U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science Emery Berger University of Massachusetts Amherst Operating Systems CMPSCI 377 Lecture 5: Threads & Scheduling

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 2 Last Time: Processes Process = unit of execution Process control blocks Process state, scheduling info, etc. New, Ready, Waiting, Running, Terminated One at a time (on uniprocessor) Change by context switch Multiple processes: Communicate by message passing or shared memory

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 3 This Time: Threads & Scheduling What are threads? vs. processes Where does OS implement threads? User-level, kernel How does OS schedule threads?

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 4 Processes versus Threads Process = Control + address space + resources fork() Thread = Control only PC, stack, registers pthread_create() One process may contain many threads

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 5 Threads Diagram Address space in process: shared among threads Cheaper, faster communication than IPC

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 6 Threads Example, C/C++ POSIX threads standard #include void * run (void * d) { int q = ((int) d); int v = 0; for (int i = 0; i < q; i++) { v = v + expensiveComputation(i); } return (void *) v; } main() { pthread_t t1, t2; int r1, r2; pthread_create (&t1, run, 100); pthread_create (&t2, run, 100); pthread_wait (&t1, (void *) &r1); pthread_wait (&t2, (void *) &r2); printf (“r1 = %d, r2 = %d\n”, r1, r2); }

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 7 Threads Example, Java import java.lang.*; class Worker extends Thread implements Runnable { public Worker (int q) { this.q = q; this.v = 0; } public void run() { int i; for (i = 0; i < q; i++) { v = v + i; } } public int v; private int q; } public class Example { public static void main(String args[]) { Worker t1 = new Worker (100); Worker t2 = new Worker (100); try { t1.start(); t2.start(); t1.join(); t2.join(); } catch (InterruptedException e) {} System.out.println ("r1 = " + t1.v + ", r2 = " + t2.v); } }

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 8 Classifying Threaded Systems One or many address spaces, one or many threads per address space MS-DOS

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 9 Classifying Threaded Systems One or many address spaces, one or many threads per address space MS-DOS Embedded systems

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 10 Classifying Threaded Systems One or many address spaces, one or many threads per address space UNIX, Ultrix, MacOS (< X), Win95 Embedded systems MS-DOS

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 11 Classifying Threaded Systems One or many address spaces, one or many threads per address space UNIX, Ultrix, MacOS (< X), Win95 Mach, Linux, Solaris, WinNT MS-DOS Embedded systems

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 12 This Time: Threads What are threads? vs. processes Where does OS implement threads? User-level, kernel How does CPU schedule threads?

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 13 Kernel Threads Kernel threads: scheduled by OS A.k.a. lightweight process (LWPs) Switching threads requires context switch PC, registers, stack pointers BUT: no mem mgmt. = no TLB “shootdown”  Switching faster than for processes Hide latency (don’t block on I/O) Can be scheduled on multiple processors

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 14 User-Level Threads No OS involvement w/user-level threads Only knows about process containing threads Use thread library to manage threads Creation, synchronization, scheduling Example: Java green threads Cannot be scheduled on multiple processors

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 15 User-Level Threads: Advantages No context switch when switching threads But… Flexible: Allow problem-specific thread scheduling policy Computations first, service I/O second, etc. Each process can use different scheduling algorithm No system calls for creation, context switching, synchronization  Can be much faster than kernel threads

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 16 User-Level Threads: Disadvantages Requires cooperative threads Must yield when done working (no quanta) Uncooperative thread can take over OS knows about processes, not threads: Thread blocks on I/O: whole process stops More threads ≠ more CPU time Process gets same time as always Can’t take advantage of multiple processors

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 17 Solaris Threads Hybrid model: User-level threads mapped onto LWPs

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 18 Threads Roundup User-level threads Cheap, simple Not scheduled, blocks on I/O, single CPU Requires cooperative threads Kernel-level threads Involves OS – time-slicing (quanta) More expensive context switch, synch Doesn’t block on I/O, can use multiple CPUs Hybrid “Best of both worlds”, but requires load balancing

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 19 Load Balancing Spread user-level threads across LWPs so each processor does same amount of work Solaris scheduler: only adjusts load when I/O blocks thread scheduler kernel thread scheduler threads processes processors

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 20 Load Balancing Two classic approaches: work sharing & work stealing Work sharing: give excess work away Can waste time

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 21 Load Balancing Two classic approaches: work sharing & work stealing Work stealing: get threads from someone else Optimal approach Sun, IBM Java runtime but what about OS?

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 22 This Time: Threads What are threads? vs. processes Where does OS implement threads? User-level, kernel How does OS schedule threads?

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 23 Scheduling Overview Metrics Long-term vs. short-term Interactive vs. servers Example algorithm: FCFS

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 24 Scheduling Multiprocessing: run multiple processes Improves system utilization & throughput Overlaps I/O and CPU activities

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 25 Scheduling Processes Long-term scheduling: How does OS determine degree of multiprogramming? Number of jobs executing at once Short-term scheduling: How does OS select program from ready queue to execute? Policy goals Policy options Implementation considerations

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 26 Short-Term Scheduling Kernel runs scheduler at least: When process switches from running to waiting On interrupts When processes are created or terminated Non-preemptive system: Scheduler must wait for these events Preemptive system: Scheduler may interrupt running process

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 27 Comparing Scheduling Algorithms Important metrics: Utilization = % of time that CPU is busy Throughput = processes completing / time Response time = time between ready & next I/O Waiting time = time process spends on ready queue

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 28 Scheduling Issues Ideally: Maximize CPU utilization, throughput & minimize waiting time, response time Conflicting goals Cannot optimize all criteria simultaneously  Must choose according to system type Interactive systems Servers

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 29 Scheduling: Interactive Systems Goals for interactive systems: Minimize average response time Time between waiting & next I/O Provide output to user as quickly as possible Process input as soon as received Minimize variance of response time Predictability often important Higher average better than low average, high variance

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 30 Scheduling: Servers Goals different than for interactive systems Maximize throughput (jobs done / time) Minimize OS overhead, context switching Make efficient use of CPU, I/O devices Minimize waiting time Give each process same time on CPU May increase average response time

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 31 Scheduling Algorithms Roundup FCFS: First-Come, First-Served Round-robin: Use quantum & preemption to alternate jobs SJF: Shortest job first Multilevel Feedback Queues: Round robin on each priority queue Lottery Scheduling: Jobs get tickets Scheduler randomly picks winner

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 32 Scheduling Policies FCFS (a.k.a., FIFO = First-In, First-Out) Scheduler executes jobs to completion in arrival order Early version: jobs did not relinquish CPU even for I/O Assume: Runs when processes blocked on I/O Non-preemptive

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 33 FCFS Scheduling: Example Processes arrive 1 time unit apart: average wait time in these three cases?

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 34 FCFS: Advantages & Disadvantages + Advantage: Simple - Disadvantages: - Average wait time highly variable  Short jobs may wait behind long jobs - May lead to poor overlap of I/O & CPU  CPU-bound processes force I/O-bound processes to wait for CPU  I/O devices remain idle

U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science 35 Summary Thread = single execution stream within process User-level, kernel-level, hybrid No perfect scheduling algorithm Selection = policy decision Base on processes being run & goals Minimize response time Maximize throughput etc. Next time: much more on scheduling