deep learning techniques including primers on different neural network architectures and the basics of sequential decision making. Then, we will cover how these techniques are used in the context of systems decision making including compiler optimizations, auto-tuning, performance modelling, performance aware neural architecture search, hardware systems design etc. We will go through recent papers on each topic to understand and to critically evaluate the latest developments in this space. This course will help prepare students for independent research in the covered topic areas. Prerequisites: Following are preferred courses. CS421 or CS426, CS 433 For up-to-date information about CS course restrictions, please see the following link: http://go.c