Operating Systems CMPSCI 377 Lecture 6: Scheduling
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Transcript of Operating Systems CMPSCI 377 Lecture 6: Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Emery BergerUniversity of Massachusetts, Amherst
Operating SystemsCMPSCI 377
Lecture 6: Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 2
Last Time: Threads & Scheduling Thread = execution stream within
process User-level, kernel-level, hybrid
No perfect scheduling algorithm Policy decision Goals:
Minimize response time Maximize throughput Fairness
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 3
This Time: Scheduling Algorithms FCFS
First-Come, First-Served Round-robin SJF Multilevel Feedback Queues Lottery Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 4
Round-Robin Scheduling Quantum expires: move to back of
queue Variants used in most real systems
Tradeoffs: length of quantum Large: response time increases
quantum ) 1 = FCFS Small: throughput decreases
quantum ) 0 = overhead dominates context switches, cache misses
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 5
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 6
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 7
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 8
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 9
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 10
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 11
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 12
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 13
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 14
Example: Round-Robin
waitingrunning
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 15
Example: Round-Robin
waitingrunning
+ Fair- Long
average wait times
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 16
Round-Robin vs. FCFS Example 1:
5 jobs, 100 seconds each, quantum = 1s
ignore context switch time
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 17
Round-Robin vs. FCFS Example 1:
5 jobs, 100 seconds each, quantum = 1s
ignore context switch time
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 18
Round-Robin vs. FCFS Example 2:
5 jobs: 50, 40, 30, 20, 10 seconds each
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 19
Round-Robin vs. FCFS Example 2:
5 jobs: 50, 40, 30, 20, 10 seconds each
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 20
This Time: Scheduling Algorithms FCFS
First-Come, First-Served Round-robin SJF Multilevel Feedback Queues Lottery Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 21
Example: SJF
5040
3020
10
Schedule job with least work until I/O or done
0 10 30 60 100 150
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 22
Example: SJF
5040
3020
10
Schedule job with least work until I/O or done
0 10 30 60 100 150
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 23
Example: SJF
5040
3020
10
Schedule job with least work until I/O or done
0 10 30 60 100 150
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 24
Example: SJF
5040
3020
10
Schedule job with least work until I/O or done
0 10 30 60 100 150
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 25
Example: SJF
5040
3020
10
Schedule job with least work until I/O or done
0 10 30 60 100 150
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 26
Example: SJF
5040
3020
100 10 30 60 100 150
Schedule job with least work until I/O or done
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 27
Example: SJF 5 jobs, length 50, 40, 30, 20, 10
seconds
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 28
Example: SJF 5 jobs, length 50, 40, 30, 20, 10
seconds
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 29
SJF/SRTF: Shortest-Job First Advantages:
Provably optimal – minimizes average waiting time
Works for preemptive & non-preemptive schedulers
Preemptive SJF = SRTF Shortest remaining time first
I/O-bound jobs get priority over CPU-bound jobs
Disadvantages: Impossible to predict CPU time job has left Long-running CPU-bound jobs can starve
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 30
This Time: Scheduling Algorithms FCFS
First-Come, First-Served Round-robin SJF Multilevel Feedback Queues Lottery Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 31
Multilevel Feedback Queues (MLFQ) Use past behavior to predict future,
assign job priorities Overcome prediction problem in SJF
Assumption: I/O-bound in past, I/O-bound in future Scheduler favors jobs that used least
CPU time Adaptive:
Change in behavior ) change in scheduling decisions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 32
MLFQ: Approximating SJF Multiple queues, different priorities
Round-robin scheduling at each priority level
Run all at highest priority first, then next, etc.
Can lead to starvation Increase quantum exponentially at
lower priorities
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 33
MLFQ Example
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 34
MLFQ: Assigning Priorities Job starts in highest priority queue
Quantum expires ) CPU-bound Drop priority one level
Quantum does not expire ) I/O-bound Increase priority one level
CPU-bound jobs move down,I/O-bound jobs move up
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 35
Improving Fairness SJF: optimal, but unfair
Increase fairness = give long jobs CPU time degrades average waiting time
Solutions: Each queue – fraction of CPU time
Fair iff even distribution of jobs among queues
Adjust priority of jobs w/o service Originally done by UNIX Avoids starvation Under load, waiting time suffers
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 36
This Time: Scheduling Algorithms FCFS
First-Come, First-Served Round-robin SJF Multilevel Feedback Queues Lottery Scheduling
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 37
Lottery Scheduling Every job gets lottery tickets Each quantum: randomly pick
winner On average:
CPU time proportional to # of tickets Give most tickets to short-running
jobs (approximates SJF) Give every job at least one ticket Degrades gracefully as load changes
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 38
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 39
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 40
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 41
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 42
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 43
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 44
Example: Lottery Scheduling
Paying customers: 40%, guests: 60% 2:1 ticket ratio
2 2 1 1 1 1 1 1
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 45
Example: Lottery Scheduling2 2 1 1 1 1 1 1
2/5=40%
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 46
Example: Lottery Scheduling
Probabilistically achieves desired proportions
2 2 1 1 1 1 1 1
2/5=40%
3/5=60%
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 47
Summary of Scheduling Algorithms FCFS:
unfair, average waiting time poor Round robin:
fair, average waiting time poor SJF:
unfair, minimizes average waiting time requires accurate prediction
Multilevel Feedback Queueing: approximates SJF
Lottery scheduling: fair, low average waiting time poor fit to priority
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science 48
Next Time Synchronization