1. Computer Science Surplus Fair Scheduling: A Proportional-Share Scheduling Algorithm for Symmetric Multiprocessors Abhishek Chandra Micah Adler Pawan Goyal † Prashant Shenoy UMASS Amherst and † Ensim Corporation http://lass.cs.umass.edu/software/gms

2. Computer Science Motivation  Diverse web and multimedia applications popular  HTTP, Streaming, e-commerce, games, etc.  Applications hosted on large servers (typically multiprocessors)  Key Challenge: Design OS mechanisms for Resource Management End-stations Network Server Streaming E-commerce Web

3. Computer Science Requirements for OS Resource Management  Fair, Proportionate Allocation  Eg: 20% for http, 30% for streaming, etc.  Application Isolation  Misbehaving/overloaded applications should not affect other applications  Efficiency  OS mechanisms should have low overheads Focus: Achieving these objectives for CPU scheduling on multiprocessor machines

4. Computer Science Outline  Motivation  Proportional-Share Scheduling  Weight Readjustment  Surplus Fair Scheduling  Experimental Evaluation  Concluding Remarks

5. Computer Science Proportional-Share Scheduling  Associate a weight with each application and allocate CPU bandwidth proportional to weight  Existing Algorithms  Ideal algorithm: Generalized Processor Sharing  E.g.: WFQ, SFQ, SMART, BVT, etc.  Question: Are the existing algorithms adequate for multiprocessor systems? Wt=2 Wt=1 2/31/3 CPU bandwidth Applications

6. Computer Science Starvation Problem  SFQ : Start tag of a thread ( Service / weight )  Schedules the thread with minimum start tag CPU 1 CPU 2 01001000 1100 C arrives B starves Time A (Wt=100) B (Wt=1) C (Wt=1) S1=10 S1=11 S1=0 S1=1 S2=0 S2=100S2=1000 S3=10S3=110 CPU 2...

7. Computer Science Weight Readjustment  Reason for starvation:  Infeasible Weight Assignment (eg: 1:100 for 2 CPUs)  Accounting is different from actual allocation  Observation:  A thread can’t consume more than 1 CPU bandwidth  A thread can be assigned at most (1/p) of total CPU bandwidth  Feasibility Constraint:

8. Computer Science Weight Readjustment (contd.)... CPU 1CPU 2CPU 3 CPU p Decreasing Order of weights  Efficient: Algorithm is O(p)  Can be combined with existing algorithms  Goal: Convert given weights to feasible weights

9. Computer Science Effect of Readjustment 0 5 10 15 20 25 30 01020304050 SFQ without Readjustment Number of iterations (10 5 ) Time (s) 01020304050 SFQ with Readjustment Time (s)  Weight Readjustment gets rid of starvation problem A (wt=10) B (wt=1) C (wt=1) A (wt=10) B (wt=1) C (wt=1)

10. Computer Science Short Jobs Problem 0510152025303540 SFQ J1, wt=20 J2-J21, wt=1x20 J_short, wt=5 Time (s) 0 5 10 15 20 0510152025303540 Ideal J1, wt=20 J2-J21, wt=1x20 J_short, wt=5 Time (s)  Frequent arrivals and departures of short jobs SFQ does unfair allocation! Number of iterations (10 5 )

11. Computer Science Surplus Fair Scheduling Service received by thread i Ideal Actual Time Surplus t  Scheduler picks the threads with least surplus values  Lagging threads get closer to their due  Threads that are ahead are restrained Surplus = Service Actual - Service Ideal

12. Computer Science Surplus Fair Scheduling (contd.)  Start tag (S i ) : Weighted Service of thread i S i = Service i / w i  Virtual time (v) : Minimum start tag of all runnable threads  Surplus (α i ) : α i = Service i - Service lagging = w i S i - w i v  Scheduler selects threads in increasing order of surplus

13. Computer Science Surplus Fair Sched with Short Jobs 0510152025303540 Surplus Fair Sched Time (s) 0 0510152025303540 Ideal Time (s) 5 10 15 20 Number of iterations (10 5 )  Surplus Fair Scheduling does proportionate allocation J1, wt=20 J2-J21, wt=1x20 J_short, wt=5 J1, wt=20 J2-J21, wt=1x20 J_short, wt=5

14. Computer Science Outline  Motivation  Proportional-Share Scheduling  Weight Readjustment  Surplus Fair Scheduling  Experimental Evaluation  Concluding Remarks

15. Computer Science Requirements for OS Resource Management  Fair, Proportionate Allocation  Eg: 20% for web, 30% for streaming, etc.  Application Isolation  Misbehaving/overloaded applications should not affect other applications  Efficiency  OS mechanisms should have low overheads

16. Computer Science Proportionate Allocation 0 1 2 3 4 5 6 7 1:11:21:41:7 Processor Shares received by two web servers Processor Allocation (Normalized) Weight Assignment

17. Computer Science Application Isolation MPEG decoder with background compilations 0 10 20 30 40 50 0246810 Frame Rate (frames/sec) Number of background compilations Surplus Fair Time-sharing

18. Computer Science Scheduling Overhead 0 2 4 6 8 10 0 20304050 Surplus Fair Time-sharing Context switch time (microsec) Number of processes  Context-switch time(~10μ s) vs. Quantum size (~100ms)

19. Computer Science Related Work  CPU Reservations [Jones99]  Uniprocessor proportional-share:  Hierarchical Scheduling [Goyal96]  BVT [Duda99], SMART [Nieh97]  Lottery Scheduling [Waldspurger94]

20. Computer Science Summary  Existing proportional-share algorithms inadequate for multiprocessors  Readjustment Algorithm can reduce unfairness  Surplus Fair Scheduling practical for multiprocessors  Achieves proportional fairness, isolation  Has low overhead  Heuristics for incorporating processor affinity  Source code available at: http://lass.cs.umass.edu/software/gms