Chapter 5: CPU Scheduling

1. Chapter 5: CPU Scheduling

2. Algorithm Evaluation How to compare scheduling algorithms? How to determine which is a good algorithm for a given system Deterministic modeling – takes a particular predetermined workload and defines the performance of each algorithm for that workload Queueing models Simulation

3. Evaluation of CPU schedulers by Simulation

4. End of Chapter 5

5. Chapter 6: Process Synchronization

6. Chapter 6: Process Synchronization Background The Critical-Section Problem Peterson’s Solution Synchronization Hardware Semaphores Classic Problems of Synchronization Monitors Synchronization Examples Atomic Transactions

7. Objectives To introduce the critical-section problem, whose solutions can be used to ensure the consistency of shared data To present both software and hardware solutions of the critical-section problem To introduce the concept of an atomic transaction and describe mechanisms to ensure atomicity

8. Background Processes and threads provide concurrency Data sharing among cooperating processes/threads Simultaneous access to shared data (especially simultaneous writes) lead to data inconsistency Producer/Consumer problem example

9. Producer while (count == BUFFER.SIZE) ; // do nothing // add an item to the buffer buffer[in] = item; in = (in + 1)%BUFFER.SIZE; ++count;

10. Consumer while (count == 0) ; // do nothing // remove an item from the buffer item = buffer[out]; out = (out + 1)%BUFFER.SIZE; --count;

11. Race Condition count++ can be implemented asregister1 = count register1 = register1 + 1 count = register1 count-- can be implemented asregister2 = count register2 = register2 - 1 count = register2

12. Race Condition (Contd.) Consider a scenario with one producer and one consumer count++ and count-- executed simultaneously Count value should remain unaltered Execution interleaving with “count = 5” initially: T0: producer execute register1 = count {register1 = 5}T1: producer execute register1 = register1 + 1 {register1 = 6} T2: consumer execute register2 = count {register2 = 5} T3: consumer execute register2 = register2 - 1 {register2 = 4} T4: producer execute count = register1 {count = 6 } T5: consumer execute count = register2 {count = 4}

13. Critical Section A conceptual tool to help programmers avoid race conditions A section of code where shared memory/resources (variables, files, tables, etc.) are modified At most one cooperating process can be in the critical region at any given point in time Processes needs to follow a protocol when they modify shared resources – Critical Section Problem Process need to request permission before they enter critical region Program structured as “Entry Section”, Critical Section”, “Exit Section” and “Remainder Section”

14. Structure of a Typical Process

15. Critical Section Solution Requirements Mutual Exclusion - If process Pi is executing in its critical section, then no other processes can be executing in their critical sections. Progress - If no process is executing in its critical section and there exist some processes that wish to enter their critical section, then the selection of the processes that will enter the critical section next cannot be postponed indefinitely. Bounded Waiting - A bound must exist on the number of times that other processes are allowed to enter their critical sections after a process has made a request to enter its critical section and before that request is granted.

16. Critical Section Solution Assumptions Assume that each process executes at a nonzero speed No assumption concerning relative speed of the N processes

17. Peterson’s Solution Two process solution Theoretical solution – May not work correctly on modern architectures Assume that the LOAD and STORE instructions are atomic; that is, cannot be interrupted. The two processes share two variables: int turn; boolean flag[2] The variable turn indicates whose turn it is to enter the critical section. The flag array is used to indicate if a process is ready to enter the critical section. flag[i] = true implies that process Piis ready!

18. while (true) { flag[i] = true; turn = j; while (flag[j] && turn == j); critical section flag[i] = false; remainder section } Algorithm for Process Pi

19. Peterson’s Solution – Points to Note Each process plays the “nice guy” Asserts it is the other processes turn to enter into the critical section The infinite wait loop is broken if at least one of the following holds The other process is not interested in entering the critical region The other process’s write on the “turn” variable survived (i.e., turn has been set to this process)

20. Peterson’s Solution – Correctness proof Mutual exclusion Impossible for both processes to break the while loop simultaneously – Why? Progress and bounded wait Process Pi can be stuck in the wait loop only if turn == j and flag[j] == true If both conditions hold -- Pj wants to be in critical region and it has necessary permission to do so When Pj exits the critical section it sets flag[j] to false Pi enters critical region after at most one entry by Pj When Pj is in the remainder region it has no effect on Pi’s entry into critical region

21. Critical regions protected by locks Processes need to acquire lock before entering CR Acquiring and releasing locks are atomic operations while (true) { acquire lock critical section release lock remainder section } Locks – A Generic Hardware Paradigm

22. Synchronization Hardware Modern machines provide special atomic hardware instructions Atomic mean non-interruptable (i.e., the instruction executes as one unit) getAndSet() -- Test memory word and set its value swap() – exchange the contents of two memory words

23. Illustration of getAndSet and swap

24. Solution using GetAndSet Instruction

25. Solution using Swap Instruction

26. Semaphore • Synchronization tool for programmers • Semaphore S – integer variable • Two standard operations modify S: acquire() and release() • Originally called P() (proberen) andV() (verhogen) • Can only be accessed only via the above atomic operations

27. Semaphore for Mutual Exclusion • Binary semaphore – integer value can range only between 0 and 1 • Also known as mutex locks

28. Java Example Using Semaphores

29. Java Example Using Semaphores

30. Semaphore for Imposing Order • P1 and P2 are concurrently running processes • S1– Statement in process P1; S2 – Statement in Process P2 • Ensure that S2 gets executed only after S1 Initialize semaphore synch to 0 Process P1: Process P2: S1; synch.acquire(); synch.release(); S2;

31. Counting Semaphores • Counting semaphore – integer value can range over an unrestricted domain • Controlling access to a resource with finite number of instances • Initialize semaphore to # of available instances • A process wanting to access resource will do an acquire on the semaphore • Processes will do a release on the semaphore after using the resource • Processes will wait if all available resources are currently being used

32. Semaphore Implementation • Must guarantee that no two processes can execute acquire () and release () on the same semaphore at the same time • Disadvantage: Required busy waiting • Processes continually wait in the entry code • Spinlock – another name for this type of semaphore • Wastes CPU cycles