Last Updated: 2019-08-29 Thu 14:21

CSCI 2021: Machine Architecture and Organization

University of Minnesota

4 credits, Fall 2019

Table of Contents

1 Basic Information

1.1 Catalog Description

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.

1.2 Prerequisites

Grade of C or better in CSCI 1913 or 1933 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.

1.3 Course Goals

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.

1.4 Instructor

Name Chris Kauffman
Sections 001 and 010
Email kauffman@umn.edu
Office Shepherd 327
Phone 612-626-9531

1.5 Teaching Assistants

Name Email Role  
Jaskaran Veer Singh singh882@umn.edu GTA 50%
Kartik Ramkrishnan ramkr004@umn.edu GTA 25%
Marco Dow dow00017@umn.edu GTA 50%
Sai Kumar Kayala kayal004@umn.edu GTA 50%
Renjie Li li001000@umn.edu GTA 50%
Aaron Councilman counc009@umn.edu UTA  
Daniel Luick luick009@umn.edu UTA  
David Ma maxxx818@umn.edu UTA  
Emma Yoho yohox014@umn.edu UTA  
Ge Yu yuxx0851@umn.edu UTA  
Jacob Lindahl linda187@umn.edu UTA  
Jacob Walters walte735@umn.edu UTA  
Jonathan Brenner brenn563@umn.edu UTA  
Joseph Larson lars4076@umn.edu UTA  
Klarisse Andre de St Amat andre971@umn.edu UTA  
Min Hyung Choi choix698@umn.edu UTA  
Noah Park park1623@umn.edu, UTA  
Sam Matenaer maten009@umn.edu UTA  
Terrance Gray grayx501@umn.edu UTA  
Tien Dinh dinh0080@umn.edu UTA  
Yancheng (Gordon) Yuan yuanx322@umn.edu UTA  

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.

1.6 Lectures and Labs

Meeting Day / Time Location
Lecture 01 MWF 01:25 PM-02:15 PM Willey Hall 125
Lab 02 Wed 08:00 AM-08:50 AM Keller Hall 1-250
Lab 03 Wed 09:05 AM-09:55 AM Keller Hall 1-250
Lab 05 Wed 10:10 AM-11:00 AM Keller Hall 1-250
Lab 06 Wed 10:10 AM-11:00 AM Lind Hall 40
Lab 07 Wed 11:15 AM-12:05 PM Keller Hall 1-250
Lecture 10 MWF 03:35 PM-04:25 PM Amundson Hall B75
Lab 11 Wed 11:15 AM-12:05 PM Lind Hall 40
Lab 12 Wed 12:20 PM-01:10 PM Keller Hall 1-250
Lab 13 Wed 12:20 PM-01:10 PM Lind Hall 40
Lab 14 Wed 01:25 PM-02:15 PM Keller Hall 1-250
Lab 15 Wed 01:25 PM-02:15 PM Lind Hall 40

1.7 Course Materials

Textbook

Computer Systems: A Programmer's Perspective, Third Edition by R. Bryant, D. O'Hallaron, Pearson, 2016
(Required) This is our main course text and covers a wide range of computer architecture issues. The textbook website is here: http://csapp.cs.cmu.edu/
C Programming Language Second Edition by Brian Kernighan and Dennis M. Ritchie, Prentice Hall 1988
(Optional) This is the classic reference to the C programming language. It is aimed at folks with a good understanding of computing systems and is thus not the easiest introduction to the language for beginners. The tutorials below supplement this somewhat.

Additional online resources associated with C programming and architecture will be posted in the course materials.

Video Tutorials

The following Video Programming Tutorials are available via Lynda.com for free via licensing at the UMN. They are not required but can serve as an additional resource on C programming for those that want more explanation than what is provided in lecture and lab meetings.

Note: All of these tutorials favor IDEs (integrated development environments) rather than the command line tools we will use.

Computing

It is assumed you will have access to a computer with the ability to edit, compile, and run Unix programs. Some university labs provide this ability; the first week of the course will cover how to set up your personal environment as well. If you have difficulty accessing a suitable environment, contact the course staff.

You will need to create a CSE Labs account for use on assignments and during Discussion. Accounts can be created here: https://wwws.cs.umn.edu/account-management/

1.8 Communication

  • Canvas is used for overall grade dissemination and Lab Quizzes. https://canvas.umn.edu/courses/114140
  • Gradescope is used for Assignment submission/grading and Exam grade dissemination.
  • Piazza is the central site for our announcements and discussion board. The announcements and discussion board are part of the required reading for the course.
    • Sign up for our piazza site here: http://piazza.com/umn/fall2019/csci2021
    • All instructors and TAs can view all material on Piazza
    • Do not e-mail course staff about programming problems; use the discussion board.
    • Use public posts on Piazza to discuss programming project requirements, labs, and other material related to the course.
    • When prompted by a TA, use private posts on Piazza to share portions of your code pertaining to your questions. Don't share your project code in public posts.
    • Refer to the Piazza main page for etiquette on what should be posted publicly versus privately.
    • Email course staff only for logistical issues such as illness, emergencies, meeting outside of office hours, missing lab/lecture, etc.
  • 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.

2 Coursework

2.1 Lectures

During lectures we will discuss concepts and instructors will provide demos relevant to other course work. In addition to attending the regular meeting times, you are strongly encouraged to visit the professor and teaching assistant(s) during office hours to further your understanding of the material: we are here to help you learn.

2.2 Textbook Readings

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.

2.3 Lab Sections

Lab sections meet once per week and attendance is not required to get full credit. In each meeting, the lab leader will guide students through exercises to reinforce course concepts. These exercises are required and completing them will prepare students take short, online quizzes associated with the lab work. Students are encouraged to freely collaborate on lab exercises and quizzes which are usually due prior to the next lab meeting.

2.4 Assignments

Students will receive a number of homework assignments during the semester. These will be a combination of programming, analysis, debugging, and problem solving. Unless otherwise stated, assignments will require individual work with no collaboration allowed. Pay careful attention to the guidelines for each assignment. Assignments are usually large and require a significant amount of work to complete.

2.5 Exams

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

3 Grading Policies

3.1 Graded Components

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

Component Weight Policy
Collaborative Lab Exercises (14) 10% Drop two lowest scores
Individual Assignments (5-6) 20% No drops
Midterm Exams (3 x 15%) 45% No drops
Final Exam 25% Comprehensive

3.2 Final Grade Determination

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

Percent Grade Percent Grade Percent Grade Percent Grade
>= 93 A 87-89 B+ 77-79 C+ 65-69 D+
90-92 A- 83-86 B 73-76 C 60-64 D
    80-82 B- 70-72 C- <60 F

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

3.3 Lab Exercises Grading

No late submissions for Lab Exercises and Quizzes will be accepted. Missing the deadline results in 0 credit. The two lowest scores on Labs will be dropped in final grade calculations

During labs, students will receive a short introduction to a topic by lab staff members then be given time to work on problems.

Lab grades will be based on short, online quizzes associated with the lab exercises. The lab exercise questions must be completed and submitted as part of the quiz as they are used to prepare for the quiz. If students wish to improve their lab score, they can meet with a TA in person to review their mistakes and improve their answers to receive credit back.

Students may collaborate with other students in our section(s) of the course to complete exercises/quizzes and are encouraged to do so. Submitting identical answers for exercises is acceptable so long as it does not violate the PRIME DIRECTIVE.

3.4 Assignment Grading

Rules for collaboration on assignments are indicated in the assignment specification and usually involve NO collaboration with other students. Utilize the discussion board and office hours of course staff if you have questions about the projects.

Assignment grading will include the following elements for grading.

  1. Manual Inspection: Assignments 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 assignments 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.

3.5 Late Assignment Submission

Late submission of assignments is governed by the following.

  • No assignment will be accepted more than 48 hours after a deadline
  • On-time assignments receive no penalties
  • Assignments submitted 1-24 hours late are capped at 75%
  • Assignments submitted 25-48 hours late are capped at 50%
  • Students can use a maximum of 3 Day-Late Tokens over the entire semester
  • On submitting late, up to two tokens are automatically charged to the student which will "buy back" a higher max score.
  • Token charges happen automatically and require no communication:
    • Submitting 1 day late will automatically charge 1 token
    • Submitting 2 days late will automatically charge 2 tokens unless only 1 token remains
  • Each unused token is worth 0.25% bonus credit overall in the course so submitting on time confers benefit at the end of the course
  • To avoid penalties and losing tokens, submit on time.
  • The table below gives examples of when an assignment is submitted, whether penalties apply, how tokens are charged, and their effects on assignment scores
    Pre- #Used #Used Post-      
    Token Tokens Tokens Token Raw Penalized  
Ex# Submitted Max Before After Max Score Score Comments
1 On-time 100% 0 0 100% 93 93 On-time means:
2 On-time 100% 0 0 100% 68 68 1. No tokens lost
3 On-time 100% 0 0 100% 46 46 2. No penalties
4 1-24 hours late 75% 0 1 100% 93 93 1 token used, max 100%
5 1-24 hours late 75% 3 3 75% 93 75 No tokens remain, max 75%
6 1-24 hours late 75% 2 3 100% 68 68 1 token used, max 100%, no benefit
7 1-24 hours late 75% 3 3 75% 68 68 No tokens remain, max 75%
8 25-48 hours late 50% 0 2 100% 93 93 2 tokens used, max 100%
9 25-48 hours late 50% 2 3 75% 93 75 1 token used, max 75%
10 25-48 hours late 50% 3 3 50% 93 50 No tokens, max 50%
11 25-48 hours late 50% 1 3 100% 68 68 2 tokens used, max 100%
12 25-48 hours late 50% 2 3 75% 68 68 1 token used, max 75%
13 25-48 hours late 50% 3 3 50% 68 50 No tokens, max 50%
14 >48 hours late 0% 0 0 0% 93 0 Not accepted or graded
15 >48 hours late 0% 1 1 0% 68 0 Not accepted or graded
16 >48 hours late 0% 3 3 0% 46 0 Not accepted or graded

3.6 Exam Policies and Grading

  • Your U-CARD is required for all exams though it may not be checked. You may be asked to show ID on handing your exam in to verify your identity.
  • Missing an exam results in a zero score and make-up exams will be considered only in situations involving death, near death, and documented dangerous diseases. Proof of such circumstances will be required for a make-up to be considered.
  • Open Resource Exams: Unless otherwise specified, exams will be open resource: notes, textbook, editor, compiler, and any code the student finds useful is allowed to be used. No communication is allowed during the exam (no email/texting/chat), no Internet searches are allowed, and no unauthorized web sites may be visited. If in doubt, ask about specifics before or during the exam.

3.7 Regrade Requests

Most Assignments and Exams 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 assignments 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 request that the grader involve 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.

3.8 Bonus Credit

Bonus credit will be awarded based on participation in class discussions in lecture. Students may elect to sit in the first few rows of the room ("hot seats") and answer questions. Reasonable effort on answering questions in class will garner class participation credit. Participation points may also earned for involvement in the class discussion board such as giving suggestions to students with questions (but not revealing answers wholesale). The highest point winner at the end of the semester will receive a 3% bonus to their overall score in the course. All other students will receive a bonus proportional to the highest point winner. For example, someone tied with the highest point scorer will also receive a 3% bonus while someone with half the participation points will receive a 1.5% bonus.

A small amount of bonus credit also available for unused Day Late Tokens at the end of each semester.

4 Academic Integrity

PRIME DIRECTIVE: Be able to explain your own work including assignment answers, program code, and exam solutions. The work you submit should be the product of your own effort and reflect your personal understanding.

Nearly all cheating in programming can be averted by adhering to the PRIME DIRECTIVE. Students may be asked at any time to explain code or exam solutions they submit. Inability to do so will be construed as evidence of misconduct. More specific guidelines are given below.

4.1 Thou Shalt Not

Unless otherwise specified, all assessments in this course are individual efforts involving no unfair collaboration. For the purposes of this course, 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 homework problem.
  • Making use of an Instructor Solution manual to complete problems.
  • Submitting someone else's work as your own.
  • Paying someone for a solutions to assignments.
  • 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.
  • Aiding or abetting any of the above.
  • Witnessing any of the above and failing to report it to an instructor immediately.

Refer to the following links for additional information.

4.2 Penalties

Any instance of misconduct that is detected will be referred to the Office of Community Standards and will likely result in failing the course. Be advised that the teaching team will be employing electronic means to detect plagiarism. This is extremely easy with computer code so keep your nose clean.

4.3 Fair Collaboration

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

  • Collaboration on Lab Exercises 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 assignments/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.
  • 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 another student. The above collaborations should be limited to getting someone over a hurdle, not carrying them across the finish line.

5 General Policies

General university policies which apply to our course are listed here: https://policy.umn.edu/education/syllabusrequirements-appa

Summaries of those policies are below.

Students are expected to maintain a high level of civility for all participants in and out of class meetings. This includes respecting participants of all genders, ethnicities, and social backgrounds. Harassment of any type will not be tolerated and failure to behave in a respectful manner will be reported to the University.

Observance of religious events will be accommodated for students of any faith. All possible accommodations will be made for students with disabilities. Please contact the Disability Resource Center and the instructor for further information.


Author: Chris Kauffman (kauffman@umn.edu)
Date: 2019-08-29 Thu 14:21