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Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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14
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Course Overview
15-213/18-213/15-513/14-513/18-613: Introduction to Computer Systems
1st Lecture, Sept 1, 2020
Instructors:
Brandon Lucia Brian Railing
Phil Gibbons David Varodayan
The course that gives CMU its “Zip”!
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Overview
Big Picture
▪ Course theme
▪ Five realities
▪ How the course fits into the CS/ECE/INI curriculum
Academic integrity
Logistics and Policies
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The Big Picture
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Course Theme:
(Systems) Knowledge is Power!
Systems Knowledge
▪ How hardware (processors, memories, disk drives, network infrastructure) plus software (operating systems, compilers, libraries, network protocols) combine to support the execution of application programs
▪ How you as a programmer can best use these resources
Useful outcomes from taking 213/513/613 ▪ Become more effective programmers
▪ Able to find and eliminate bugs efficiently
▪ Able to understand and tune for program performance ▪ Prepare for later “systems” classes in CS, ECE, INI, …
▪ Compilers, Operating Systems, Networks, Computer Architecture, Embedded Systems, Storage Systems, Computer Security, etc.
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It’s Important to Understand How Things Work
Why do I need to know this stuff?
▪ Abstraction is good, but don’t forget reality
Most CS courses emphasize abstraction ▪ (CE courses less so)
▪ Abstract data types
▪ Asymptotic analysis
These abstractions have limits
▪ Especially in the presence of bugs
▪ Need to understand details of underlying implementations
▪ Sometimes the abstract interfaces don’t provide the level of control or performance you need
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Great Reality #1:
Ints are not Integers, Floats are not Reals Example 1: Is x2 ≥ 0?
▪ Float’s: Yes!
▪ Int’s:
▪ 40000 * 40000 –> 1600000000 ▪ 50000 * 50000 –> ?
Example 2: Is (x + y) + z = x + (y + z)? ▪ Unsigned & Signed Int’s: Yes!
▪ Float’s:
▪ (1e20 + -1e20) + 3.14 –> 3.14
▪ 1e20 + (-1e20 + 3.14) –> ?? Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Computer Arithmetic
Does not generate random values
▪ Arithmetic operations have important mathematical properties
Cannot assume all “usual” mathematical properties ▪ Due to finiteness of representations
▪ Integer operations satisfy “ring” properties
▪ Commutativity, associativity, distributivity
▪ Floating point operations satisfy “ordering” properties
▪ Monotonicity, values of signs
Observation
▪ Need to understand which abstractions apply in which contexts
▪ Important issues for compiler writers and serious application programmers
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Great Reality #2:
You’ve Got to Know Assembly
Chances are, you’ll never write programs in assembly
▪ Compilers are much better & more patient than you are
But: Understanding assembly is key to machine-level execution model
▪ Behavior of programs in presence of bugs ▪ High-level language models break down
▪ Tuning program performance
▪ Understand optimizations done / not done by the compiler ▪ Understanding sources of program inefficiency
▪ Implementing system software
▪ Compiler has machine code as target
▪ Operating systems must manage process state
▪ Creating / fighting malware
▪ x86 assembly is the language of choice! Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Great Reality #3: Memory Matters
Random Access Memory Is an Unphysical Abstraction
Memory is not unbounded
▪ It must be allocated and managed
▪ Many applications are memory dominated
Memory referencing bugs especially pernicious ▪ Effects are distant in both time and space
Memory performance is not uniform
▪ Cache and virtual memory effects can greatly affect program performance
▪ Adapting program to characteristics of memory system can lead to major speed improvements
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Memory Referencing Bug Example
typedef struct {
int a[2];
double d;
} struct_t;
double fun(int i) {
volatile struct_t s;
s.d = 3.14;
s.a[i] = 1073741824; /* Possibly out of bounds */ return s.d;
}
fun(0) –> fun(1) –> fun(2) –> fun(3) –> fun(4) –> fun(5) –>
3.14
3.14 3.1399998664856 2.00000061035156 3.14
Segmentation fault
▪ Result is system specific
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Memory Referencing Bug Example
typedef struct {
int a[2];
double d;
} struct_t;
Explanation:
fun(0) –> fun(1) –> fun(2) –> fun(3) –> fun(4) –> fun(6) –>
6 5 4 3 2 1 0
3.14
3.14 3.1399998664856 2.00000061035156 3.14
Segmentation fault
Critical State
?
?
d7 … d4
d3 … d0
a[1]
a[0]
struct_t
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Location accessed by
fun(i)
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Memory Referencing Errors
C and C++ do not provide any memory protection ▪ Out of bounds array references
▪ Invalid pointer values ▪ Abuses of malloc/free
Can lead to nasty bugs
▪ Whether or not bug has any effect depends on system and compiler ▪ Action at a distance
▪ Corrupted object logically unrelated to one being accessed
▪ Effect of bug may be first observed long after it is generated
How can I deal with this?
▪ Program in Java, Ruby, Python, ML, …
▪ Understand what possible interactions may occur
▪ Use or develop tools to detect referencing errors (e.g. Valgrind)
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Great Reality #4: There’s more to performance than asymptotic complexity
Constant factors matter too!
And even exact op count does not predict performance
▪ Easily see 10:1 performance range depending on how code written
▪ Must optimize at multiple levels: algorithm, data representations, procedures, and loops
Must understand system to optimize performance
▪ How programs compiled and executed
▪ How to measure program performance and identify bottlenecks
▪ How to improve performance without destroying code modularity and
generality
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Memory System Performance Example
void copyij(int src[2048][2048],
int dst[2048][2048])
{
int i,j;
for (i = 0; i < 2048; i++)
for (j = 0; j < 2048; j++)
}
dst[i][j] = src[i][j];
4.3ms
81.8ms
void copyji(int src[2048][2048],
int dst[2048][2048])
{
int i,j;
for (j = 0; j < 2048; j++)
for (i = 0; i < 2048; i++)
}
2.0 GHz Intel Core i7 Haswell
Hierarchical memory organization
Performance depends on access patterns
▪ Including how step through multi-dimensional array Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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dst[i][j] = src[i][j];
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Why The Performance Differs
copyij
16000 14000 12000
10000 8000 6000
4000 2000 0
copyji
s1
s3
Stride (x8 bytes)
32k 128k
s5
s7
8m 32m
2m 512k
Size (bytes)
s9
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s11 128m
Read throughput (MB/s)
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Great Reality #5:
Computers do more than execute programs They need to get data in and out
▪ I/O system critical to program reliability and performance
They communicate with each other over networks ▪ Many system-level issues arise in presence of network
▪ Concurrent operations by autonomous processes ▪ Coping with unreliable media
▪ Cross platform compatibility
▪ Complex performance issues
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Course Perspective
Most Systems Courses are Builder-Centric ▪ Computer Architecture
▪ Design pipelined processor in Verilog ▪ Operating Systems
▪ Implement sample portions of operating system ▪ Compilers
▪ Write compiler for simple language ▪ Networking
▪ Implement and simulate network protocols
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Course Perspective (Cont.) Our Course is Programmer-Centric
▪ By knowing more about the underlying system, you can be more effective as a programmer
▪ Enable you to
▪ Write programs that are more reliable and efficient ▪ Incorporate features that require hooks into OS
– E.g., concurrency, signal handlers
▪ Cover material in this course that you won’t see elsewhere ▪ Not just a course for dedicated hackers
▪ We bring out the hidden hacker in everyone!
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Role within CS/ECE Curriculum
Foundation of Computer Systems Underlying principles for hardware, software, and networking
CS Systems
• 15-319
• 15-330
• 15-410
• 15-411
• 15-415
• 15-418
• 15-440
• 15-441
• 15-445
Cloud Computing Computer Security Operating Systems Compiler Design Database Applications Parallel Computing Distributed Systems Computer Networks Database Systems
ECE Systems
CS 122 Imperative
Programming
213/513 /613
• 18-349
• 18-349
• 18-441
• 18-447
• 18-452
• 18-451
Computer Security
Intro to Embedded Systems Computer Networks Computer Architecture Wireless Networking Cyberphysical Systems
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CS Graphics
• 15-462 Computer Graphics
• 15-463 Comp. Photography
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Systems Concentration
For CS undergrads (currently)
Take ~5 systems courses
Chance to learn about wide range of systems and systems issues
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Academic Integrity
Please pay close attention, especially if this is your first semester at CMU
Carefully review policy:
http://www.cs.cmu.edu/~213/academicintegrity.html
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Cheating/Plagiarism: Description
Unauthorized use of information
▪ Borrowing code: by copying, retyping, looking at a file
▪ Describing: verbal description of code from one person to another. ▪ Searching the Web for solutions
▪ Copying code from a previous course or online solution
▪ Reusing your code from a previous semester (here or elsewhere)
▪ Arrange meeting with instructor before reusing your old solutions
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Cheating/Plagiarism: Description (cont.)
Unauthorized supplying of information
▪ Providing copy: Giving a copy of a file to someone ▪ Providing access:
▪ Putting material in unprotected directory
▪ Putting material in unprotected code repository (e.g., Github)
– Or, letting protections expire ▪ Applies to this term and the future
▪ There is no statute of limitations for academic integrity violations
Collaborations beyond high-level, strategic advice
▪ Anything more than block diagram or a few words
▪ Code / pseudo-code is NOT high level
▪ Coaching, arranging blocks of allowed code is NOT high level ▪ Code-level debugging is NOT high level
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Cheating/Plagiarism: Description
What is NOT cheating?
▪ Explaining how to use systems or tools
▪ Helping others with high-level design issues
▪ High means very high ▪ Using code supplied by us
▪ Starter code, class examples
▪ Using code from the CS:APP web site
Attribution Requirements ▪ Starter code: No
▪ Other allowed code (course, CS:APP): Yes ▪ Indicate source, beginning and end
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Cheating: Consequences
Penalty for cheating:
▪ Best case: -100% for assignment
▪ You would be better off to turn in nothing
▪ Worst case: Removal from course with failing grade
▪ This is the default
▪ Permanent mark on your record
▪ Loss of respect by you, the instructors and your colleagues ▪ If you do cheat – come clean asap!
Detection of cheating:
▪ We have sophisticated tools for detecting code plagiarism
▪ In Fall 2015, 20 students were caught cheating and failed the course.
▪ Some were expelled from the University
▪ In January 2016, 11 students were penalized for cheating violations that occurred as far back as
Spring 2014.
▪ In May 2019, we gave an AIV to a student who took the course in Fall 2018 for unauthorized coaching of a Spring 2019 student. His grade was changed retroactively.
Don’t do it!
▪ Manage your time carefully
▪ Ask the staff for help when you get stuck
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Some Concrete Examples: This is Cheating:
▪ Searching the internet with the phrase 15-213, 15213, 213, 18213, malloclab, etc.
▪ That’s right, just entering it in a search engine
▪ Looking at someone’s code on the computer next to yours
▪ Giving your code to someone else, now or in the future
▪ Posting your code in a publicly accessible place on the Internet, now or in the future
▪ Hacking the course infrastructure
This is OK (and encouraged): ▪ Googling a man page for fputs
▪ Asking a friend for help with gdb (but not with your code)
▪ Asking a TA or course instructor for help, showing them your code, ... ▪ Using code examples from book (with attribution)
▪ Talking about a (high-level) approach to the lab with a classmate Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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How it Feels: Student and Instructor
Fred is desperate. He can’t get his code to work and the deadline is drawing near. In panic and frustration, he searches the web and finds a solution posted by a student at U. Oklahoma on Github. He carefully strips out the comments and inserts his own. He changes the names of the variables and functions. Phew! Got it done!
The course staff run checking tools that compare all submitted solutions to the solutions from this and other semesters, along with ones that are on the Web.
▪ Remember: We are as good at web searching as you are
Meanwhile, Fred has had an uneasy feeling: Will I get away with it? Why
does my conscience bother me?
Fred gets email from an instructor: “Please see me tomorrow at 9:30 am.”
▪ Fred does not sleep well that night Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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How it Feels: Student and Instructor (cont.)
The instructor feels frustrated. His job is to help students learn, not to be police. Every hour he spends looking at code for cheating is time that he cannot spend providing help to students. But, these cases can’t be overlooked
At the meeting:
▪ Instructor: “Explain why your code looks so much like the code on Github.”
▪ Fred: “Gee, I don’t know. I guess all solutions look pretty much alike.”
▪ Instructor: “I don’t believe you. I am going to file an academic integrity violation.”
▪ Fred will have the right to appeal, but the instructor does not need him to admit his guilt in order to penalize him.
Consequences
▪ Fred may (most likely) will be given a failing grade for the course
▪ Fred will be reported to the university
▪ A second AIV will lead to a disciplinary hearing
▪ Fred will go through the rest of his life carrying a burden of shame
▪ The instructor will experience a combination of betrayal and distress Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Why It’s a Big Deal
This material is best learned by doing
▪ Even though that can, at times, be difficult and frustrating
▪ Starting with a copy of a program and then tweaking it is very different from writing from scratch
▪ Planning, designing, organizing a program are important skills We are the gateway to other system courses
▪ Want to make sure everyone completing the course has mastered the material
Industry appreciates the value of this course
▪ We want to make sure anyone claiming to have taken the course is
prepared for the real world
Working in teams and collaboration is an important skill
▪ But only if team members have solid foundations
▪ This course is about foundations, not teamwork Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Version Control: Your Good Friend
We will be using Github Education ▪ Assignment distribution
▪ Your workspace
▪ Use your course account, rather than a personal Github account
Use as you should a version server ▪ Commit early and often
▪ Document your commits
▪ Missing GIT history can count against you
How we use it
▪ If we suspect academic integrity issues, we can see if commit history looks
reasonable.
▪ Steady, consistent, and sustained work ▪ It can serve as your character witness
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How to Avoid AIVs Start early
Don’t rely on marathon programming sessions
▪ Your brain works better in small bursts of activity
▪ Ideas / solutions will come to mind while you’re doing other things
Plan for stumbling blocks
▪ Assignment is harder than you expected
▪ Code doesn’t work
▪ Bugs hard to track down ▪ Life gets in the way
▪ Minor health issues
▪ Unanticipated events
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Logistics
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Instructors 15-213/18-213
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Brian Railing Brandon Lucia
David Varodayan Phil Gibbons 14-513 18-613
Brian Railing 15-513
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15-213/18-213, 14-513, 15-513, and 18-613
15-213/18-213
▪ Undergraduates
▪ Lectures on Zoom (1:30-2:50 pm ET), link on Canvas syllabus page
15-513
▪ CS Masters and other Masters students
▪ Watch recorded lectures (no in-class quizzes) or join in on Zoom
14-513
▪ INI Masters students
▪ Lectures on Zoom (11:40 am-1:00 pm ET), link on Canvas syllabus page
18-613
▪ ECE Masters Students
▪ Lectures on Zoom (11:40 am-1:00 pm ET), link on Canvas syllabus page
Alternate time for in-class quizzes (if you’re in an awkward timezone)
▪ Canvas quizzes will be reopened 1:00-1:30 am ET (approx. 12 hours after lecture)
Everything else is the same for all the courses Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Textbooks
Randal E. Bryant and David R. O’Hallaron,
▪ Computer Systems: A Programmer’s Perspective, Third Edition (CS:APP3e), Pearson, 2016
▪ http://csapp.cs.cmu.edu
▪ This book really matters for the course!
▪ How to solve labs
▪ Practice problems typical of exam problems
▪ Electronic editions available (Don’t get paperback version!)
▪ On reserve in Sorrells Library
Brian Kernighan and Dennis Ritchie,
▪ The C Programming Language, Second Edition, Prentice Hall, 1988 ▪ Still the best book about C, from the originators
▪ Even though it does not cover more recent extensions of C
▪ On reserve in Sorrells Library
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Course Components
Lectures
▪ Higher level concepts
▪ In-class quizzes (except 15-513) could tilt you to a higher grade if borderline
Labs (8)
▪ 1-2+ weeks each
▪ Provide in-depth understanding of an aspect of systems ▪ Programming and measurement
Written Assignments (best 10 of 12) ▪ Reinforce concepts
▪ You earn 1/3 of score by grading your peers’ work according to our rubric
▪ Due Wednesdays at 11:59pm ET with peer grades due the next Wednesday
Final Exam (No midterm!)
▪ Test your understanding of concepts & mathematical principles
▪ Covers content from the whole semester Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Recitations
Recitations for students in 15-213/18-213, 14-513, 18-613 (everyone except 15-513)
First recitation on Monday Sept 14
Please indicate your desire for in-person recitations
▪ Look out for the form on Piazza in the near future
▪ We don’t have the resources to offer all recitations in-person or hybrid
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Getting Help
Class Web pages:
▪ http://www.cs.cmu.edu/~213
▪ Complete schedule of lectures, exams, and assignments ▪ Copies of lectures, assignments, exams, solutions
▪ FAQ
Piazza
▪ Best place for questions about assignments
▪ By default, your posts will be private
▪ We will fill the FAQ and Piazza with answers to common questions
Canvas
▪ Zoom links
▪ In-class quizzes
▪ Written assignments
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Getting Help Email
▪ Send email to individual instructors or TAs only to schedule appointments
Office hours (starting date TBA)
▪ TAs: SMTWRF, tentatively 6:00–9:00pm (see course webpage for updates)
▪ Use online queue https://cmu.ohqueue.com
▪ You provide the zoom meeting link and TA comes to you ▪ Instructors: See course home page
Walk-in Tutoring
▪ Details TBA. Will put information on class webpage.
1:1 Appointments
▪ You can schedule 1:1 appointments with any of the teaching staff Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Policies: Lab Work groups
▪ You must work alone on all lab assignments
Handins
▪ Labs due at 11:59pm ET
▪ Electronic handins using Autolab (no exceptions!)
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Facilities
Labs will use the Intel Computer Systems Cluster
▪ The “shark machines”
▪ linux> ssh shark.ics.cs.cmu.edu
▪ 21 servers donated by Intel for 213/513/613 ▪ 10 student machines (for student logins) ▪ 1 head node (for instructor logins)
▪ 10 grading machines (for autograding)
▪ Each server: Intel Core i7: 8 Nehalem cores, 32 GB DRAM, RHEL 6.1 ▪ Rack-mounted in Gates machine room
▪ Login using your Andrew ID and password
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Timeliness
Grace days
▪ 5 grace days for the semester
▪ Limit of 0, 1, or 2 grace days per lab used automatically
▪ Covers scheduling crunch, out-of-town trips, illnesses, minor setbacks
Lateness penalties
▪ Once grace day(s) used up, get penalized 15% per day ▪ No handins later than 3 days after due date
Catastrophic events
▪ Major illness, death in family, …
▪ Formulate a plan (with your academic advisor) to get back on track
Advice
▪ Once you start running late, it’s really hard to catch up ▪ Try to save your grace days until the last few labs
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Policies: Grading Final Exams (30%)
Labs (50%): weighted according to effort
Written Assignments (20%): drop lowest 2 out of 12 ▪ 1/3 points for making a credible submission
▪ 1/3 points from average of the three scores assigned by the peer graders ▪ 1/3 points for completing the peer reviews with constructive feedback
Final grades based on a straight scale (90/80/70/60) with a small amount of curving
▪ Only upward
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Programs and Data
Topics
▪ Bit operations, arithmetic, assembly language programs
▪ Representation of C control and data structures ▪ Includes aspects of architecture and compilers
Assignments
▪ L0 (C programming Lab): Test/refresh your C programming abilities
▪ L1 (datalab): Manipulating bits
▪ L2 (bomblab): Defusing a binary bomb
▪ L3 (attacklab): The basics of code injection attacks
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The Memory Hierarchy
Topics
▪ Memory technology, memory hierarchy, caches, disks, locality ▪ Includes aspects of architecture and OS
Assignments
▪ L4 (cachelab): Building a cache simulator and optimizing for locality.
▪ Learn how to exploit locality in your programs.
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Virtual Memory
Topics
▪ Virtual memory, address translation, dynamic storage allocation ▪ Includes aspects of architecture and OS
Assignments
▪ L5 (malloclab): Writing your own malloc package
▪ Get a real feel for systems-level programming
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Exceptional Control Flow Topics
▪ Hardware exceptions, processes, process control, Unix signals, nonlocal jumps
▪ Includes aspects of compilers, OS, and architecture
Assignments
▪ L6 (tshlab): Writing your own Unix shell.
▪ A first introduction to concurrency
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Networking, and Concurrency
Topics
▪ High level and low-level I/O, network programming
▪ Internet services, Web servers
▪ concurrency, concurrent server design, threads
▪ I/O multiplexing with select
▪ Includes aspects of networking, OS, and architecture
Assignments
▪ L7 (proxylab): Writing your own Web proxy
▪ Learn network programming and more about concurrency and synchronization.
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Lab Rationale
Each lab has a well-defined goal such as solving a puzzle or winning a contest
Doing the lab should result in new skills and concepts
We try to use competition in a fun and healthy way
▪ Set a reasonable threshold for full credit
▪ Post intermediate results (anonymized) on Autolab scoreboard for glory!
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Autolab (https://autolab.andrew.cmu.edu)
Labs are provided by the CMU Autolab system ▪ Project page: http://autolab.andrew.cmu.edu
▪ Developed by CMU faculty and students
▪ Key ideas: Autograding and Scoreboards
▪ Autograding: Providing you with instant feedback.
▪ Scoreboards: Real-time, rank-ordered, and anonymous summary.
▪ Used by over 3,000 students each semester
With Autolab you can use your Web browser to:
▪ Download the lab materials
▪ Handin your code for autograding by the Autolab server
▪ View the class scoreboard
▪ View the complete history of your code handins, autograded results, instructor’s evaluations, and gradebook.
▪ View the TA annotations of your code for Style points. Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Autolab accounts
Students enrolled on Friday, Aug 28 have Autolab accounts
You must be enrolled to get an account ▪ Autolab is not tied in to the Hub’s rosters
▪ If you add in, sign up with Google form (check on Piazza)
▪ We will update the autolab accounts once a day, so check back in 24
hours.
For those who are waiting to add in, the first lab (C Programming Lab) is available on the Schedule page of the course Web site.
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Bootcamps
Bootcamp #1
▪ Linux & the Command Line
▪ Friday Sept 4 at 7:00-9:00pm ET (may finish in 1.5 hours)
Bootcamp #2
▪ GCC & Build Automation (makefiles)
▪ Wednesday Sept 9 at 7:00-9:00pm ET (may finish in 1.5 hours)
Bootcamp #3
▪ Debugging Fundamentals & GDB
▪ Friday Sept 11 at 7:00-9:00pm ET (may finish in 1.5 hours)
Bootcamps will be on zoom and will be recorded
More bootcamps to be announced for specific labs later
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Carnegie Mellon
Waitlist questions
15-213: Mary Widom (marwidom@cs.cmu.edu)
18-213: ECE Academic services (ece-asc@andrew.cmu.edu) 15-513: Mary Widom (marwidom@cs.cmu.edu)
14-513: INI Enrollment (ini-enrollment@andrew.cmu.edu) 18-613: ECE Academic services (ece-asc@andrew.cmu.edu)
Please don’t contact the instructors with waitlist questions.
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Carnegie Mellon
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Welcome and Enjoy!
Carnegie Mellon
Appendix: GitHub Classroom Example
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Carnegie Mellon
Git basics – create a project for your lab
Follow link from writeup in TPZ Use link to create a repo
Clone to your local machine
Commit often!
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Carnegie Mellon
Git basics – create a project for your lab
Follow link from writeup in TPZ Use link to create a repo
Clone to your local machine
Commit often!
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Carnegie Mellon
Git basics – create a project for your lab
Follow link from writeup in TPZ Use link to create a repo
Clone to your local machine
Commit often!
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
59
Carnegie Mellon
Git basics – create a project for your lab
Follow link from writeup in TPZ Use link to create a repo
Clone to your local machine
Commit often!
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Carnegie Mellon
Git basics – clone it to a working directory Clone into a directory with the proper permissions
git clone git@github.com:cmu15213s19/213s19-lab0- seth4618.git
cd 213s19-lab0-seth4618
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