CSCI 3753: Operating Systems Programming Assignment Four

CSCI 3753: Operating Systems
Fall 2016
Programming Assignment Four
Due Date and Time: 11:55 PM, Monday, November 14, 2016
1 Assignment Introduction
The goal of this assignment is to spend some time investigating the behavior of the Linux
scheduler. You will create a set of benchmarks and run them under a variety of Linux
scheduling polices. You will then use the data from these benchmarks to draw some conclusions
about the differences between various Linux scheduler polices. You will submit a
report explaining your conclusions and showing your supporting data.
You may complete this assignment on the course VM or your own native Linux installation.
You will not be able to complete this lab directly on the CU CSEL or elra machines as
you will require root access in order to utilize certain scheduler policies. You will probably
get the most reliable data off of a personal, native Linux install with few other programs
running simultaneously. Whatever environment you choose to use must be used consistently
throughout this assignment. Switching environments part way through the assignment will
make it difficult, if not impossible, to accurately compare and contrast your data. Be sure
to document your environment in your report.
2 The Linux Scheduler
The current implementation of the Linux Scheduler has existed since kernel version 2.6.23
when the Completely Fair Scheduler (CFS) was added to the mainline Linux kernel [7, 1, 5].
Prior to kernel version 2.6.23, Linux used the O(1) scheduler [6]. This assignment will focus
on the current scheduler implementation.
The addition of the CFS scheduler to the Linux kernel brought with it a more modular
scheduler implementation. The scheduler is implemented as a core unit (kernel/sched.c)
that implements the core scheduler behavior and a series of scheduler class modules that
implement specific scheduling policies. Currently, the kernel contains two of these scheduler
classes: The CFS class (kernel/sched fair.c) and the Real Time (RT) class (kernel/sched rt.c).
These classes are organized hierarchically, with the RT class taking precedence over the CFS
class. The scheduler core attempts to schedule all runnable jobs from each class before
moving on to the next class in the hierarchy.
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RT
CFS
Highest
Priority
Lowest
Priority
Includes:
SCHED_RR
SCHED_FIFO
Includes:
SCHED_OTHER (SCHED_NORMAL)
SCHED_BATCH
SCHED_IDLE
kernel/sched_rt.c
kernel/sched_fair.c
Class Policy
Figure 1: Linux Scheduling Classes and Policies
Each scheduler class implements one or more scheduler policies. Each policy controls
the scheduling behavior of all system processes assigned to it. The RT class currently provides
implementations of the POSIX SCHED RR and SCHED FIFO policies. The CFS
class currently provides implementations of the SCHED OTHER (aka SCHED NORMAL),
SCHED BATCH, and SCHED IDLE policies. The default policy is SCHED OTHER. Polices
within a given class may or may not possess a hierarchical relationship. It is up to each
class to determine how it handles any policies it implements. See Figure 1.
In Linux, each processor has its own run queue structure. Originally this structure was a
single queue that maintained a list of processes for each processor to run (hence the name “run
queue”). Today, this structure actually contains a collection of sub-structures (or pointers to
sub-structures), where each sub-structure corresponds to the necessary data structure(s) for
each scheduling class. Since Linux currently has two scheduling classes, CFS and RT, each
run queue structure contains a pointer to a CFS run queue structure and a RT run queue
structure. These run queue structures are managed by their respective scheduling classes.
Also, note that although we still use the phrase “run queue” many of these structures are
no longer actually queues. For instance, the CFS class uses a Red-Black Tree as its so called
“run queue”. We will use the term “run queue” in this assingnment to refer to any data
structure that a class uses to organize or derive a scheduling order for a set of processes.
In a Linux SMP multiprocessor installation there is one set of run queue structures per
processor (or core). This means there must also be a load balancing system to move tasks
from one run queue to another. Like the rest of the scheduling system, load balancing
is handled separately by each scheduling class. Figure 2 provides an illustration of the
organization of the scheduling system.
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Figure 2: Linux Scheduler Overview [6]
The scheduler core is coordinated by a series of regular, frequent ticks. At eEach tick,
the scheduler attempts to find a runnable process for each available core on each available
processor. As mentioned previously, the scheduler accepts processes from each class in order
of the class hierarchy. The scheduler core calls a function hook in each scheduler class called
pick next task, passing this function a copy of the run queue structure corresponding to the
processor currently being scheduled. Each scheduler class then accesses its corresponding
sub-structure within the run queue structure and performs the necessary computation to
arrive at the appropriate next task. It then passes a pointer to the task struct for this
task back to the scheduler core for running. If a class has no runnable process, it returns a
NULL pointer and the scheduler moves on to the next class in the hierarchy.
Scheduler polices are used within each class to indicate a desired scheduling behavior. By
convention, if multiple polices can share a run queue data structure, they are implemented
in the same class. The default policy, SCHED OTHER (also called SCHED NORM) corresponds
to the standard CFS time-sharing scheduling parameters. The two RT policies, SCHED FIFO
and SCHED RR implement real-time first-in-first-out and real-time round-robin scheduling
policies, respectively. It should be noted that the “real-time” policies in Linux are soft realtime
polices, as Linux is not a hard real-time operating system. This means that Linux will
make a best effort to adhere to real-time scheduling rules for these policies, but can not
guarantee it. Each task assigned to a RT policy must be given a scheduling priority. These
priorities dictate the ordering of tasks in the real-time run queue. The CFS class does not
use user-supplied scheduling priorities.
The foregoing is mostly a review of topics from lecture and Chapters 6 and 18 of the
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textbook. The main points to keep in mind are that RT classes (RR and FIFO) are scheduled
with higher priority than the timeshare class (OTHER or NORM).
3 Process Types
In general, we speak of processes as being either compute bound or I/O bound. A compute
bound (aka CPU bound) process is a process that primarily requires use of the CPU in order
to complete. The speed and availability of the CPU is the limiting factor determining the
run time of such a process.
An I/O bound process, on the other hand, is a process that primary relies on completing
I/O requests (hard disk, user input, etc) in order to complete. The run time of an I/O
bound process is primary determined by the amount of time it must spend waiting for I/O
resources to become available.
In reality, most programs lie somewhere in between these two extremes. But it is helpful
to consider these extremes when analyzing the speed and behavior of a process.
4 Your Task
This project requires you to complete the following three items:
• Design a series of benchmarks to evaluate the behavior of several scheduling polices in
the Linux scheduler.
• Run your benchmarks and analyze the resulting data to draw conclusions about the
behavior of the tested policies.
• Write a report explaining your conclusions and supporting data.
Each item is discussed in detail below.
4.1 Create Benchmarks
You will need to benchmark and analyze the behavior of the following three Linux Scheduling
policies:
• SCHED OTHER (aka SCHED NORM)
• SCHED FIFO
• SCHED RR
You will need to investigate the impact of priorities/nice values on the scheduling performance:
• Priorities and nice values of all processes are the same.
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• There is a combination of priorities and nice values, i.e. some processes have higher
priorities while other have lower priorities in a single run, and similarly, some processes
have higher nice values while other have lower values in a single run.
You will need to compare the behavior of these polices across the following three representative
process types:
• Compute (CPU) Bound
• I/O Bound
• Mixed
Additionally, you will need to investigate how the behavior of each process type under
each scheduling policy scales across the following three levels of system utilization:
• Low (5 to 10 simultaneous process instances)
• Medium (10s of simultaneous process instances)
• High (100s of simultaneous process instances)
4.2 Run and Analyze
The four testing vectors mentioned above give rise to 54 possible test cases (every possible
combination of each of the three elements from each of the three vectors). You will need to
gather data for all 54 of these cases. You should probably also repeat each test case a few
times and average the results over this set of runs. This will help insure that you are getting
good data and will minimize the effect of spurious events.
Once you have gathered all of your data, you will need to analyze it to answer the
following questions:
• Which scheduling policy is best suited for each process type in terms of run-time and
overhead efficiency? Why? If there is not a clear winner, why not?
• How does each scheduling policy scale? Why?
• What are some pros and cons of each scheduling policy?
• Provide an example of an instance for which each scheduling policy is well suited.
• Provide an example of an instance for which each scheduling policy is not well suited.
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4.3 Report
Write a report that explains how you gathered your data, what your data show, and why
you believe you obtained the results that you did. Work the answers to the above questions
into your report. The questions need not be answered directly, but the reader should be able
to answer all of the questions posed above after reading your report.
Your report must include the following section:
• Abstract - A single paragraph overview of your work and conclusions
• Introduction - An overview of your work
• Method (or Experimental Design) - An explanation of how your benchmarks work and
what they test for. You should also describe your test system and setup.
• Results - Summary of your results (possibly with graphs)
• Analysis - Explanation of your results and what they indicate
• Conclusion - What you learned from your results
• References - Any external resources you consulted
• Appendix A - Raw Data
• Appendix B - All Code
The report should be no longer than necessary to effectively convey your meaning. Excluding
the Appendices, 10 pages would seem a reasonable upper limit, but adjust as necessary.
The report should be written in active, first person English and should adhere to the
standards of good writing [9, 2]. References may be in any format you chose, as long as they
convey the point.
Assume that your audience is educated in the subject (i.e. the course TAs, CAs or
professor). Thus, you need not dwell on background information. Concentrate on explaining
the unique properties of your work (your benchmark implementation, etc), your results, and
your conclusions.
5 Some Implementation Ideas
There are a variety of ways you could meet the requirements of the assignment listed in the
previous section. Here we provide suggestions for a few possible ways.
5.1 Create Test Programs
To create test programs for the three required process types, write a simple C program
implementing each. For example, the compute bound program might involve calculating pi
to the nth digit or generating a pseudo-random number. Algorithms for these and other
CPU heavy tasks can be found online and in reference texts.
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To create an I/O bound program, consider writing a program that writes B bytes to a
file, and then reads the B bytes back from the file, repeating N times. You may need to pick
B and N such that you can overcome the caching effects of the system in order to get the
best data. The Linux /dev/null and /dev/urandom files may come in handy if you wish to
throw data away or read random data. Be wary of accessing a common file in your program,
as you will need to be able to run multiple copies of your program simultaneously to get
accurate benchmark results. If your program must read in or write out to a file, it would be
best to create a separate input/output file for each instance of your program.
For a mixed program, combine the previous ideas. For example, carry out a computationally
heavy step in an algorithm, write the intermediate result to a file, and then repeat
N times.
Once you have your three programs implementing the three process types, modify the
program so that it spawns N instances of itself. You will need to utlize the fork system
call in order to spawn additional programs. You should probably structure the program
to maintain a single parent process that spawns and monitors all children. Your children
processes will then carry out the necessary work for the given test program as discussed
above. You will need to make sure that your parent process waits on each child to insure
they are properly reaped, avoiding zombie processes. This becomes especially important
when you start gathering data, as you will not be able to properly collect performance
metrics from zombie processes.
In order to set the scheduling policy for a process, you will need to use the sched setscheduler
system call. If called at the start of each of your test programs, the appropriate scheduling
policy will be inherited by any forked children within the program. You must pass
sched setscheduler a priority level when you call it. The SCHED OTHER priority should
always be 0. SCHED RR and SCHED FIFO should have priorities greater than 0.
You should experiment with a combination of priorities for SCHED RR and SCHED FIFO,
and for SCHED RR, you should also report the value of the time slice used for each priority.
You may use the sched get priority max function to find the max priority a given schedule
policy supports. In addition, the RT scheduling polices can only be run by a privileged
user. Thus, you will need to use the sudo command to run any benchmark that uses a RT
scheduling policy. For SCHED OTHER, you should experiment with varying the nice values of
the processes. See nice( ) system call for details on how to do this.
Using the above steps, you can write a generalized version of each of the three necessary
test programs that takes as arguments the scheduler class, where the priorities/nice values
should be same or different, and the number of copies to spawn (and, if desired, some measure
of the amount of time, number of iterations, etc that it should run each copy). You could
then write a script that calls each program with the appropriate parameters to generate test
runs across the 54 different combinations of test values. Remember, the computer works for
you, not the other way around.
Note that you should wait for each specific test case to complete before starting the next.
You will adversely intertwine your results if you run multiple tests simultaneously. Also note
that you will need a minimum value of 5 to 10 simultaneous copies (children) of each test
program running simultaneously to get interesting results. If only a single instance (child)
of each test program is running at a time, all of the scheduling policies will behave in the
same manner since there is nothing to schedule.
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5.2 Measure Program Performance
The previous section focused on building benchmark programs, but does not include any info
on actually gathering data on the performance of these programs. Linux provides a number
of ways to collect metrics on a program’s performance. We discuss a few here.
The simplest means of collecting performance metrics is to use the Linux time command.
The GNU version of this command returns a wealth of data about a program, including the
system time, user time, real time, and number of context switches. All of this data can be
used to gain insights into the behavior of various scheduling classes. With proper scripting,
you can even automatically collect and average this data over several test runs of each test
case.
The upside to using time is that you may apply it directly to each of the test programs
you have built, without needing to modify any of the test code discussed above (except maybe
the top level script). The downside to using the time command is that you will only be able
to gather the total aggregate data for each test case. You will not be able to gain any insight
into the fine grain distribution of this data across each specific child instance. Assuming your
test program properly waits on any children that it spawns, the results returned by time
will be the sum of the results from the parent process and any descendants. You can use this
to compute the average resource usage of each test program child instance by dividing the
results by the number of instanced spawned in a given test case. This averaged data may
be fine for your purposes, or it may leave you needing finer grain data.
If you want to gather the same data that time can give you, but for each individual
child process instance, you can use the getrusage or wait4 system calls. Unlike time, these
function will need to be built directly into your test programs. They will, however allow
you to gather data on each individual child process as it finished and is reaped. If using
getrusage, you may have to setup the necessary signal handlers to insure it gets called each
time a child process exits. If using wait4, you can gather statistics on each child process as
it is reaped.
It may be wise to start by using the time command and to only add getrusage or wait4
if you feel you need it. Alternatively, if you are uncomfortable with a scripting language and
do not wish to record your results by hand, you could use getrusage or wait4 to collect
and process all necessary data inside a top level c program.
6 What You Must Provide
When you submit your assignment, you must provide the following as a single archive file:
• A copy of your report in pdf format
• A copy of all your test code
• A makefile that builds any necessary test code
• A README explaining how to build and run your code
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7 What’s Included
We provide some code to help you get started. Feel free to use it as a jumping off point
(appropriately cited).
1. pi.c The source code for a statistically-based pi calculator. Accepts as the first argument
the number of iterations to compute over. Example of a CPU bound process.
2. pi-sched.c Same as pi.c, but with the addition of the ability to select one of the following
three Linux scheduling policies: SCHED OTHER, SCHED RR, or SCHED FIFO.
Accepts a scheduling policy as the second argument. Note 1: Only privileged users can
utilize the RT SCHED RR and SCHED FIFO policies. Note 2: Neither pi or pi-sched
spawns multiple instances. This is functionality you will need to add if you wish to use
these programs as part of your test suite
3. testscript A simple bash script that runs and measures the performance of a single
instance of the pi-sched program across all three scheduling policies.
4. rw.c The source code for a simple program that copies N bytes in blocks of K bytes
from an input file to an output file. The program will read the input file multiple times
in order to generate the required number of N bytes when N is larger than the size of
the input file. Uses the low-level read and write system calls in the O SYNC mode to
minimize the effects of filesystem buffering and maximize I/O delays. Example of an
I/O bound process.
5. Makefile A GNU Make makefile to build all the code listed here.
6. README As the title so eloquently instructs: read it.
8 Extra Credit
There are a few options for receiving extra credit on this assignment. Completion of each
of the following will gain you the specified number of points. In no case will the maximum
score on this assignment exceed 110/100.
• Time slice variation: Extend your assignment by experimenting with different quantum
values for SCHED RR policy. Note that the method to change the value of the
quantum varies depending on the Linux version you are using. On traditional Linux,
the SCHED RR quantum is 0.1 seconds. Since Linux 3.9, the limit is adjustable via
the /proc/sys/kernel/sched rr timeslice ms file, where the quantum is expressed as a
millisecond value whose default is 100. Include your observations about the impact of
quantum size in your report. 10 Points
• BFS: The BFS is an alternative to the CFS. It is actively maintained as a set of
patches that can be found at http://ck.kolivas.org/patches/bfs/ [3, 4]. Patch
and recompile a copy of the Linux kernel that uses the BFS instead of the CFS. Run
all of the required test combinations in the BFS kernel, as well as in the CFS kernel
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(bringing your total test cases to 108). Compare the performance of the BFS and CFS
policy implementations in your report. 10 Points Bonus: Fame. If you do this well,
there may be a demand for your report online or in publication. There has been a lot
of speculation on the relative performance of CFS vs BFS but not much comprehensive
data to back it up.
• Visualization: Build or deploy a visualization system that will create visual representations
of how various scheduling polices schedule the different tasks. Your output
might look like the Gantt charts we have looked at in recitation and class. You will
probably have to use some form of process trace library to gather the necessary temporal
data. 10 Points
• Multi-Core: Investigate how the various scheduling polices scale with the number
of cores. You will essentially need to add core count as an additional test parameter
(multiplying the total number required test results in the process). Compare the
performance of the various scheduling policies on single, double, and quad or more
core machines and comment on the results in your report. A virtualized environment
would seem the best suited for this extension. 10 Points
9 Grading
40% of you grade will be based on the submission you provide. To received full credit your
submission must:
• Meet all requirements elicited in this document
• Code must build with “-Wall” and “-Wextra” enabled, producing no errors or warnings.
• Report must be well written and reasoned.
The other 60% of your grade will be determined via your grading interview where you will
be expected to explain your results and answer questions regarding them and any concepts
related to this assignment. This includes adhering to good coding style and writing practices.
10 Resources
Refer to your textbook and class notes on Moodle for an overview of OS scheduling policies
and implementations.
The Internet[8] is also a good resource for finding information related to solving this
assignment.
You may wish to consult the man pages for the following items, as they will be useful
and/or required to complete this assignment. Note that the first argument to the “man”
command is the chapter, insuring that you access the appropriate version of each man page.
See man man for more information.
• man 1 time
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• man 2 sched setscheduler
• man 2 sched get priority max
• man 2 getrusage
• man 2 ptrace
• man 2 fork
• man 2 wait
• man 2 wait4
• man 2 open
• man 2 close
• man 2 read
• man 2 write
• man 4 random
• man 4 null
• man 5 proc
• man 7 sched.h
References
[1] Jones, M. Tim. Inside the Linux 2.6 Completely Fair Scheduler. IBM developerWorks:
2009. Accessed 06/01/12. http://www.ibm.com/developerworks/linux/library/
l-completely-fair-scheduler/.
[2] Kernighan, Brian and Dennis, Ritchie. The C Programming Language. Second Edition:
2009. Prentice Hall: New Jersey.
[3] Kolivas, Con. BFS - The Brain Fuck Scheduler. 2009. Accessed 06/01/12. http:
//ck.kolivas.org/patches/bfs/sched-BFS.txt.
[4] Kolivas, Con. FAQS about BFS. v0.330: 2009. Accessed 06/01/12. http://ck.kolivas.
org/patches/bfs/bfs-faq.txt.
[5] Kumar, Avinesh. Multiprocessing with the Completely Fair Scheduler. IBM developerWorks:
2008. Accessed 06/01/12. http://www.ibm.com/developerworks/linux/
library/l-cfs/.
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[6] Le, Thang Minh. A Study on Linux Kernel Scheduler: version
2.6.32. 2009. Accessed 06/01/12. http://www.scribd.com/thangmle/d/
24111564-Project-Linux-Scheduler-2-6-32.
[7] Molnar, Ingo. This is the CFS scheduler. 2007. Accessed 06/01/12. http://people.
redhat.com/mingo/cfs-scheduler/sched-design-CFS.txt.
[8] Stevens, Ted. Speech on Net Neutrality Bill. 2006. http://youtu.be/f99PcP0aFNE.
[9] Strunk, William, Jr. and White, E.B. The Elements of Style. Fourth Edition: 2000.
Pearson: New York.
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