CSC 4320/6320 Operating Systems Lecture 5 CPU Scheduling

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CSC 4320/6320Operating SystemsLecture 5
CPU Scheduling

• Saurav Karmakar

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Chapter 5 CPU Scheduling

• Basic Concepts
• Scheduling Criteria
• Scheduling Algorithms
• Thread Scheduling
• Multiple-Processor Scheduling
• Operating Systems Examples
• Algorithm Evaluation

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Objectives

• To introduce CPU scheduling, which is the basis
  for multiprogrammed operating systems
• To describe various CPU-scheduling algorithms
• To discuss evaluation criteria for selecting a
  CPU-scheduling algorithm for a particular system

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Basic Concepts

• Uniprocessor system ?one process may run at a
  time
• Objective of multiprogramming
• ?some process running at all
  times
• ? to maximize CPU
  utilization
• When one process has to wait, the operating
  system takes the CPU away from that process and
  gives the CPU to another process
• Almost all computer resources are scheduled
  before use

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CPU-I/O Burst Cycle

• Success of CPU scheduling follows
• Process execution ? CPUI/O Burst Cycle
• Consists of a cycle of CPU execution and I/O
  wait
• Basically While a process waits for I/O, CPU sits
  idle if no multiprogramming
• Instead the OS can give CPU to another process
• CPU burst distribution
• Distribution for frequency vs duration of CPU
  bursts.
• Exponential or hyperexpoinential in nature

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Alternating Sequence of CPU And I/O Bursts
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Histogram of CPU-burst Times
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CPU Scheduler

• Selects from among the processes in memory that
  are ready to execute, and allocates the CPU to
  one of them Short-term Scheduler
• The ready queue is not necessarily a FIFO queue
• CPU scheduling decisions may take place when a
  process
• 1. Switches from running to waiting state
• 2. Switches from running to ready state
• 3. Switches from waiting to ready
• Terminates
• Scheduling under 1 and 4 leaves us no choice
• But option 2 and 3 does.

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CPU Scheduler

• Nonpreemptive once the CPU has been allocated
  to a process, the process keeps the CPU until it
  releases the CPU either
• Scheduling under 1 and 4 is
  Nonpreemptive/Cooperative
• All other scheduling is Preemptive
• Preemptive Scheduling incurs some costs
• Access to shared data
• Effects on the design of operating system kernel
• Effects of interrupts

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Dispatcher

• Dispatcher module gives control of the CPU to the
  process selected by the short-term scheduler
  this involves
• Switching context
• Switching to user mode
• Jumping to the proper location in the user
  program to restart that program
• Dispatch latency time it takes for the
  dispatcher to stop one process and start another
  running

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First-Come, First-Served (FCFS) Scheduling

• Process Burst Time
• P1 24
• P2 3
• P3 3
• Suppose that the processes arrive in the order
  P1 , P2 , P3 The Gantt Chart for the schedule
  is
• Waiting time for P1 0 P2 24 P3 27
• Average waiting time (0 24 27)/3 17

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FCFS Scheduling (Cont)

• Suppose that the processes arrive in the order
• P2 , P3 , P1
• The Gantt chart for the schedule is
• Waiting time for P1 6 P2 0 P3 3
• Average waiting time (6 0 3)/3 3
• Much better than previous case
• So Average waiting time vary substantially if the
  burst time for processes vary Generally quite
  long.
• This is non-preemptive in nature ? troublesome
  for time sharing system

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CPU SCHEDULING
FCFS Algorithm
Process Arrival
Service Time Time 1
0 8 2 1 4
3 2 9 4 3 5
FCFS
P1
P2
P3
P4
0
8
12
21
26
Average wait ( (8-0) (12-1) (21-2) (26-3)
)/4 61/4 15.25
Residence Time at the CPU
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Shortest-Job-First (SJF) Scheduling

• Associate with each process the length of its
  next CPU burst.
• Using these lengths to schedule the process with
  the shortest time
• If two processes have the same length next CPU
  burst, FCFS scheduling is used to break the tie.
• Scheduling depends on the length of the next CPU
  burst(lower the better)
• SJF is optimal gives minimum average waiting
  time for a given set of processes
• Difficulty ?knowing the length of the next CPU
  request

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Shortest-Job-First (SJF) Scheduling
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Example of SJF

• Process Burst Time
• P1 6
• P2 8
• P3 7
• P4 3
• SJF scheduling chart
• Average waiting time (3 16 9 0) / 4 7
• By moving a short process before a long one, the
  waiting time of the short process decreases more
  than it increases the waiting time of the long
  process. Consequently, the average waiting time
  decreases.
• SJF scheduling is used frequently in long-term
  scheduling.

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Determining Length of Next CPU Burst

• How to implement it at short-term scheduler ?
• Can only estimate the length
• Can be done by using the length of previous CPU
  bursts, using exponential averaging

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Examples of Exponential Averaging

• ? 0
• ?n1 ?n
• Recent history does not count
• ? 1
• ?n1 ? tn
• Only the actual last CPU burst counts
• If we expand the formula, we get
• ?n1 ? tn(1 - ?)? tn -1
• (1 - ? )j ? tn -j
• (1 - ? )n 1 ?0
• Since both ? and (1 - ?) are less than or equal
  to 1, each successive term has less weight than
  its predecessor

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Prediction of the Length of the Next CPU Burst
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Preemptive SJF Algorithm
Shortest Remaining Time First Algorithm
Process Arrival Service
Time Time 1 0 8 2
1 4 3 2 9
4 3 5
Preemptive Shortest Job First
P2
P4
P1
P3
P1
0
5
10
26
1
17
Average wait ( (10-1) (1-1) (17-2) (5-3)
)/4 26/4 6.5
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Priority Scheduling

• SJF is a special case of the general priority
  schedule algorithm
• Priority ? inverse of the next CPU Burst
• A priority number (integer) is associated with
  each process
• The CPU is allocated to the process with the
  highest priority (smallest integer ? highest
  priority)
• Preemptive
• Nonpreemptive
• Problem ? Starvation low priority processes may
  never execute
• Solution ? Aging as time progresses increase
  the priority of the process

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Priority Scheduling

• Average Waiting Time (0161618)/5 8.2

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What about fairness ?

• What about it?
• Strict fixed-priority scheduling between queues
  is unfair (run highest, then next, etc)
• long running jobs may never get CPU
• In Multics, shut down machine, found 10-year-old
  job
• Must give long-running jobs a fraction of the CPU
  even when there are shorter jobs to run
• Tradeoff fairness gained by hurting avg response
  time!
• How to implement fairness?
• Could give each queue some fraction of the CPU
• What if one long-running job and 100
  short-running ones?
• Like express lanes in a supermarketsometimes
  express lanes get so long, get better service by
  going into one of the other lines

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Fair Share Scheduling

• Problems with priority-based systems
• Priorities are absolute no guarantees when
  multiple jobs with same priority
• No encapsulation and modularity
• Behavior of a system module is unpredictable a
  function of absolute priorities assigned to tasks
  in other modules
• Solution Fair-share scheduling
• ? Each job has a share some measure of its
  relative importance
• denotes users share of system
  resources as a fraction of the total
• usage of those resources
• ? e.g., if user As share is twice that of user
  B then, in the long term, A will receive twice
  as many resources as B
• Traditional implementations
• keep track of per-process CPU utilization (a
  running average)
• reprioritize processes to ensure that
  everyone is getting their share
• are slow!

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Lottery Scheduling

• Yet another alternative here.
• Give each job some number of lottery tickets
• On each time slice, randomly pick a winning
  ticket
• On average, CPU time is proportional to number of
  tickets given to each job
• How to assign tickets?
• To approximate SRTF, short running jobs get more,
  long running jobs get fewer
• To avoid starvation, every job gets at least one
  ticket (everyone makes progress)
• Advantage over strict priority scheduling
• behaves gracefully as load changes
• Adding or deleting a job affects all jobs
  proportionally, independent of how many tickets
  each job possesses

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Lottery Scheduling Example

• Assume short jobs get 10 tickets, long jobs get 1
  ticket

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Round Robin (RR)

• Designed specially for time sharing system.
• Each process gets a small unit of CPU time (time
  quantum), usually 10-100 milliseconds. After
  this time has elapsed, the process is preempted
  and added to the end of the ready queue.
• The ready queue generally is circular queue.
• Avg wait time is often long
• If there are n processes in the ready queue and
  the time quantum is q, then each process gets 1/n
  of the CPU time in chunks of at most q time units
  at once. No process waits more than (n-1)q time
  units.
• Performance
• q large ? FIFO
• q small ? q must be large with respect to context
  switch, otherwise overhead is too high
  processor sharing

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Example of RR with Time Quantum 4

• Process Burst Time
• P1 24
• P2 3
• P3 3
• The Gantt chart is
• Avg Waiting Time ((10-4)47)/3 5.66
• Typically, higher average turnaround than SJF,
  but no better response

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Time Quantum and Context Switch Time
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Turnaround Time Varies With The Time Quantum
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Multilevel Queue

• Ready queue is partitioned into
• separate queues foreground (interactive) backg
  round (batch)
• Each queue has its own scheduling algorithm
• foreground RR
• background FCFS
• Scheduling must be done between the queues
• Fixed priority scheduling (i.e., serve all from
  foreground then from background). Possibility of
  starvation.
• Time slice each queue gets a certain amount of
  CPU time which it can schedule amongst its
  processes i.e., 80 to foreground in RR 20 to
  background in FCFS

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Multilevel Feedback Queue

• A process can move between the various queues
  aging can be implemented this way
• Multilevel-feedback-queue scheduler defined by
  the following parameters
• number of queues
• scheduling algorithms for each queue
• method used to determine when to upgrade a
  process
• method used to determine when to demote a process
• method used to determine which queue a process
  will enter when that process needs service

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Example of Multilevel Feedback Queue

• Three queues
• Q0 RR with time quantum 8 milliseconds
• Q1 RR time quantum 16 milliseconds
• Q2 FCFS
• Scheduling
• A new job enters queue Q0 which is served FCFS.
  When it gains CPU, job receives 8 milliseconds.
  If it does not finish in 8 milliseconds, job is
  moved to queue Q1.
• At Q1 job is again served FCFS
• and receives 16 additional milliseconds.
• If it still does not complete,
• it is preempted and moved to queue Q2.

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Thread Scheduling Contention Scope

• The contention scope of a user thread defines how
  it is mapped to a kernel thread.
• System contention scope/global contention scope
  user thread is a user thread that is directly
  mapped to one kernel thread.
• All user threads in a 11 thread model have
  system contention scope.
• Process contention scope/local contention scope
  user thread is a user thread that shares a kernel
  thread with other (process contention scope) user
  threads in the process.
• All user threads in a M1 thread model have
  process contention scope.

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Contention Scope

• In an MN thread model, user
• threads can have either system
• or process contention scope Mixed Scope
• The concurrency level is a property of MN
  threads libraries.
• It defines the number of VPs used to run the
  process contention scope user threads.
• This number cannot exceed the number of process
  contention scope user threads, and is usually
  dynamically set by the threads library.

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Pthread Scheduling

• Pthread API allows specifying either PCS or SCS
  during
• thread creation
• PTHREAD_SCOPE_ PROCESS schedules threads using
  PCS scheduling
• PTHREAD_SCOPE_SYSTEM schedules threads using SCS
  scheduling.
• Two functions for setting and getting
• pthread_attr_setscope(pthread_attr_t attr, int
  scope)
• pthread_attr_getscope(pthread_attr_t attr, int
  scope)

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• include ltpthread.hgt
• include ltstdio.hgt
• define NUM THREADS 5
• int main(int argc, char argv)
• int i
• pthread_t tidNUM THREADS
• pthread _attr_t attr
• / get the default attributes /
• pthread_attr_init(attr)
• / set the scheduling algorithm to PROCESS or
  SYSTEM /
• pthread_attr _setscope(attr, PTHREAD_SCOPE_SYSTE
  M)
• / set the scheduling policy - FIFO, RR, or
  OTHER /
• pthread_attr_setschedpolicy(attr, SCHED_OTHER)
• / create the threads /
• for (i 0 i lt NUM THREADS i)
• pthread_create(tidi,attr,runner,NULL)
• / now join on each thread /
• for (i 0 i lt NUM THREADS i)

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Multiple-Processor Scheduling

• CPU scheduling more complex when multiple CPUs
  are available
• Here we consider homogeneous processors within a
  multiprocessor
• Asymmetric multiprocessing only one processor
  accesses the system data structures, alleviating
  the need for data sharing
• Symmetric multiprocessing (SMP) each processor
  is self-scheduling, all processes in common ready
  queue, or each has its own private queue of ready
  processes
• Processor affinity
• Process has affinity for processor on which it is
  currently running
• For avoiding to invalidate and repopulate caches
  due to migration
• Soft Affinity (Ex Solaris)
• Hard Affinity (Ex Linux, Solaris)

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NUMA and CPU Scheduling
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Multiple-Processor Scheduling Load Balancing

• Distributing the load
• Necessary for system, where each processor has
  its own private queue.
• Approaches
• Push Migration
• Pull Migration
• Generally implemented together
• It often counteracts the benefit of processor
  affinity.

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Multicore Processors

• Recent trend to place multiple processor cores on
  same physical chip
• Faster and consume less power
• Multiple threads per core also growing
• Takes advantage of memory stall to make progress
  on another thread while memory retrieve happens

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Virtualization

• It creates fake impression of the CPU(resources)
  for the guest operating systems running in
  virtual machines.
• E.g Running a time sharing system or real time OS
  in virtual machine
• Thus it can undo the good scheduling efforts.

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Algorithm Evaluation

• Need to make our criteria more specific by adding
  constraints
• Approaches
• Analytic Evaluation
• Deterministic modeling takes a particular
  predetermined workload and defines the
  performance of each algorithm for that workload
• It requires exact input and outcome is bound to
  the defined cases.

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Deterministic Modelling

• Process Burst Time
• P1 10
• P2 29
• P3 3
• P4 7
• P5 12
• FIFO
• Non preemptive SJF
• RR with TQ10

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Queueing Models

• Basically analysis comes from different
  distributions
• Considers a computer system as a network of
  servers where each server has a queue off waiting
  processes.
• Computes utilization, avg queue length, avg wait
  time through arrival and service rates
• This is queueing network analysis
• Littles Formula n ?W
• Has limitations on the classes of algorithm it
  could be applied.
• Mathematical equations does not always represent
  realistic situations

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Evaluation of CPU schedulers by Simulation
Implementation High Cost for evaluation
Dynamic nature of coders/users Best to have
options for fine tuning .
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Linux Scheduling

• Preemptive priority based implementation
• Two priority ranges time-sharing and real-time
• Real-time range from 0 to 99 and nice value from
  100 to 140

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List of Tasks Indexed According to Priorities

• Kernel maintains list of all runnable tasks in a
  runqueue data structure
• Each process maintains own runqueue
• Each runqueue contains two priority arrays
  active expired

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Solaris Scheduling
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End of Lecture 5