Click
here to see a PREVIEW of important rules
that was posted before the semester started.
This is an undergraduate course on computer operating systems.
(But -
**Instructor**Bill Cheng (click to see office hours) E-mail: <bill.cheng@usc.edu>.*(Please do***not**send HTML-only e-mails. They will not be read.)**DEN Section (29945D+29946D)****PM Section (30243D)****TT Section (30203D)****Time**MW 10:00am - 11:20am (NEW) MW 12:25pm - 1:45pm (NEW) TT 9:30am - 10:50am **Location**OHE 136 SGM 226 VHE 217 **TA**Ben Yan, E-mail: <wumoyan@usc.edu> Office Hours: Mon 3:00pm - 5:00pm in SAL 200Chien-Lun Chen, E-mail: <chienlun@usc.edu> Office Hours: Fri 1:30pm - 3:30pm in SAL 200Chien-Lun Chen, E-mail: <chienlun@usc.edu> Office Hours: Fri 1:30pm - 3:30pm in SAL 200**Course Producer**Chang Xu, E-mail: <cxu925@usc.edu>, Helpdesk Hours: Tue 1:00pm-3:00pm, Thu 1:00pm-3:00pm, Fri, 2:30pm-4:30pm in SAL student computer lab (SAL 125) **Graders**Parth Kapadia, E-mail: <pkapadia@usc.edu>
Deepa Sreekumar, E-mail: <dsreekum@usc.edu>
*(If needed, the grader will hold office hours the week after the announcement of each assignment's grades.)***Midterm Exam**during class time, Wed, 10/30/2019 *(firm)*during class time, Wed, 10/30/2019 *(firm)*during class time, Thu, 10/31/2019 *(firm)***Final Exam**8am-10am, Mon, 12/16/2019 *(firm)*.11am-1pm, Fri, 12/13/2019 *(firm)*.11am-1pm, Thu, 12/12/2019 *(firm)*.
Class Resources
(in reversed chronological order)
**12/16/2019:**- Below is the grade normalization information for kernel3.
Please note that this only applies to the
**grader-dependent**part of your grade. If you are graded by Parth Kapadia <pkapadia@usc.edu>, his kernel3 average was 84.45 with a standard deviation of 20.84. If you are graded by Deepa Sreekumar <dsreekum@usc.edu>, her kernel3 average was 79.40 with a standard deviation of 22.32. The overall class average for kernel3 was 82.42 with a standard deviation of 21.59.To figure out your normalized score for kernel3, here's what you can do. If your **grader-dependent**part of your grade is X and your grader's average is A with a standard deviation of D, then Y=(X-A)/D is the number of standard deviations away your score is from your grader's average. Therefore, your normalized**grader-dependent**part of your grade would be 82.42+Y*21.59 (i.e., same number of standard deviation away from the overall class average). Your minimum score is still one point if you have submitted something for grading.As I have mentioned in Lecture 1, although we assume that we have a bell-shaped curve, when your score is normalized, linear interpolation is used. It's clearly not perfect since the actual curve will never be bell-shaped and linear interpolation is not the same as bell-shaped-curve interpolation. But this is what was announced at the beginning of the semester, and therefore, we will stick to this particular way of normailzation for all the programming assignments for the rest of the semester, knowing that it's not perfect.
- Below is the grade normalization information for kernel3.
Please note that this only applies to the
**12/4/2019**: The final exam will be closed book, closed notes, and closed everything (and no "cheat sheet"). Also, no calculators, cell phones, or any electronic gadgets are allowed. Please bring a photo ID. Your ID will be collected at the beginning of the exam and will be returned to you when you turn in your exam. Please only go to the exam for the section you are registered. Also, no matter how late you show up for the exam, your exam must end at the same time as everyone else in your section. There will be assigned seating.The final exam will cover everything from slide 31 of Lecture 13 to slide 43 of Lecture 15 PLUS from slide 37 of Lecture 17 to the last slide of Lecture 30. Since the 2nd part of the course depends on stuff covered by the midterm, I cannot say that I will not ask anything covered by the midterm and you do need to know the material covered by the midterm. Therefore, it would be more appropriate to say that the final exam will **focus**on the material**not**covered by the midterm.Regarding what types of questions will be on the exam, please see the Exams section of the course description web page. Regarding regrade policy, please see the Regrade section of the course description web page. Please note that if you are asked to run the **Stride Scheduling**algorithm, to get any credit, you**must**run the algorithm described in Lecture 29 (and**not**the one in the textbook).Here is a quick summary of the final exam topics (not all topics covered may be listed): - Ch 3 - Basic Concepts
- shared libraries
- Ch 4 - Operating-System Design
- devices
- virtual machines, microkernels
- Ch 5 - Processor Management
- threads implementations
- interrupts
- scheduling
- Ch 6 - File Systems
- the basics of file systems
- performance improvements
- crash resiliency
- directories and naming
- RAID, flash memory, case studies
- Ch 7 - Memory Management
- virtual memory
- OS issues
- Kernel assignments 2 & 3
- spec
- FAQ
- my posts to class Google Group
- Ch 3 - Basic Concepts
**12/3/2019:**- The CP is not available this Thursday (12/5/2019) and Friday(12/6/2019) . Therefore, the helpdesk hours this Thursday and Friday are canceled.
**11/24/2019:**- Below is the grade normalization information for kernel2.
Please note that this only applies to the
**grader-dependent**part of your grade. If you are graded by Parth Kapadia <pkapadia@usc.edu>, his kernel2 average was 90.87 with a standard deviation of 9.90. If you are graded by Deepa Sreekumar <dsreekum@usc.edu>, her kernel2 average was 92.45 with a standard deviation of 12.31. The overall class average for kernel2 was 91.59 with a standard deviation of 11.09.To figure out your normalized score for kernel2, here's what you can do. If your **grader-dependent**part of your grade is X and your grader's average is A with a standard deviation of D, then Y=(X-A)/D is the number of standard deviations away your score is from your grader's average. Therefore, your normalized**grader-dependent**part of your grade would be 91.59+Y*11.09 (i.e., same number of standard deviation away from the overall class average). Your minimum score is still one point if you have submitted something for grading.As I have mentioned in Lecture 1, although we assume that we have a bell-shaped curve, when your score is normalized, linear interpolation is used. It's clearly not perfect since the actual curve will never be bell-shaped and linear interpolation is not the same as bell-shaped-curve interpolation. But this is what was announced at the beginning of the semester, and therefore, we will stick to this particular way of normailzation for all the programming assignments for the rest of the semester, knowing that it's not perfect.
- Below is the grade normalization information for kernel2.
Please note that this only applies to the
**11/14/2019:**- The CP is holding helpdesk hours in SAL 109D today.
**11/5/2019:**- The CP is holding helpdesk hours in SAL 109C today.
**11/4/2019:**- Below is the grade normalization information for kernel1.
Please note that this only applies to the
**grader-dependent**part of your grade. If you are graded by Parth Kapadia <pkapadia@usc.edu>, his kernel1 average was 88.37 with a standard deviation of 10.30. If you are graded by Deepa Sreekumar <dsreekum@usc.edu>, her kernel1 average was 88.96 with a standard deviation of 6.48. The overall class average for kernel1 was 88.68 with a standard deviation of 8.52.To figure out your normalized score for kernel1, here's what you can do. If your **grader-dependent**part of your grade is X and your grader's average is A with a standard deviation of D, then Y=(X-A)/D is the number of standard deviations away your score is from your grader's average. Therefore, your normalized**grader-dependent**part of your grade would be 88.68+Y*8.52 (i.e., same number of standard deviation away from the overall class average). Your minimum score is still one point if you have submitted something for grading.As I have mentioned in Lecture 1, although we assume that we have a bell-shaped curve, when your score is normalized, linear interpolation is used. It's clearly not perfect since the actual curve will never be bell-shaped and linear interpolation is not the same as bell-shaped-curve interpolation. But this is what was announced at the beginning of the semester, and therefore, we will stick to this particular way of normailzation for all the programming assignments for the rest of the semester, knowing that it's not perfect.
- Below is the grade normalization information for kernel1.
Please note that this only applies to the
**10/31/2019:**- The CP is holding helpdesk hours in SAL 109L today.
**10/30/2019:**- I'm cutting my office hour short tomorrow (Thursday) so I can go record a make-up lecture. It will go from 11am to 11:45am. Sorry about the inconvenience.
**10/29/2019:**- The CP will hold a make-up helpdesk hours tomorrow (Thursday) from 3:00pm to 5:30pm in SAL 125 (if there will be a location change, I will update it here).
**10/28/2019:**- The CP's helpdesk hours tomorrow (Tuesday) will go from 2:30pm to 6pm in SAL 125 (if there will be a location change, I will update it here).
**10/28/2019:**- A big fire broke out last night on the west side of LA.
I will stay home today in case we have to evacuate. So, I'm canceling all lectures today and tomorrow. Sorry about the short notice.
Since we are one lecture ahead of schedule this semester, we can simply shift the lecture schedule back to normal. I will have to record a lecture another time to make up for the missing lecture for Thanksgiving.
- A big fire broke out last night on the west side of LA.
I will stay home today in case we have to evacuate. So, I'm canceling all lectures today and tomorrow. Sorry about the short notice.
**10/22/2019:**- The Course Producer's helpdesk hours this Thursday and Friday (10/24 & 10/25) are canceled. He will make up the hours next week. Sorry about the inconvenience. I will hold an extra office hour this Friday from 11am to 12pm.
**10/21/2019:**- I'm moving my office hour this Thursday (10/24/2019) from 11am-noon to 3pm-4pm. Sorry about the inconvenience.
**10/20/2019:**- Below is the grade normalization information for warmup2.
Please note that this only applies to the
**grader-dependent**part of your grade. If you are graded by Parth Kapadia <pkapadia@usc.edu>, his warmup2 average was 79.76 with a standard deviation of 26.80. If you are graded by Deepa Sreekumar <dsreekum@usc.edu>, her warmup2 average was 71.60 with a standard deviation of 33.93. The overall class average for warmup2 was 75.18 with a standard deviation of 30.92.To figure out your normalized score for warmup2, here's what you can do. If your **grader-dependent**part of your grade is X and your grader's average is A with a standard deviation of D, then Y=(X-A)/D is the number of standard deviations away your score is from your grader's average. Therefore, your normalized**grader-dependent**part of your grade would be 75.18+Y*30.92 (i.e., same number of standard deviation away from the overall class average). Your minimum score is still one point if you have submitted something for grading.
- Below is the grade normalization information for warmup2.
Please note that this only applies to the
**10/16/2019**: The midterm exam will be closed book, closed notes, and closed everything (and no "cheat sheet"). Also, no calculators, cell phones, or any electronic gadgets are allowed. Please bring a photo ID. Your ID will be collected at the beginning of the exam and will be returned to you when you turn in your exam. Please only go to the exam for the section in which you are**registered**. Also, no matter how late you show up for the exam, your exam must end at the same time as everyone else in your section. There will be assigned seating.The midterm exam will cover everything from the beginning of the semester to slide 22 of Lecture 17 on 10/16,17/2019, MINUS Chapter 5 (i.e., material in Ch 5 is **excluded**from the midterm).Regarding what types of questions will be on the midterm, please see the Exams section of the course description web page and slides 26 through 36 of Lecture 17 on 10/16,17/2019. Regarding regrade policy, please see the Regrade section of the course description web page. Here is a quick summary of the midterm exam topics (not all topics covered may be listed): - Ch 1 - Introduction
- introduction
- a simple OS
- files
- Ch 2 - Multithreaded Programming
- thread creation, termination
- thread synchronization
- thread safety, deviations
- Ch 3 - Basic Concepts
- context switching, I/O
- dynamic storage allocation
- static linking and loading
- booting
- Ch 4 - Operating-System Design
- a simple system
- storage management
- Warmup assignments 1 & 2
- specs
- FAQs
- my posts to class Google Group
- Kernel assignment 1
- spec
- FAQ
- my posts to class Google Group
Please note that kernel 1 is included in the midterm coverage but Chaper 5 is not. This mean that I can ask `weenix`-specific questions.- Ch 1 - Introduction
**10/16/2019:**- Please read the message I posted in the class Google group about the cancellation of the PM section lecture today and that I'm holding office hour starting at 11:30am today for at least half an hour. If no student is waiting to see me at noon, I will leave campus. Everyone will get rollsheet signing credit for today and tomorrow's lectures. Sorry about the short notice and inconvenience.
**10/15/2019:**- Since some students missed the CP's helpdesk hours today because they couldn't find him, he will have an extra helpdesk hour tomorrow (Wednesday) from 3pm to 5pm. If he moves location, he will post to the class Google group. (Please also note that during the Fall recess, there will be no lectures, no discussion sections, no office hours, and no helpdesk hours.)
**10/15/2019:**- I'm very sorry that I have to cancel office hour (but not lecture) today because I need to go to a doctor's appointment. Sorry about the short notice and inconvenience.
**9/25/2019:**- The CP's helpdesk hours tomorrow (Thursday, 9/26) has been moved to 6-8pm (originally 1-3pm).
**9/22/2019:**- Below is the grade normalization information for warmup1.
Please note that this only applies to the
**grader-dependent**part of your grade. If you are graded by Parth Kapadia <pkapadia@usc.edu>, his warmup1 average was 84.63 with a standard deviation of 24.36. If you are graded by Deepa Sreekumar <dsreekum@usc.edu>, her warmup1 average was 90.32 with a standard deviation of 16.92. The overall class average for warmup1 was 87.48 with a standard deviation of 21.17.To figure out your normalized score for warmup1, here's what you can do. If your **grader-dependent**part of your grade is X and your grader's average is A with a standard deviation of D, then Y=(X-A)/D is the number of standard deviations away your score is from your grader's average. Therefore, your normalized**grader-dependent**part of your grade would be 87.48+Y*21.17 (i.e., same number of standard deviation away from the overall class average). Your minimum score is still one point if you have submitted something for grading.
- Below is the grade normalization information for warmup1.
Please note that this only applies to the
**8/6/2019:**- Watch this area for important announcements.
- To get
**user ID**and**password**for accessing protected area of this web site, please visit the request access page**after semester starts**and submit the requested information. (You do not have to be registered for the course to get the password. You just need to have an USC e-mail address.) - Please do
**not**send request to join the class Google Group until**after**the Lecture 1.
- Watch this area for important announcements.
In the official syllabus, it is listed that the prerequisites are:
(CSCI 201L or CSCI 455x)Apparently, they are the prerequisites for undergraduate students only.
The CS department would waive these prerequisites for graduate students.
Since undergraduate students are required to take CS 350 for OS credit,
there should only be graduate students enrolled in CS 402. Therefore,
these prerequisites are really not prerequisites.
They should be considered recommended preparation for graduate students.
The basic idea behind these prerequisites is that you are expected to know
how to program and you are expected to know something about computer architecture
(such as what the CPU does).
The programming assignments of this class will be very demanding.
You will be required to write
C code. Since C is
a proper subset of C++, knowing C++ well would give you enough
background. However, some of the things that available in C++,
such as strings and streams, are not be available in C. So, you need
to know how to do things such as
manipulating null-terminated array of characters
(using functions such as strchr, strrchr, strlen, strcmp, strncpy, etc.)
and performing console and file I/O
(using functions such as printf/snprintf, fread/fwrite, read/write, fgets, etc.)
in C.
No other programming language will be accepted.
We will not teach C in this class.
You are expected to pick up C on your own if you are not familiar with it.
You should also get familiar with the Unix
development environment (vi/pico/emacs, cc/gcc, make, etc.)
You are expected to know how to use Unix.
If you are not familiar with Unix,
please read Unix for the Beginning Mage,
a tutorial written by Joe Topjian.
You can also visit UNIX Tutorial for Beginners
or Learn
The
These days, I have been using VagrantBox (i.e., Vagrant with Virtualbox)
to install and run Ubuntu 16.04.
I think it has a better integration with Windows 10 than other systems.
The down side is that
If a student |
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