CMP 110 Orientation Notes (Intro to Computer Engineering)

CMP 110 Orientation Notes

  • Opening anecdote and setting: a personal moment about sailing at 10-11 mph on Lake Ontario; the speaker mentions a photo and that it’s visible on every screen they own.

  • Instructor and course context

    • Instructor: Omlang Nangli, department head of Computer Engineering.
    • Co-instructor: Dr. Cusak (mentioned as a co-guide for extending knowledge).
    • Course code: CMP 110 (one credit, first-semester introduction to computer engineering).
    • Audience engagement: questions about attendance at RIT Open House and other universities’ open houses.
    • Purpose: provide a basic overview of many topics in computer engineering, not an immersion in a single topic.

  • Course structure and expectations

    • Format: one credit, introductory across multiple topics, spanning ~14 weeks.
    • Depth: not designed for deep mastery of every topic in class; depth available via self-study and instructor guidance.
    • Topics: six plus real technical topics introduced; some topics will align with 1–3 future courses in the program.
    • Sneak peek: instructors will preview how future courses cover topics to help students plan their learning path.
    • Student initiative: students should pursue deeper understanding if desired; instructors will guide to materials.
    • Challenge: some topics will be brand-new compared to high school; expect difficult problem solving; emphasis on persistence with questions.
    • Advice: when stuck, ask questions; do not move on without ensuring understanding; attend office hours.

  • Learning approach and motivation

    • Emphasis on deep and critical thinking; self-initiated learning; material extendable through guidance from faculty.
    • Understanding motivation: different students motivated by curiosity, value creation, or creativity; instructors aim to connect motivation to topics.
    • Communications and professionalism: focus on how students write, speak, and interact with peers, superiors, faculty, and staff.
    • Importance of collaboration: engineering projects are typically group-based; strong communication and teamwork are essential.
    • Advisory council feedback: industry partners value effective communication of students’ skills beyond technical content; emphasis on employability through professional communication.

  • Student life, adaptation, and personal development

    • Transition to college: many students are away from home for the first time; acknowledge homesickness and emotional changes.
    • Coping strategies: acknowledge feelings, maintain self-discipline, balance study and play; avoid burnout (e.g., extreme late-night gaming).
    • Advising resources: advisers Ken, Lam, and Corina; they help with time management and academic planning.
    • Behavioral guidance: seek guidance early if falling behind or struggling with time management or other issues.
    • Availability of support: open to discuss non-academic concerns; instructors encourage reaching out for help.
    • Personal well-being: encourage unplugging, recharging through wholesome hobbies; avoid overcommitment to distractions.

  • Technology in class and classroom expectations

    • Laptop policy: instructors encourage bringing laptops for class activities; historically, they were hesitant to allow electronics due to disruptions.
    • Trust and responsibility: students are trusted not to misuse devices; inappropriate behavior (e.g., phone conversations in class) is discouraged but not policed at the table level.
    • Slide access: slides will be posted prior to classes; students can review them on their devices.
    • Distraction management: the instructor emphasizes personal responsibility and professional conduct; learning depends on engagement.

  • Instructor ethos and grading philosophy

    • Mantra: "you and I, we’re on the same team; your success is our success."
    • Goals: department aims for student success; not trying to give everyone an A, but assessments measure learning.
    • Honest grading: exams and assignments are necessary to assess learning; bad grades are undesirable for both sides.
    • Collaboration vs copying: groups may discuss solutions, but submitted work must be original unless otherwise specified; originality helps detect plagiarism.
    • AI usage: AI tools like GPT or Copilot may be used with acknowledgement; the instructor will guide productive use and proper attribution.
    • Encouragement to seek help: students should ask questions until satisfied; ample opportunities for clarification via office hours or in-class questions.

  • Faculty and student life: meet the faculty panels

    • The course features panels with department faculty to discuss areas of expertise, ongoing research, and course offerings.
    • Purpose: help students understand the department’s strengths and potential future research/career paths.
    • Key contacts: Alyssa (department navigation and services; coffee hours), Sean Kane (lab manager; lab access, TA/RA opportunities, purchasing), Netty (Linux sysadmin; IT support), Lourdes Douglas (Graduate program, scheduling, events, open houses).
    • Office locations and walk-bys: students are encouraged to visit during office hours or informal walking conversations.
    • Coffee hours and donuts: biannual social events to meet faculty, upperclassmen, and peers.

  • Department structure and cross-school collaboration

    • Shared foundations: CMP 110 is designed so Computer Engineering students take the same CS-1 and CS-2 sequence as Computer Science students.
    • Shared hardware foundations: Circuits courses are shared with Electrical Engineering to ensure a similar strength in circuit design.
    • Resulting breadth and versatility: enables students to pivot toward CS or EE strengths as they advance.

  • Course content access and organization

    • Course materials are organized in a digital repository with folders for: syllabus, lab exercises, helpful resources, lectures, homeworks, etc.
    • Syllabus highlights: academic honesty, use of AI tools, tentative weekly schedule, security and lab access, and expectations for online systems.
    • Academic honesty policy: groups may discuss problems, but submitted work must be original; plagiarism policies are strongly enforced and can affect records for years.
    • AI policy: use AI tools with proper attribution; instructors may provide guidance on appropriate use.
    • Weekly schedule and lab/mentoring rhythm: weeks alternate between lab work and mentoring sessions; mentoring focuses on awareness of department and major navigation, not experiments.
    • Assessment structure: no midterm or final exam in CMP 110; majority of grade comes from labs, homework, and a final project lasting 3–4 weeks.
    • Accommodations: DSO-accommodated adjustments are recognized; extended time for graded activities or alternate arrangements can be provided.
    • Accessibility and seating: reserved seating policies; options to sit where students can best hear and see; instructors accommodate accessibility needs.
    • MyCourses and Starfish: MyCourses hosts course materials, assignments, and communication; Starfish provides early alerts for attendance and performance.
    • Class sections and grading: lecture and lab sections exist (e.g., 110.0one for lecture, 110.01 for lab); labs remain separate for grading, but assignments are posted in the lecture section to streamline access.

  • Problem-solving mindset and what engineers do

    • What is a computer? A device that processes information faster than humans, can store and transmit information, and can communicate with other devices.
    • The three-tier stack in computing:
    • Hardware: low-level circuitry; transistors; circuits; hardware systems.
    • Low-level system software: assemblers and operating systems.
    • Host applications: software that enables human interaction with the computer.
    • What is an engineer? A problem solver who is a critical thinker, persistent, dedicated, efficient, and capable of delivering practical solutions.
    • Engineer vs scientist: scientists discover existing phenomena; engineers create new things, devices, concepts to solve problems; boundaries are blurred in practice.
    • Problem definition workflow:
    • Step 1: Identify stakeholders and the problem.
    • Step 2: Define the problem in engineering terms with measurable metrics; if you cannot measure it, you cannot improve it.
    • Large-scale brainstorming exercise (global challenges): groups discuss big problems to solve (e.g., health improvements, sustainable data centers, faster transportation, clean energy, fusion energy).
    • Report-back and reflection prompts: how would computing help enable teleportation; how does knowledge in computer engineering contribute to solving these problems?
    • Essential computing engineer competencies: technical knowledge; analytical ability; practical problem-domain knowledge; professional communication; teamwork; awareness of global/ethical issues; adaptability and flexibility to pivot when needed.

  • Industry context, accreditation, and career pathways

    • Accreditation: BS degree is accredited on a six-year cycle; the program is rated among the highest in the country; reflects quality and ongoing evaluation.
    • Co-ops: mandatory component totaling about 48 weeks of work experience.
    • Graduate pathways: MS in Electrical and Computer Engineering; dual BS/MS programs; accelerated paths for high-achieving students (GPA > 3.4 after fall of year 2, eligibility for accelerated program).
    • PhD opportunities: available in Electrical and Computer Engineering.
    • Core and follow-on courses (quick cognition of the program stack):
    • Digital systems
    • Assembly language
    • Computer organization
    • Computer architecture (follow-up to organization; discusses instructions and architecture and how the computer operates at a hardware/software interface)
    • Employers hiring CMP 110 graduates: Amazon, Apple, AMD, Lockheed Martin, L3 Harris, Sparta, and a range of smaller firms.
    • Perspective on data centers and power: data centers are extremely power-hungry; 10–100 MW range; a single megawatt equals 10^6 watts; a hundred megawatts roughly equals powering about 100 city blocks; data centers can include integrated power generation plants; power consumption translates directly into environmental and economic considerations.
    • Data-scale comparison: data centers (kilometer-scale) vs CPU chips (centimeter-scale); orders of magnitude difference illustrated to emphasize breadth of computer engineering—from millimeter-scale CPUs to kilometer-scale data centers.

  • Quantitative insights and examples (with LaTeX-ready expressions)

    • Power and units:
    • 1 W = 1 J/s
    • 1 MW = 10^6 W
    • A data center power consumption estimate: between
      10×106 extW10\times 10^6\ ext{W} and 100×106 W100\times 10^6\ \text{W}
    • Intuition: 1 MW is roughly the power needed for a small town block; 100 MW is roughly 100 city blocks of power usage.
    • Data center vs CPU scale:
    • Data center footprint: roughly a kilometer scale; typical width/length on the order of hundreds of meters.
    • CPU chip: roughly 10 mm by 10 mm; a quad-core processor with visible cores (blue-green blocks) in the center.
    • Length scales across computer engineering:
    • From millimeter to kilometer: about six orders of magnitude difference in linear dimension (i.e., from 10^-3 m to 10^3 m, difference factor of 10^6).
    • CPU architecture example: quad-core processor with multiple cores arranged around a central computing core network; illustrates hardware organization.

  • Practical implications and real-world relevance

    • The environmental footprint of digital activity: every online interaction has power costs; understanding power vs energy helps engineers design more efficient systems.
    • The value of soft skills: engineering success depends not only on technical chops but also on effective teamwork, documentation, and professional communication.
    • Career planning: awareness of co-op requirements, graduate pathways, and employer landscapes helps students map a practical path through the program.
    • Ethical and professional responsibility: engineers must consider societal impact, global context, and responsible conduct in both technical work and team interactions.

  • Summary of core ideas from the orientation

    • CMP 110 introduces the breadth of computer engineering, emphasizes the importance of soft skills, and sets expectations for a collaborative, inquiry-driven learning environment.
    • The program is designed to lay a foundation across CS and EE areas, preparing students for a broad range of future courses and career paths.
    • Students should engage actively, leverage office hours, and use the department resources to navigate the program and maximize learning outcomes.

  • Quick practical checklist for week 1–2

    • Bring a laptop to class for activities; ensure access to MyCourses and the syllabus.
    • Read the syllabus with emphasis on academic honesty, AI usage policy, and the tentative weekly schedule.
    • Familiarize with MyCourses, Starfish, and the grade roster systems; understand how labs and lectures are organized.
    • Note the absence of a midterm/final exam; expect grades primarily from labs, homeworks, and the final mini-project.
    • Identify your advisor (Ken or Corina) and plan your first advising meeting.
    • Attend “Meet the Faculty” panels to learn about areas of expertise and possible research opportunities.
    • If you need accommodations, contact the DSO and arrange suitable arrangements.

  • Final reflection prompts for study planning

    • How can you leverage your strengths (curiosity, creativity, value creation) in computer engineering projects?
    • Which future courses align with your interests, and how can CMP 110 help you prepare to pursue them?
    • What is one measurable problem you would like to solve, and how could computing contribute to solving it? Consider stakeholders and metrics.