Lecture: Dana 132, MWF 10:00 am – 10:50 am.
Cross-listed: ECEG 443/643 High-Performance Computer Architecture
Instructor
- Office: Dana 335a
- Email: amm042@bucknell.edu
- Meet: Schedule an appointment
Resources
- Course schedule
- Slides and materials are available on Google Classroom.
- Course Discord
Course Summary
Use a hardware description language to describe and design digital computing systems. Topics include: processor design, pipelining, cache and storage systems, instruction, thread, and process level parallelism, speculation, and branch prediction.
Course Objectives
By the end of the semester:
- Students will be able to express designs based on classical computer architectural concepts using appropriate engineering tools. (EAC a, b, c, k) (CAC a, c, i)
- Students will be able to explain and apply fundamental architectural principles such as locality, optimizing common cases, and parallelism to modern architecture design. (EAC a, e) (CAC a)
Textbook
The course closely follows parts of the Hennessy and Patterson Computer Architecture textbook (6e). See the schedule for the chapter/sections corresponding to each class. Some students may be successful from the provided materials alone, however, reviewing the indicated sections will significantly deepen your learning.
Required Textbook
- Hennessy and Patterson, “Computer Architecture: A Quantitative Approach”, 6th Edition. ISBN978-0128119051. The library also has the eBook version available (Bucknell login required).
Recommended Reference Textbooks
- Patterson and Hennessy, “Computer Organization and Design RISC-V Edition“, 2nd Edition. ISBN 978-0124077263. This is the required text for CSCI 206. The eBook is also available (Bucknell login required).
- Samir Palnitkar, “Verilog HDL”, 2nd Edition. ISBN 978-0132599702. One (physical) copy is available at the library. No eBook available.
Attendance and Participation
An important part of the class is your active participation in lecture sections. If people do not come to lecture, come late, or do not engage while in lecture, it degrades the quality of the class for everyone. Therefore, all students are expected to attend and actively participate in all lectures. If you have to miss class for job interviews, athletics, etc, please contact the instructor at least 24 hours prior to the start of that class. If you are unable to come to class due to illness or an urgent emergency, let me know when you can. You will be responsible for making up any/all missed work. If you miss a graded activity/quiz without prior notice, you will receive a grade of zero for that activity.
Activities & Homework
Many classes will include some sort of activity. Many times you will have time to complete the activity in class. If you do not complete an activity in class, it is your homework and is due on the assigned due date. If there is no date, assume it’s due at the beginning of the next class. Activities will make up the majority of your Quizzes, Activities, Participation grade. It is your responsibility to complete the activities and submit them to Google Classroom before the due date.
Late Work
If you need an extension for a valid reason, such as illness, family emergencies, or other unforeseen circumstances, please request permission from the instructor at least 24 hours before the deadline via email or Discord. Note that sports competitions, job interviews, and deadlines in other courses are generally not considered valid reasons.
Unexcused late submissions will incur a 10% grade reduction per week, up to a maximum of 3 weeks. Weeks round up to the nearest week.
Grading
Your instructor will make every effort to promptly return all graded work to you (usually by the next scheduled class). Projects and larger assignments will take longer (typically 1 week). All grades will be published on Google Classroom. If you think you find a grading error, you may request a regrade. Regrade requests must be received no later than 72 hours after the assignment/exam is returned. It is possible for the new grade to be lower than the original grade. In all cases, the most recent grade is used (not the highest grade). If you would like to discuss your grade at any time, please contact me for a meeting.
The grade distribution of the components of the course is shown below. Students must pass all bold items marked with a * to pass the course (separately).
| Quizzes, Activities, Participation* | 35% |
| Exam 1 | 15% |
| Exam 2 | 15% |
| Exam 3 | 15% |
| Final Exam* | 20% |
The standard grading scale (below) is used to assign letter grades.
| Score | Grade |
| 93 | A |
| 90-92 | A- |
| 87-89 | B+ |
| 83-86 | B |
| 80-82 | B- |
| 77-79 | C+ |
| 73-76 | C |
| 70-72 | C- |
| 60-69 | D |
| <60 | F |
Bucknell University Honor Code
As a student and citizen of the Bucknell University community:
- I will not lie, cheat, or steal in my academic endeavors.
- I will forthrightly oppose each and every instance of academic dishonesty.
- I will let my conscience guide my decision to communicate directly with any person or persons I believe to have been dishonest in academic work.
- I will let my conscience guide my decision on reporting breaches of academic integrity to the appropriate faculty or deans.
Expectations for Academic Engagement
Courses at Bucknell that receive one unit of academic credit have a minimum expectation of 12 hours per week of student academic engagement. Student academic engagement includes both the hours of direct faculty instruction (or its equivalent) and the hours spent on out-of-class student work.
Source: Bucknell University Academic Policies and Requirements
Use of AI
The use of Artificial Intelligence (AI) tools and resources is encouraged to enhance learning and understanding. However, students must use these tools ethically and responsibly. AI can be a powerful aid in coding, debugging, and conceptual understanding, but it should not be a substitute for personal effort and academic integrity. Additionally, note that AI tools will not be available for exams, including the final.
Guidelines for the ethical use of AI tools and resources:
- Academic Integrity: Any work submitted must be the student’s own. While AI can assist in learning and problem-solving, all submitted work should reflect individual effort. Plagiarism or reliance on AI to complete assignments without proper understanding will not be tolerated and may result in disciplinary action.
- Proper Attribution: When AI tools are used, proper attribution must be given. If AI resources provide specific code snippets, solutions, or significant assistance, this should be clearly noted in the submission, including the prompts used.
- Learning Enhancement: AI can be a valuable tool for exploring new concepts, generating ideas, and improving coding skills. Students are encouraged to use AI to experiment and learn, but they should also strive to understand the underlying principles and logic behind the AI-generated content.
- Limitations of AI: Students should be aware that AI tools have limitations and may not always provide accurate or optimal solutions. Critical thinking and independent verification of AI-generated content are essential to ensure correctness and understanding.
- Written Work: AI tools may be used to create drafts and revise written work. However, AI-generated text should not be used verbatim. Students must critically review, edit, and revise any AI-generated content to ensure it is accurate, coherent, and aligns with the assignment requirements. The final submission should reflect the student’s own understanding and effort. Using AI-generated text without proper revision or personal contribution is unacceptable and will be considered a violation of academic integrity.
Access Statement
Any student who needs accommodation based on the impact of a disability should contact the OAR at OAR@bucknell.edu; 570-577-1188 or complete the Disability Accommodation Request form. The OAR will coordinate reasonable accommodations for students with documented disabilities.
If you have a disability and think you may need an accommodation, I encourage you to contact the OAR. The OAR is here to help and will work with you to determine appropriate accommodations. If accommodations are needed, the OAR will communicate those to me through a Letter of Accommodation. I will not be given information about the nature of your disability, only the accommodations you need. I will treat any information I receive as private and confidential. Please visit https://www.bucknell.edu/life-bucknell/diversity-equity-inclusion/accessibility-resources.
Common Course Policies
This course will adhere to the common course policies as outlined by the department.