Course Information

Cross Listed ENGRD 2300 Digital Logic and Computer Organization
Instructor Prof. Christopher Batten, 323 Rhodes Hall
Office Hours: Friday, 4:30–5:30pm, 323 Rhodes Hall
Head TAs Derin Ozturk, Aidan McNay
Graduate TAs Mahathi Andavolu, Vesal Bakhtazad, Ali Taha, Bolong Tan
Klora Wang, Zichao Yue
Undergraduate TAs Mohammad Al-Labadi, Anjelica Bian, Dyllan Hofflich, Zach Jessup
Zarif Karim, Nita Kattimani, Amy Le, Nicole Li, Kevin Rodriguez
Paige Shelton, Max Trager, Justin Wong, Steven Yu, Wei Zheng
Lectures Tue/Thu, 11:40–12:55pm @ 155 Olin Hall
Lab Sessions Mon, 11:15– 2:15pm @ 238 Phillips Hall
Mon, 1:25– 4:25pm @ 238 Phillips Hall
Tue, 7:30–10:30pm @ 238 Phillips Hall
Wed, 7:30–10:30pm @ 238 Phillips Hall
Optional
Discussion
Section
Fri, 1:25–2:15pm @ 225 Upson Hall
Fri, 2:30–3:20pm @ 225 Upson Hall
Fri, 3:35–4:25pm @ 225 Upson Hall
Required
Textbook
D. M. Harris and S. L. Harris
"Digital Design and Computer Architecture: RISC-V Edition"
1st edition, Morgan Kaufmann, 2021
Available through Canvas via the Cornell Academic Materials Program
Available in paperback from Amazon ($95)
Staff Email ece2300-staff-l cornell edu

Objectives

This course is meant to be a foundational course in computer engineering. The course will prepare students for more advanced coursework in computer engineering (e.g., embedded systems, computer architecture) as well as provide context for more advanced coursework that focuses lower in the computer systems stack (e.g., micro-electronics, digital VLSI) or higher in the computer systems stack (e.g., compilers, operating systems). By the end of this course, students should be able to:

Prerequisites

This course is targeted towards sophomore-level undergraduate students, although it is also appropriate for advanced freshman students and upperclassman. An introductory course on computing is required. Students need to be comfortable using at least one programming language (e.g., Python through CS 1110 or MATLAB through CS 1112). No prior knowledge of the Verilog hardware description language is necessary.

Topics

The course includes four parts. The first two parts cover digital logic, while the second two parts cover computer organization. A list of topics for each part is included below. The exact topics covered in the course are subject to change based on student progress and interest.

Required Textbook

The required textbook for the course is "Digital Design and Computer Architecture, RISC-V Edition," by D. M. Harris and S. L. Harris (Morgan Kaufmann, 2021). There are three different editions of this book for three different instruction set architectures: MIPS, ARM, RISC-V. It is critical that students use the RISC-V edition. All students will have access to the textbook online through Canvas via the Cornell Academic Materials Program.

Format and Procedures

This course includes a combination of lectures, quizzes, discussion sections, readings, practice problems, lab assignments, and exams.

Grading Scheme

This course will be adopting a philosophy of ``grading for equity'' where grading is exclusively used to assess mastery of the material covered in the course as opposed to rewarding effort and/or incentivizing specific behaviors. To this end, each part or criteria of every assignment is graded on a five-point scale without any curve according to the following rubric.

A score of 5 corresponds to an A, 4 corresponds to a B, 3 corresponds to a C, and so on. A score of 5.25 is reserved for when the submitted work is perfect with absolutely no mistakes or is exceptional in some other way.

Total scores for an assignment are a weighted average of the scores for each part or criteria. Parts or criteria are usually structured to assess a student's understanding according to four kinds of knowledge: basic recall of previously seen concepts, applying concepts in new situations, qualitatively and quantitatively evaluating alternatives, and creatively implementing new designs; these are ordered in increasing sophistication and thus increasing weight. In almost all cases, scores are awarded for demonstrating understanding and not for effort. Detailed rubrics for all quizzes, lab assignments, and exams are provided once the assignment has been graded to enable students to easily see how the score was awarded.

The final grade is calculated using a weighted average of all assignments. All quiz grades are averaged to form a single total. Students can drop their lowest quiz score.

Quizzes 5%(students can drop lowest score)
Lab 1 4%(part 1 and 2 weighted equally)
Lab 2 8%(part 1 and 2 weighted equally)
Lab 3 8%(part 1 and 2 weighted equally)
Lab 4 12%(part 1 and 2 weighted equally)
Lab 5 4%
Prelim 1 17%
Prelim 2 17%
Final Exam 25%

We will drop a student's lowest quiz grade. This means if a student has to miss one quiz for any reason (including for a family or medical emergency) there is no need to notify the course instructor. If a student has to miss more than one quiz due to a family or medical emergency then the student should notify the instructor in advance to discuss an alternative.

Note that the exams account for over half of a student's final grade. The exams in this course are very challenging. Successful students begin preparing for the exams far in advance by carefully reviewing the assigned readings, independently developing study problems, and participating in critical study groups.

To pass the course, a student must at a bare minimum satisfy the following requirements: (1) submit six out of the nine laboratory assignment parts; (2) take both prelim exams; and (3) take the final exam. \BF{If a student does not satisfy these criteria then that student may fail the course regardless of the student's numerical grade.} The instructor reserves the right to award a D letter grade for students who barely satisfy this criteria but are clearly making no real effort to engage in the course and their own learning.

Policies

This section outlines various policies concerning auditors, usage of cellular phones and laptops in lecture, turning in assignments late, regrading assignments, collaboration, copyright, and accommodations for students with disabilities.

Auditor Policy

Casual listeners that attend lecture but do not enroll as auditors are not allowed; you must enroll officially as an auditor. If you would like to audit the course please talk to the instructor first! Usually we wait until the second week of classes before allowing auditors to enroll, to ensure there is sufficient capacity in the lecture room. The requirements for auditors are: (1) attend most of the lectures; (2) complete most of the in-class quizzes; and (3) perform reasonably well on these quizzes. If you do not plan on attending the lectures, then please do not audit the course. Please note that students are not allowed to audit the course and then take it for credit in a later year unless there is some kind of truly exceptional circumstance.

Cellular Phones and Laptops in Lecture Policy

Students are prohibited from using cellular phones and laptops in lecture unless they receive explicit permission from the instructor. It is not practical to take notes with a laptop for this course. Students will need to write on the handouts, quickly draw timing diagrams, and sketch gate- or block-level diagrams during lecture. The distraction caused by a few students using (or misusing) laptops during lecture far outweighs any benefit. Tablets are allowed as long as they are kept flat and used exclusively for note taking. If you feel that you have a strong case for using a laptop during lecture then please speak with the instructor.

Late Assignment Policy

Lab assignment code must be submitted electronically via GitHub. Lab reports must be submitted electronically in PDF format. No other formats will be accepted! Assignments must be submitted by 11:59pm on the due date unless otherwise specified. No late submissions will be accepted and no extensions will be granted except for a family or medical emergency. The instructors must be notified of this emergency in advance if at all possible. You can continue to push your code to GitHub and resubmit your report to Canvas as many times as you would like up until the deadline, so please feel free to upload early and often. If you submit an assignment even one minute past the deadline, then the assignment will be marked as late and not graded. We simply cannot accept late work given the tight timeline of the course. If you do not finish the code for the simulation part of an assignment, push what you have to GitHub and you can continue working on it after the deadline to: (1) ensure you have working code for the FPGA part; and (2) earn some points back for the simulation part through the revision process.

Regrade Policy

Addition errors in the total score are always applicable for regrades. Regrades concerning the actual solution should be rare and are only permitted when there is a significant error. Please only make regrade requests when the case is strong and a significant number of points are at stake. Regrade requests should be submitted online via a private post on Ed within one week of when an assignment is returned to the student or within one week of when an exam is reviewed with the class. You must provide a justification for the regrade request.

Collaboration Policy

The work you submit for the lab assignments is expected to accurately demonstrate your understanding of the material. The use of a computer in no way modifies the standards of academic integrity expected under the University Code. You are encouraged to discuss information and concepts covered in lecture and relevant to the lab assignments with other students. You can give ``consulting'' help to or receive ``consulting'' help from other students about the lab assignments. Students can also freely discuss basic computing skills or the course infrastructure. However, this permissible cooperation should never involve one student (or group) having possession of or observing in detail a copy of all or part of work done by someone else, in the form of an email, an email attachment file, a flash drive, or on a computer screen. Students are not allowed to seek consulting help from online forums outside of Cornell University. If a student receives consulting help from anyone outside of the course staff, then the student must acknowledge this help on the submitted assignment.

As an exception to the outside consulting policy described above, students are allowed to use artificial intelligence (AI) systems (e.g., OpenAI ChatGPT, Anthropic Claude, Microsoft Copilot) in absolutely any way they want in the course as long as all submitted material still represents the students' understanding. Students are free to use AI to explain lecture concepts, create practice problems, explain problem solutions, write Verilog code, debug Verilog code, analyze Verilog compile-time errors, brainstorm test cases, and/or edit lab reports. The only condition is that students must acknowledge how they used AI in any submitted work. Students must include an AI acknowledgment as a comment at the top of any source code for which AI was used in any way. Students must include an AI acknowledgment at the end of lab report for which AI was used in any way. The AI acknowledgment should clearly specify which AI was used and how it was used. Using AI without acknowledgment will be considered and academic integrity violation. Students are responsible for all of their submitted work and that work must represent their understanding even with an AI acknowledgment. The instructor reserves the right to use a short oral inquiry with students to verify that they understand anything they submit as their own work.

During in-class paper quizzes and examinations, you must do your own work. Talking or discussion is not permitted during the in-class paper quizzes and examinations, nor may you compare papers, copy from others, or collaborate in any way. Students must not discuss a quiz/exam's contents with other students who have not taken the quiz/exam. If prior to taking it, you are inadvertently exposed to material in an quiz/exam (by whatever means) you must immediately inform an instructor.

Should a violation of the code of academic integrity occur, then a primary hearing will be held. See https://deanoffaculty.cornell.edu/faculty-and-academic-affairs/academic-integrity for more information about academic integrity proceedings.

Examples of acceptable collaboration:

Examples of unacceptable collaboration:

Notice that the key is that students should not share the actual code with each other unless expressly permitted by the course instructors; and that all submitted work must represent a student's understanding.

Copyright Policy

All course materials produced by the course instructor (including all handouts, tutorials, quizzes, exams, videos, scripts, and code) are copyright of the course instructor unless otherwise noted. Download and use of these materials are permitted for individual educational non-commercial purposes only. Redistribution either in part or in whole via both commercial (e.g., Course Hero) or non-commercial (e.g., public website) requires written permission of the copyright holder.

Accommodations for Students with Disabilities

In compliance with the Cornell University policy and equal access laws, the instructor is available to discuss appropriate academic accommodations that may be required for students with disabilities. All communications concerning accommodations should be done privately with the instructor either via email or in-person. Requests for academic accommodations are to be made during the first three weeks of the semester, except for unusual circumstances, so arrangements can be made. Students must register with Student Disability Services to verify their eligibility for appropriate accommodations. Note that students cannot simply rely on Student Disability Services to email the instructor without actually speaking to the instructor in person. Students with a disability must speak with the instructor in person during the first three weeks to discuss their accommodations.

Online and Computing Resources

We will be making use of a variety of online websites and computing resources.