Michigan EECS 370: Introduction to Computer Organization
EECS 370 covers how computers actually execute programs: assembly language, instruction set architecture, pipelining, caches, and virtual memory. It's a core requirement after EECS 280, with projects that include building a simulator and an assembler in C.
Fennie is independent and not affiliated with University of Michigan. This is an unofficial study guide.
What makes it hard
Pipelining and caches are the walls. The concepts are simple to state and brutally detailed to execute, and exam questions about hazards, stalls, and cache hit patterns demand exact bookkeeping. The projects are long C programs where a subtle indexing bug costs hours, and students who let project crunch eat exam prep get caught by the detail-dense midterms.
What you'll cover
- • Assembly language and ISAs
- • Datapath and control
- • Pipelining and hazards
- • Caches and memory hierarchy
- • Virtual memory
- • C programming for systems projects
The EECS 370 study guide
How to study for Michigan EECS 370, step by step.
- 1
Trace the pipeline by hand, cycle by cycle
Draw pipeline diagrams for instruction sequences and mark every stall and forward. Exams grade exact cycle bookkeeping, and the precision only comes from doing it on paper repeatedly.
- 2
Work cache problems until the arithmetic is boring
Index, tag, offset, hit, miss: cache questions are mechanical once the address-breakdown habit is automatic. Volume now buys back exam minutes later.
- 3
Start projects early and test incrementally
The simulator and assembler projects punish big-bang debugging. Build in small tested pieces, because finding an indexing bug in 500 untested lines is how weekends disappear.
- 4
Use old exams as the study spine
Past EECS 370 exams show exactly how pipelining and cache questions are framed. Work them timed and audit every miss down to the specific bookkeeping slip.
Today
Today's EECS 370 plan
What a Fennie Daily Plan looks like for EECS 370. Yours is built from your own syllabus and adapts every day to your deadlines and progress.
First plan free, no card required. Fennie is independent and unaffiliated with your school.
FAQ
Is EECS 370 hard at Michigan?
It's considered moderate-to-hard in the core, easier than 281 for most, but the exams demand exact detail on pipelining and caches, and the C projects are real time commitments. Students who keep cycle-level tracing skills sharp through the term find the exams fair.
How long do EECS 370 projects take?
Plan for 10-20 hours per project depending on your C comfort and debugging luck. Incremental testing is the variable you control. Students who build in small verified pieces spend dramatically less time lost in debugging.
What should I review before EECS 370?
C programming from EECS 280. Pointers, arrays, and bit manipulation get used immediately in projects. The architecture content is taught from scratch, but weak C turns every project into a double assignment.
More Michigan courses
EECS 183: Elementary Programming Concepts
EECS 183 is Michigan's intro programming course for students with little or no coding experience, taught in C++ and Python. It's the standard entry point into the CS sequence for students who aren't ready to jump straight into EECS 280, and it ends with an open-ended final team project.
EECS 280: Programming and Introductory Data Structures
EECS 280 is the second course in Michigan's CS sequence, covering C++ programming in depth: pointers, dynamic memory, container ADTs, polymorphism, and recursion. It's a prerequisite for nearly everything in the CS major and the course where Michigan students first hit serious multi-week projects.
EECS 281: Data Structures and Algorithms
EECS 281 is Michigan's data structures and algorithms course and the gateway to upper-level CS. Most 400-level EECS courses require it. It covers algorithm analysis, sorting, hashing, trees, graphs, and dynamic programming, with large C++ projects graded heavily on runtime performance.
EECS 203: Discrete Mathematics
EECS 203 is the discrete math requirement for the CS major, covering logic, proofs, set theory, combinatorics, graphs, and an introduction to algorithm analysis. It's typically taken alongside EECS 280, and together they form the gateway pair into the Michigan CS core.