CSC 591/791 Course Syllabus

CSC 591/791 – High Performance Machine Learning and Real-Time AI

Fall 2024

3 Credit Hours

Course Description

Description: As machine learning (ML) and Artificial Intelligence (AI) gets rapidly adopted everywhere, the speed in learning and inference has become one of the most frequently encountered roadblocks for practical adoptions. This course focuses on the challenges and solutions for achieving high performance and real-time response of ML and AI while keeping the accuracy satisfactory. The course will cover the common platforms and toolkits for modern Machine Learning and AI, the factors and tradeoffs affecting the performance, various optimization techniques for ML and AI, and the trends and research directions being actively investigated in this field.

Learning Outcomes

By the end of the course, students should be able to do the following.

Course Structure

The course will consist of a series of lectures, student presentations, and in-class discussions.

Instructors

Xipeng Shen (xshen5) - Instructor
Email: xshen5@ncsu.edu
Phone: 919-513-7577
Office Location: EBII 3276
Office Hours: 1:00-2:00pm Friday.

Course Meetings

Lecture

Days: MWF
Time: 8:30am - 11:15am
Campus: Centennial
Location: EBII 01228
This meeting is required.

Course Materials

Textbooks


None. The class will be based on slides, notes, and research papers.

Expenses

None.

Materials

None.

Requisites and Restrictions

Prerequisites

Introduction-level knowledge of ML, data structures (CSC316 or equivalent), Python. Helpful: C/C++, CUDA, GPU.

Co-requisites

None.

Restrictions

None.

General Education Program (GEP) Information

GEP Category

This course does not fulfill a General Education Program category.

GEP Co-requisites

This course does not fulfill a General Education Program co-requisite.

Transportation

This course will not require students to provide their own transportation. Non-scheduled class time for field trips or out-of-class activities is NOT required for this class.

Safety & Risk Assumptions

None.

Grading

Grade Components

ComponentWeightDetails
Course Project 30%

The course project will be a group programming project with group size >= 1 and <=3.

Assignments 50%

There will be several written/programming assignments.

Quizes & Presentations 20%

There will be a number of in-class quizes throughout the semester. For CSC791 students, each will additionally give a paper presentation (which weights 5% in the total grades and quizes weight 15% instead of 20%).

Letter Grades

This Course uses the Following (Non-Standard) Letter Grading Scale:
97%A+100%
93%A<97%
87%A-<93%
85%B+<87%
80%B<85%
75%B-<80%
70%C+<75%
65%C<70%
60%C-<65%
56%D+<60%
50%D<56%
45%D-<50%
0%F<45%

Requirements for Credit-Only (S/U) Grading

Performance in research, seminar and independent study types of courses (6xx and 8xx) is evaluated as either "S" (Satisfactory) or "U" (Unsatisfactory), and these grades are not used in computing the grade point average. For credit only courses (S/U) the requirements necessary to obtain the grade of "S" must be clearly outlined.

Requirements for Auditors (AU)

Information about and requirements for auditing a course can be found at http://policies.ncsu.edu/regulation/reg-02-20-04.

Policies on Incomplete Grades

If an extended deadline is not authorized by the Graduate School, an unfinished incomplete grade will automatically change to an F after either (a) the end of the next regular semester in which the student is enrolled (not including summer sessions), or (b) by the end of 12 months if the student is not enrolled, whichever is shorter. Incompletes that change to F will count as an attempted course on transcripts. The burden of fulfilling an incomplete grade is the responsibility of the student. The university policy on incomplete grades is located at http://policies.ncsu.edu/regulation/reg-02-50-03. Additional information relative to incomplete grades for graduate students can be found in the Graduate Administrative Handbook in Section 3.18.F at http://www.fis.ncsu.edu/grad_publicns/handbook/

Late Assignments

No late assignments will be accepted. If an emergency (e.g., hospitalization) prevented an assignment from being submitted, its grade will be determined by averaging the completed assignments in the same category. Instructor may grant an extension if a student has some extenuating circumstances warranting it (which is very rare). Student must receive this extension by noon the day it is due. Note: requesting an extension is not the same as receiving it.

Attendance Policy

For complete attendance and excused absence policies, please see http://policies.ncsu.edu/regulation/reg-02-20-03

Attendance Policy

While attendance is not officially recorded, students are expected to attend classes. Class periods will include material not covered in the reading assignments, and students are responsible for knowing this information. While efforts are made to provide critical information through electronic resources (web page, mailing list, etc.), some information may not be available outside of class in a timely manner or at all. Although this may be unintentional, students are still responsible for all information presented in class. There will be several in-class quizzes; make-up quizzes will only be offered if the student has a legitimate reason for the absence, supported by convincing proof.


Absences Policy

A legitimate absence requires proof provided to the instructor ahead of time. No make-up quizzes will be given for absences that are not justified with legitimate proof.

Makeup Work Policy

Makeup quizzes or assignments are allowed only in special cases where the student provides legitimate proof to justify the circumstances that prevented them from completing the quizzes or assignments. No makeup is allowed for the course project.

Additional Excuses Policy

None.

Academic Integrity

Academic Integrity

Students are required to comply with the university policy on academic integrity found in the Code of Student Conduct found at http://policies.ncsu.edu/policy/pol-11-35-01

 

Students are expected to maintain high standards of academic integrity and honesty. University guidelines regarding academic integrity will be followed. Cheating will result in disciplinary actions, up to the full penalties specified in the guideline. A grade of zero will be given to the assignment in question for a minor offense. A major offense, including any violation on a test, could result in failure of the course. All suspected violations will be reported to the Office of Student Conduct, where a guilty outcome on a second offense can mean suspension from the university.

 

Please keep in mind that academic integrity in the classroom translates to professional integrity in the workplace. Moreover, awarding similar grades to students who have maintained academic integrity and to students who have cheated results in conferring equivalent degrees on them, and reduces the value of that degree in the workplace. It is the responsibility of every student as well as the instructor and TA to see that this is not allowed to happen.

 

Academic Honesty

See http://policies.ncsu.edu/policy/pol-11-35-01 for a detailed explanation of academic honesty.

None.

Honor Pledge

Your signature on any test or assignment indicates "I have neither given nor received unauthorized aid on this test or assignment."

Electronically-Hosted Course Components

Students may be required to disclose personally identifiable information to other students in the course, via electronic tools like email or web-postings, where relevant to the course. Examples include online discussions of class topics, and posting of student coursework. All students are expected to respect the privacy of each other by not sharing or using such information outside the course.

Electronically-hosted Components: online discussions of class topics

Accommodations for Disabilities

Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, student must register with the Disability Services Office (http://www.ncsu.edu/dso), 919-515-7653. For more information on NC State's policy on working with students with disabilities, please see the Academic Accommodations for Students with Disabilities Regulation at http://policies.ncsu.edu/regulation/reg-02-20-01.

Non-Discrimination Policy

NC State University provides equality of opportunity in education and employment for all students and employees. Accordingly, NC State affirms its commitment to maintain a work environment for all employees and an academic environment for all students that is free from all forms of discrimination. Discrimination based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation is a violation of state and federal law and/or NC State University policy and will not be tolerated. Harassment of any person (either in the form of quid pro quo or creation of a hostile environment) based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation also is a violation of state and federal law and/or NC State University policy and will not be tolerated. Retaliation against any person who complains about discrimination is also prohibited. NC State's policies and regulations covering discrimination, harassment, and retaliation may be accessed at http://policies.ncsu.edu/policy/pol-04-25-05 or http://www.ncsu.edu/equal_op/. Any person who feels that he or she has been the subject of prohibited discrimination, harassment, or retaliation should contact the Office for Equal Opportunity (OEO) at 919-515-3148.

Course Schedule

NOTE: The course schedule is subject to change.

Introduction

  • Traditional ML/AI techniques
  • Deep learning techniques
  • Common platforms and toolkits
  • Performance considerations

  • Metrics, factors
  • Optimizations

  • ML model optimizations
  • ML compilation and optimizations
  • Advanced topics

  • Compression-compilation co-design
  • Advanced optimizations
  • Other research topics