CSCI 2021: Machine Architecture and Organization

Introduction to hardware/software components of computer system. Data representation, boolean algebra, machine-level programs, instruction set architecture, processor organization, memory hierarchy, virtual memory, compiling, linking. Programming in C.

Grade of C or better in CSCI 1913, CSCI 1933, or equivalent courses or instructor consent.

It is presumed that students will have the equivalent of 1 year of college-level programming in some high-level language such as Python or Java prior to taking this course. The C programming language will be introduced but not at an introductory level so prior programming experience is a must.

Students that complete CSCI 2021 will posses the following characteristics.

• Basic proficiency at C programming including pointers and addressing, dynamic memory allocation and management, basic file I/O operations. Ability to edit, compile, run, and debug C programs.
• Knowledge of running programs in physical memory including the stack, heap, global, and text areas of memory and how each area behaves. Basic understanding of security risks associated with programming errors related to memory such as buffer overflows.
• Understanding of the essential elements of assembly languages executed by CPUs, specifically familiarity with the x86 / x86-64 assembly language
• Knowledge of the correspondence between high-level program constructs and assembly instructions which are executed by the CPU.
• Ability to use a symbolic debugger to step through both C programs and assembly programs to aid in debugging programs.
• Basic understanding of how data is encoded in binary including signed and unsigned integers, floating point numbers, character data, and machine instructions
• Knowledge of computer memory systems, particularly the memory hierarchy of registers, caches, main memory, and permanent storage. Basic understanding of caching techniques and efficient virtual memory address translation to physical addresses.
• Basic knowledge of computer architecture including the implementation of instructions with Boolean logic gates, processor pipe-lining for efficiency, and out of order instruction execution.

Office Hours for staff will be posted on the course Canvas site. Office hours for all staff are open to all students in any section of the course governed by this syllabus. No appointments are necessary but usually students receive help on a first-come / first-serve basis. Often office hours will become crowded around project deadlines and students are advised to start projects early, come to office hours with questions prepared, and be patient.

Check our Canvas site to see available office hours and note the locations: some office hours are held in-person while other office hours are held Online via Discord.

Students are strongly encouraged to visit the professor and teaching assistant(s) during office hours to further their understanding of the material: we are here to help you learn.

This offering of the course will be administered in a mixture of in-person + online which means you should acquaint yourself with the following resources / policies on communication in the class.

• Canvas (Course Management): used to provide links to other resources and for Overall grade dissemination
• Discord (Online Office Hours): used to visit online office hours, allows real-time audio/video communication, grouping into "rooms/tables", support for text chat which is used to facilitate help queues. The invite link to our "guild" is available on our Canvas site.
• Gradescope (Assignments/Exams): used to submit most graded work, receive grades on that work, and make requests for regrades.
• Piazza (Announcements/Async Q&A): used to ask questions on course material outside of synchronous meetings and for staff to make announcements to students.
• Zoom (Video Conferencing): used to present audio/video synchronously such for individual online appointments.

This is an in-person course but many elements of the course can be completed without physical attendance. Fully remote students are not supported in this class as all students must attend exams in person.

A summary of course elements and their particulars is below.

Final grades will be determined by scores obtained on the components below according to their associated weight.

Final grades will be assigned without rounding according to the following criteria.

If circumstances require it, the grading scale may be adjusted, generally in the students' favor.

Throughout the semester, students will have opportunities to earn and use engagement points. The system is a follows.

1. Each lab completed earns 1 EP and there are typically 13-14 labs in a semester.
2. There will be a few opportunities to take course surveys which earn 1 EP as well.

3. BONUS Engagement points may be earned through participation in lecture and by answering questions on Piazza. At the end of the semester, the total number of times students participated in these places will determine their Bonus EPs according to this formula:

   BonusEP = log2(1 + LectureParticipation + PiazzaAnswers)

4. Late Project submissions COST 1 Engagement Point per day late.

Each Engagement Point is worth 1% to a maximum of 10% for a student's overall grade. Each engagement point beyond this earns 0.25% Bonus Credit to a student's overall grade. This is the sole bonus credit mechanism in the course so students are encouraged to attend Lecture and Lab to earn Engagement points.

FAQ: How many Engagment Points do I have? Count the number of labs you have completed. Then check the participation sheet in lecture and number of questions you've answered on Piazza and apply the formula above to get your bonus EPs. Subtract the number of days late you've submitted.

Lectures will be delivered in person at the times/locations mentioned in the course schedule. During lectures, students will frequently be asked to work on short exercises with a few of their colleagues. After working on these exercises, the Professor will select a 1-2 students from the "Hot Seats" section of the lecture hall to discuss their answers with the class. Showing effort on these exercises will earn bonus Engagement Points. Hot Seats locations will be announced at the beginning of the course and are typically the first few rows of a lecture hall or a few designated tables in an active classroom.

All lectures will be recorded and posted for asynchronous viewing within 48 hours of the meeting. Students not able to attend lecture synchronously will miss the chance to ask questions and earn bonus Engagement Points there but can still earn full credit in the course through other means of acquiring EPs such as completing required Lab work.

In the event that the instructor is ill or the University deems the level of plague too high too risk in-person meetings, Lectures will be held in a similar format online via Zoom. Updates on any such changes will be announced to students through Piazza and Email.

Lab sections meet once per week in the locations mentioned. Credit for Labs will be earned by submitting work online which generally earns 1 Engagement Point for correct work.

Students do not need to attend lab meetings synchronously to earn credit but during Lab meetings, staff will give brief demos, group students to help complete the lab exercises, and be on hand to help students surmount difficulties with lab work. Attending lab mostly guarantees earning credit and lab is a great place to meet other students in the class.

Lab Exercises are Open Resource and Open Collaboration. Students are encouraged to work in groups during lab to complete the work and can submit their work as a group (one submission, several students getting credit for it). Generally lab work is automatically graded so feedback is available immediately.

No late submissions will be accepted for labs. All lab work must be completed by the next week's lab.

Each week a set of Homework exercises will be posted online which reinforce and apply lecture topics. Associated with this Homework is an online Quiz. Completing Homework exercises will prepare students to take the online Quiz. Homework and Quizzes are Open Resource and Open Collaboration: students may work together with other students in our section(s) of the course to complete homework/quizzes and are encouraged to do so. Submitting identical answers for homework/quizzes is acceptable so long as it does not violate the PRIME DIRECTIVE.

Online Quizzes are graded automatically and scores will be available immediately after completing the quiz and quizzes may be retaken an unlimited number of times up to the deadline.

No late submissions for weekly Homework/Quizzes will be accepted and no regrade requests are allowed. Missing the deadline results in 0 credit. The two lowest HW Quiz scores will be dropped in final grade calculations

Students will receive a number of programming projects during the semester. Each project will involve writing programs and answering questions about them to illustrate an understanding of course material. Generally Projects are Individual Work with sharing of code or detailed solutions being a violation of the PRIME DIRECTIVE. Pay careful attention to the guidelines for each programming project. Projects are usually large and require a significant amount of work to complete.

Project grading will include the following elements.

1. Manual Inspection: Projects will include a checklist of features of completely correct answers. These usually comprise things that cannot be easily checked automatically such as showing the process to reach an answer, inclusion of key elements of an answer, or style aspects of computer code. These features will be checked by graders and assigned credit based on level of compliance.
2. Automatic Testing: Some projects may have automatic tests provided which check for correctly functioning programs or answers. In most cases, these automatic checks will be publicly available for use while working on the assignment.

Late submission of Projects is governed by the following.

• No projects will be accepted more than 48 hours after a deadline
• On-time Projects receive no penalties
• Submitting 1-24 hours will result in the loss of 1 Engagement Point
• Submitting 25-48 hours late will result in the loss of 2 Engagement Points
• Engagement points can be earned in a variety of ways mentioned in the Engagement Points Section.
• Students may submit projects as many times as they wish: the most recent submission will be graded though if it is submitted late it will cost Engagement Points.

NOTE: If students complete all 14 Labs, they will earn full engagement scores and have 4 days of late submissions possible while maintaining full credit.

There will be a series of midterm exams during the semester and a comprehensive final exam at the end of the semester. Exams take place during the regularly scheduled lecture period and are worth a significant portion of the overall course grade.

At the time of this writing, Exams will take place during lecture meetings in the normal lecture location. Any changes to this will be posted in advance of the exams.

All exams are Open Resource Exams: unless otherwise specified you may use any course content during exams including lecture slides, your notes, the textbook, editors/compilers/shells, and any code the you have written or received from course staff. No communication is allowed during the exam (no email/texting/chat), and no Internet searches are allowed (do not "google for answers"). In addition, you may only use exams from previous versions of 2021 if you personally took those exams. If in doubt, ask about specifics before or during the exam.

All exams will be preceded by official Practice Exams so that students can acquaint themselves with the tools and tactics to be successful.

Missing an exam results in a zero score and make-up exams will be considered only in situations involving significant life events. Proof of such circumstances will be required for a make-up to be considered.

Most coursework will be graded via Gradescope which features a Request Regrade Button associated with specific problems and criteria. This will notify the specific individual responsible grading about the dispute. Raise regrade requests respectfully and specifically: mention what you think a grader missed in your answer or why you feel a deduction was unfair. Keep in mind that graders assign credit based on what appears on the project and exams, not post-hoc explanations of answers.

If a Student and Grader are not able to resolve a grading issue to the satisfaction of both, the student can ask the grader to consult the Professor who will review the dispute and resolve it. Students should ask their grader to do this, not email the Professor directly.

When grades are published, there will generally be a 1 week window in which disputes are considered. Failing to request a regrade in that time will forfeit further opportunity to contest the grade.

Readings from the textbook relevant to each lecture are listed in the schedule. You will increase your understanding of lectures by reading associated textbook sections ahead of time, though this is not assumed. We may provide additional reading material to supplement the textbook which will be posted on the course web page.

Some coursework is to be done individually, usually programming Projects and Exams. For this individual work, the following actions constitute scholastic misconduct (cheating) and will be reported.

• Directly copying someone else's solution to an assessment problem, including student solutions from a previous semester
• Directly copying an answer from some outside source such as the Internet or friend for a project problem.
• Making use of an Instructor Solution manual to complete problems.
• Submitting someone else's work as your own.
• Using or sharing Exam materials from another student from past offerings of this course; you may view your own past copies of exams but not share them with others.
• Paying someone for a solutions to assignments/exams.
• Posting solutions to any web site including public posts to our course web site.
• Collaborating or copying the work of others during an exam.
• Taking another student's code with or without their consent.
• Giving another student one's own code on assignments or exams
• Aiding or abetting any of the above.
• Witnessing any of the above and failing to report it to an instructor immediately.

REMEMBER: Once you give away your code/work, you lose control of it. This may lead to pain in the following non-obvious cases

• Using a public Github repository to track your code allows anyone to copy it and submit it as their own.
• Sharing code with a classmate "just to help them" may lead to them submitting it as their own, sharing it with others, or selling it for profit
• Giving someone access to your accounts or devices to help them may mean that they use your account to steal your work subsequently.
• Leaving your work open in a public space may allow someone to take snapshots of your screen and use it as their own.

All Of This Has Happened Before And Will Happen Again. Don't become one of your Professor's stories.

Refer to the following links for additional information.

• UMN Student Conduct Code
• Computer Science Department policies on scholastic dishonesty
• Office of Community Standards

Any instance of misconduct that is detected will investigated and may be referred to the Office of Community Standards. The most common penalty is an F in the course. Be advised that the teaching team will be employing electronic means to detect plagiarism. As easy as it may be to copy code, so to it is easy to detect copies. Keep your nose clean.

The purpose of this course is to learn about programming and learning from other students is a great boon. To that end, the following actions will NOT be considered cheating in this course.

• Collaboration on Lab Activities and weekly Homework Exercises/Quizzes is allowed and encouraged. These are a great opportunity to help one another on work that counts towards your final grade. Just make sure that you understand any solutions you submit as per the PRIME DIRECTIVE.
• Discussing projects at a high level with other course students is fair so long as no code is shared. Take great care at the point of directly showing your work to others as your answers are subsequently out of your own control.
• Asking public questions on the course discussion board so long as limited information about your own solution is included. To convey details of your solution, use private posts.
• Asking any course staff member questions in person or online is acceptable and encouraged. Staff members may initiate small group discussions in which collaboration is fine.
• Making use of your own code or exam materials which you accumulated from past semesters of this class or other classes is fine. If you are retaking the course, make sure staff know this so that no misunderstandings occur.
• If you are unsure whether a given collaboration is fair or not, stop the activity and clear it with your instructor.

At all times keep the PRIME DIRECTIVE in mind when studying with other students. The above collaborations should be limited to getting someone over a hurdle, not carrying them across the finish line.

There is another section of CSCI 2021 running under a different instructor which is not coordinated with this one. Projects, homeworks, quizzes, lab topics, schedule, and exams will differ between sections. The policies within this syllabus apply only to our section and students should refrain from collaborating outside of their own section to avoid problems.

All students and staff will be required to wear protective masks during class meetings. This directive comes from the University and is intended to stop the spread of disease during the pandemic. No eating/drinking will be allowed during class meetings so masks will stay on everyone throughout each meeting. If students feel they merit an exception to the policy should contact the Professor via email before attending class.

Full details of the University Mask policy are here: https://safe-campus.umn.edu/return-campus/face-coverings

This course will have a number of online interactions and the following additional policies on student/staff behavior and Academic Integrity also apply: https://communitystandards.umn.edu/know-code/online-learning-expectations

The gist of the behavior policies are "Don't be a troll" and the Academic Integrity portion reflects our PRIME DIRECTIVE.

This course will include video and audio recordings of class lectures and classroom activities. These recordings will be used for educational purposes and the instructor will make these available to students currently enrolled in this course. Students must seek instructor permission in order to share either course recordings or course content/materials. Similarly, instructors who wish to share zoom recordings with other sections or classes must seek and document permission from students whose image or voice are in these recordings.