• Monday, C9001, Burnaby Monday lectures. In person and live.
• Wednesdays, C9001, Burnaby Quiz on Canvas + Class discussion. Quiz first-attempt will have to be on SFU campus.
• Video Aids : Slide-by-Slide video will be available on youTube prior to the lecture for flipped (pre) or post class viewing. See the schedule accompanying the weekly notes for links. You can choose to watch videos either before or after class to revise the material. They have been provided for you to watch and refresh yourself if you are not comfortable with any of the slide material.
• Monday F2F Lectures: On Mondays at class during lecture hours I will be going over slide desks and or problem sets and demonstrations (these will be marked with F2F tag on the syllabus) of the slides. F2F sessions will be spent on reinforcing concepts and problem sets (not slide-by-slide commentary). The class videos will be recorded and be made available within 72hrs after the class.
• Q&A in Piazza. See above on how to join. Students can interact with the TA and post questions on piazza.
• Homeworks/Assignments Submissions - Github. Refer lab0 for steps.
• Quiz Wednesdays. Wednesdays will be entirely dedicated for Q/A and Public OH in class (if you booked private OH then TASC 9009), Burnaby. This includes weekly quizes and labs
• Canvas Weekly Quizzes - These quizzes exist for you to obtain immediate feedback and me to tailor the learning. You can retake the quiz up to 5 times. The quizzes will be conducted on Wednesdays
• Labs/Tutorials Labs. Attend the labs and practice tutorials will be held by TAs. These are there to help you complete the assignments and attendance will be graded.

1. 📖 Read the Course Policies

• Course Policies
• Understand grading, communication rules, and course expectations.

2. 💬 Register on Piazza

• Join Piazza (link on course website).
• This is our main channel for Q\&A and announcements.
• We do not answer private emails—use Piazza instead.

3. 🖥️ Set Up Your Programming Environment

Choose one of the following:

• VM Setup
• CSIL Access (with SSH/RDP + VPN)
• VSCode + CSIL

🔒 Required: Set up MFA for CSIL.

⚠️ Without this setup you cannot do labs or assignments.

4. 🧪 Complete Lab 0 (Before First Lab)

• Lab 0 Instructions
• This lab ensures your environment works.
• Deadline: Must be done before any other lab or assignment is graded.

5. 🧑‍💻 Preview Lab 1

• Lab 1 Materials
• Watch the video and read instructions.
• Can be completed during your first in-person lab session.

6. 🎥 Prepare for Week 1 Classes

• Download: Week 1 Slides
• Watch: Week 1 Videos
• In class we’ll build on this material, not repeat every slide.

7. 📝 Late Enrollments Only

• Fill out the Late Enrollment Form by Jan 13.
• Complete Lab 0 and Lab 1 independently.

8. 📊 Grading Reminder

• Grading Criteria

• You must achieve at least:

  • 30% on Exam 1
  • 40% on Exam 2
  • 50% on the Final to pass the course.

9. 🎁 Attendance Incentive Program

• Each lecture you attend = 1-day extension credit for assignments.
• Example: Attend 7 lectures → 7 extension days you can use later.
• Normally, no late submissions are allowed—this program is your only flexibility.

✅ Tip for success: Students who complete this checklist before Week 1, and regularly attend lectures and labs, consistently achieve higher grades.

Finalized grades will always be on Coursys

• Six programming assignments. (30%)
• Labs and Participation.
• 10 Weekly Quizzes (5%). 0.5% for each quiz. Full points are awarded if you score atleast 80%.
• Exam 1 Week 1-2 (15%). Exam 2 Week 3-5 (15%)

• Exam 3 (35%) Week 7,8,9,10,11. Week 9 (only Ass5 and material in class). Week 10 (gates, flipflops, truth-tables will not be tested).

• PASS/FAIL Criteria You must achieve at least 30% on Exam 1, 40% on Exam 2, and 50% on the Final to pass.
• Students not meeting these criteria receive at most a D grade (pass, but cannot be used as prerequisite).
• This ensures everyone can independently demonstrate course knowledge to earn a C- or better.

This is the typical mapping from % to letter grade at the end: A+ 97 A 92 A- 87 B+ 82 B 77 B- 72 C+ 67 C 62 C- 55 D 50 F

In the event that distribution does not align with the CMPT departmental guidelines, we may decrease the raw score boundaries, but they will not increase i.e. it is possible to receive a higher grade than the mapping suggests, but not a lower one. this will not apply to WD students or Incompletes.

Computer-based Testing

In 295, we extensively use computer-based testing for all quizes, midterms, final, and programming assignments. State-of-the-art computer-based testing has been developed to eliminate TA-opinion based scoring ensure fairness, and accurately measure student ability to program. The scores essentially reflect at this specific moment in your educational trajectory, the programming knowledge required for 300 and 400-level courses, and minimum programming expertise required for a job. Programming is an unusual form of computer interaction that demands precise output and testing; there is no such things as “somewhat correct” in programming. Hence, we award scores based on demonstrable tests passed and failed. TAs simply verify and upload the grades; they are not evaluating the tests and cannot influence your actual scores. Please email them only in the event that there is an error in our grading scheme. We understand that tests and scores do not inherently measure your intrinsic worth as a student or human. Remember, the letter grades are not passing judgement on you as a person.

Participation grades

Participation grades are awarded at the end of the course. I want to encourage participation in my classes. I believe that learning goes both ways, and that it’s important for you to participate to get the full learning experience. Therefore, I encourage participation by making part of your grade dependent on it.

Extra credit: 0.5% class wide for active classes of your total grade comes from actively participating in class (defined broadly) and attending labs. In general, if the overall classroom environment is active everyone will be awarded this grade. So ask questions for both your sake and your neighbor’s sake. I will be judging this after each class.

• First, half the battle in learning is asking questions. So I would like to reward you.
• Second, questions help class wide learning experience and promotes a healthy classroom environment.

5% Wednesday quizes. Quizzes will always be held on Wednesdays. You are allowed to retake a quiz if you fail. We will only consider your best submission.

Understanding Software in Action

In this course, we’ll embark on an exciting exploration of what really happens when software runs. This journey takes us through multiple levels of abstraction, from hardware architecture to assembly language, and down to the intricate workings of C programming. At the core of our study is a trio of fundamental elements: C programming, assembly language, and low-level data representation. But our exploration doesn’t stop there; we’ll connect these core elements to higher-level concepts, diving into how programming languages are translated into assembly, understanding the general structure of a processor, and comprehending the processor’s role and implementation.

This course is designed to introduce you to the fascinating world of computer organization, systems programming, and the hardware/software interface. Our topics are comprehensive and include instruction sets, computer arithmetic, datapath design, data formats, addressing modes, memory hierarchies (covering both caches and virtual memory), and multicore architectures. You’ll gain hands-on experience with assembly language programming and even design a pipelined RISC V processor! This course is perfectly suited for any undergraduate who has successfully completed the 120s material.

RISC V

In this iteration of the course, we’ll delve into the core components of computer architecture through the lens of the RISC-V (Roman numeral V for Five) Instruction Set Architecture (ISA). RISC-V is a modern, open-source ISA, offering a unique opportunity for you to learn both assembly-level programming and the digital design of a processor. We’ve chosen RISC-V because it’s a standard ISA taught worldwide at prestigious universities like Berkeley, Cornell, MIT, Princeton, Stanford, and more. This choice allows us to explore the end-to-end design and toolflow of a commercially viable processor within a single term, rather than being limited to a small fraction of a more complex ISA, like x86.

A Hands-On, Programming-Intensive 4 credit Experience

Prepare for a hands-on, programming-intensive experience. This course will immerse you in the practical aspects of C, assembly, and computer architecture. We’ll engage in detailed discussions about the fundamental design and engineering trade-offs in computer organization at every level, ensuring a rich and comprehensive learning experience.

CMPT 295 is a great way to gain a deep understanding of how computers work, build a strong foundation in computer science, and pursue a career in technology. Here are some reasons:

• Understand how computers work: CMPT 295 is the study of how computer systems are designed and how they operate. You will gain a deep understanding of how computers work, from the low-level hardware components to the high-level software applications.

• Build a strong foundation in computer science Computer organization is a fundamental topic in computer science, and it provides a strong foundation for many other areas of the field.

• Pursue a career in technology: By mastering computer organization, you can develop a strong foundation that will help you succeed in other areas of computer science, such as software engineering, database management, and artificial intelligence.

• Optimize computer performance: By understanding how hardware and software interact, you can identify areas where performance can be improved and make changes to improve overall system performance.

• Drive innovation: As researchers continue to push the boundaries of what AI can do, they require more powerful systems to enable them to explore more complex models and algorithms. For example, specialized AI chips such as Google’s Tensor Processing Units (TPUs) and NVIDIA’s Tesla GPUs have driven significant improvements in AI performance.