# 1 Always want to have CPU (or CPU’s) working Usually many processes in ready queue –Ready to run on CPU –Focus on a single CPU here Need strategies for.

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1 Always want to have CPU (or CPU’s) working Usually many processes in ready queue –Ready to run on CPU –Focus on a single CPU here Need strategies for –Allocating CPU time –Selecting next process to run –Deciding what happens after a process completes a system call, or completes I/O Short-term scheduling –Must not take much CPU time to do the scheduling

Scheduling Introduction to Scheduling Bursts of CPU usage alternate with periods of I/O wait –a CPU-bound process –an I/O bound process

Scheduling Performance Criteria CPU utilization –Percentage of time that CPU is busy (and not idle), over some period of time Throughput –Number of jobs completed per unit time Turnaround time –Time interval from submission of a process until completion of the process Waiting time –Sum of the time periods spent in the ready queue Response time –Time from submission until first output/input –Approximate (estimate) by time from submission until first access to CPU

4 CPU Scheduling Algorithms First-Come, First-Served (FCFS) –Complete the jobs in order of arrival Shortest Job First (SJF) –Complete the job with shortest next CPU burst Priority (PRI) –Processes have a priority –Allocate CPU to process with highest priority Round-Robin (RR) –Each process gets a small unit of time on CPU (time quantum or time slice)

5 Solution: Gantt Chart Method Waiting times? P1: 0 P2: 20 P3: 32 P4: 40 P5: 56 Average wait time: 148/5 = 29.6 FCFS: First-Come First-Served P1 20 P2 32 P3P4P5 4056600

6 FCFS: First-Come First-Served Advantage: Relatively simple algorithm Disadvantage: long waiting times

7 SJF: Shortest Job First The job with the shortest next CPU burst time is selected Example (from before): –CPU job burst times and ready queue order: P1: 20 P2: 12 P3: 8 P4: 16 P5: 4 –Draw Gantt chart and compute the average waiting time given SJF CPU scheduling –Assume 0 context switch time

SJF Solution Waiting times (how long did process wait before being scheduled on the CPU?): P1: 40 P2: 12 P3: 4 P4: 24 P5: 0 Average wait time: 16 (Recall: FCFS scheduling had average wait time of 29.6) P1 4 P2 12 P3P4P5 2440600

9 SJF Provably shortest average wait time BUT: What do we need to actually implement this?

10 Priority Scheduling Have to decide on a numbering scheme –0 can be highest or lowest Priorities can be –Internal Set according to O/S factors (e.g., memory requirements) –External Set as a user policy; e.g., User importance –Static Fixed for the duration of the process –Dynamic Changing during processing E.g., as a function of amount of CPU usage, or length of time waiting (a solution to starvation)

11 Starvation Problem Priority scheduling algorithms can suffer from starvation (indefinite waiting for CPU access) In a heavily loaded system, a steady stream of higher-priority processes can result in a low priority process never receiving CPU time –I.e., it can starve for CPU time One solution: aging –Gradually increasing the priority of a process that waits for a long time See also: Mogul, J. C. and Ramakrishnan, K. K. (1997). Eliminating receive livelock in an interrupt-driven kernel. ACM Trans. Comput. Syst. 15, 3 (Aug. 1997), 217-252. DOI= http://doi.acm.org/10.1145/263326.263335

12 Which Scheduling Algorithms Can be Preemptive? FCFS (First-come, First-Served) –Non-preemptive SJF (Shortest Job First) –Can be either –Choice when a new (shorter) job arrives –Can preempt current job or not Priority –Can be either –Choice when a processes priority changes or when a higher priority process arrives

RR (Round Robin) Scheduling Now talking about time-sharing or multi-tasking system –typical kind of scheduling algorithm in a contemporary general purpose operating system Method –Give each process a unit of time (time slice, quantum) of execution on CPU –Then move to next process in ready queue –Continue until all processes completed Necessarily preemptive –Requires use of timer interrupt Time quantum typically between 10 and 100 milliseconds –Linux default appears to be 100ms 13

14 RR (Round Robin) Scheduling: Example CPU job burst times & order in queue –P1: 20 –P2: 12 –P3: 8 –P4: 16 –P5: 4 Draw Gantt chart, and compute average wait time –Time quantum of 4 –Like our previous examples, assume 0 context switch time

15 Solution Waiting times: P1: 60 - 20 = 40 P2: 44 - 12 = 32 P3: 32 - 8 = 24 P4: 56 - 16 = 40 P5: 20 - 4 = 16 Average wait time: 30.4 P1P2 4 P3P4P5P1 812162024 P2P3 28 P4P1P2P4 3236404448 P1P4 52 P1 5660 completes 0

16 Other Performance Criteria P1 20 P2 32 P3P4P5 405660 FCFS P1 4 P2 12 P3P4P5 244060 SJF P1P2 4 P3P4P5P1 812162024 P2P3 28 P4P1P2P4 3236404448 P1P4 52 P1 5660 RR Response time –Estimate by time from job submission to time to first CPU dispatch –Assume all jobs submitted at same time, in order given Turnaround time –Time interval from submission of a process until completion of the process –Assume all jobs submitted at same time

17 Response Time Calculations JobFCFSSJFRR P10400 P220124 P33248 P4402412 P556016 Average29.6168

18 Turnaround Time Calculations JobFCFSSJFRR P12060 P2322444 P3401232 P4564056 P560420 Average41.62842.4

19 Performance Characteristics of Scheduling Algorithms Different scheduling algorithms will have different performance characteristics RR (Round Robin) –Average waiting time often high –Good average response time Important for interactive or timesharing systems SJF –Best average waiting time –Some overhead with respect to estimates of CPU burst length & ordering ready ‘queue’

20 Context Switching Issues This analysis has not taken context switch duration into account –In general, the context switch will take time –Just like the CPU burst of a process takes time –Response time, wait time etc. will be affected by context switch time RR (Round Robin) & quantum duration –To reduce response times, want smaller time quantum But, smaller time quantum increases system overhead

21 Example  Calculate average waiting time for RR (round robin) scheduling, for  Processes:  P1: 24  P2: 4  P3: 4  Assume above order in ready queue; P1 at head of ready queue  Quantum = 4; context switch time = 1

22 Solution: Average Wait Time With Context Switch Time P1: 0 + 11 + 4 = 15 P2: 5 P3:10 Average: 10 (This is also a reason to dynamically vary the time quantum. E.g., Linux 2.5 scheduler, and Mach O/S.) P1P2P3P1 459101415192024252930343539

23 Multi-level Ready Queues Multiple ready queues –For different types of processes (e.g., system, user) –For different priority processes (e.g., Mach) Each queue can –Have a different scheduling algorithm –Receive a different amount of CPU time –Have movement of processes to another queue (feedback) e.g., if a process uses too much CPU time, put in a lower priority queue If a process is getting too little CPU time, put it in a higher priority queue

24 Multilevel Queue Scheduling

25 Multi-level Feedback Queues

Scheduling in Existing Systems: Linux 2.5 kernel Priority-based, preemptive Two priority ranges (real time and nice) Time quantum longer for higher priority processes (ranges from 10ms to 200ms) Tasks are runnable while they have time remaining in their time quantum; once exhausted, must wait until others have exhausted their time quantum

O(1) Background Briefly – the scheduler maintained two runqueues for each CPU, with a priority linked list for each priority level (140 total). Tasks are enqueued into the corresponding priority list. The scheduler only needs to look at the highest priority list to schedule the next task. Assigns timeslices for each task. Had to track sleep times, process interactivity, etc.

O(1) Background Two runqueues per CPU, I said...one active, one expired. If a process hasn't used its entire timeslice, it's on the active queue; if it has, it's expired. Tasks are swapped between the two as needed. Timeslice and priority are recalculated when a task is swapped. If the active queue is empty, they swap pointers, so the empty one is now the expired queue.

O(1) Background The first 100 priority lists are for real-time tasks, the last 40 are for user tasks. User tasks can have their priorities dynamically adjusted, based on their dependency. (I/O or CPU)

CPU Scheduling as of Linux 2.6.23 Kernel: “Completely Fair Scheduler” Goal: fairness in dividing processor time to tasks Balanced (red-black) tree to implement a ready queue; O(log n) insert or delete time Queue ordered in terms of “virtual run time” –smallest value picked for using CPU –small values: tasks have received less time on CPU –tasks blocked on I/O have smaller values –execution time on CPU added to value –priorities cause different decays of values 30 http://www.ibm.com/developerworks/linux/library/l-completely-fair-scheduler/

The Completely Fair Scheduler CFS cuts out a lot of the things previous versions tracked – no timeslices, no sleep time tracking, no process type identification... Instead, CFS tries to model an “ideal, precise multitasking CPU” – one that could run multiple processes simultaneously, giving each equal processing power. Obviously, this is purely theoretical, so how can we model it?

CFS, continued We may not be able to have one CPU run things simultaneously, but we can measure how much runtime each task has had and try and ensure that everyone gets their fair share of time. This is held in the vruntime variable for each task, and is recorded at the nanosecond level. A lower vruntime indicates that the task has had less time to compute, and therefore has more need of the processor. Furthermore, instead of a queue, CFS uses a Red- Black tree to store, sort, and schedule tasks.

Priorities and more While CFS does not directly use priorities or priority queues, it does use them to modulate vruntime buildup. In this version, priority is inverse to its effect – a higher priority task will accumulate vruntime more slowly, since it needs more CPU time. Likewise, a low-priority task will have its vruntime increase more quickly, causing it to be preempted earlier. “Nice” value – lower value means higher priority. Relative priority, not absolute...

RB Trees A red-black tree is a binary search tree, which means that for each node, the left subtree only contains keys less than the node's key, and the right subtree contains keys greater than or equal to it. A red-black tree has further restrictions which guarantee that the longest root-leaf path is at most twice as long as the shortest root-leaf path. This bound on the height makes RB Trees more efficient than normal BSTs. Operations are in O(log n) time.

The CFS Tree The key for each node is the vruntime of the corresponding task. To pick the next task to run, simply take the leftmost node. http://www.ibm.com/developerworks/linux/library/l-completely-fair-scheduler/

Modular scheduling Alongside the initial CFS release came the notion of “modular scheduling”, and scheduling classes. This allows various scheduling policies to be implemented, independent of the generic scheduler. sched.c, which we have seen, contains that generic code. When schedule() is called, it will call pick_next_task(), which will look at the task's class and call the class-appropriate method. Let's look at the sched_class struct...(sched.h L976)

Scheduling classes! Two scheduling classes are currently implemented: sched_fair, and sched_rt. sched_fair is CFS, which I've been talking about this whole time. sched_rt handles real-time processes, and does not use CFS – it's basically the same as the previous scheduler. CFS is mainly used for non-real-time tasks.

A visual aid is in order... Classes are connected via linked-list, making it easy to iterate among them. Each has its own functions corresponding to the core sched_class. http://www.ibm.com/developerworks/linux/library/l-completely-fair-scheduler/

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