本章节就关于关于操作系统的二重性做了介绍,第一点面向消息的系统,小的静态的进程,有限的数据共享,用进程标识地址空间或上下文;第二点就是面向过程的系统,大的快速的进程,使用数据的直接共享和联锁进行通信,识别执行上下文和正在执行的函数。

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1.Concurrency, threads, and events Hakim Weatherspoon CS6410 1

2.Hugh C. Lauer Adjunct Prof., Worcester Polytechnic Institute Xerox, Apollo Computer, Mitsubishi Electronic Research Lab, etc. Founded a number of businesses: Real-Time Visualization unit of Mitsubishi Electric Research Labs (MERL) Roger M. Needham Prof., Cambridge University Microsoft Research, Cambridge Lab Kerberose , Needham-Schroeder security protocol, and key exchange systems On the Duality of Operating System Structure

3.Are they really the same thing? Lauer and Needham show 1) two models are duals Mapping exists from one model to other 2) dual programs are logically identical Textually similar 3) dual programs have identical performance Measured in exec time, compute overhead, and queue/wait times Message vs Procedure oriented systems (i.e. Events vs Threads)

4.Small, static # of process Explicit messaging Limited data sharing in memory Identification of address space or context with processes Message-oriented system (Event)

5.Characteristics Queuing for congested resource Data structure passed by reference (no concurrent access) Peripheral devices treated as processes Priority of process statically determined No global naming scheme is useful Message-oriented system

6.Calls: SendMessage , AwaitReply SendReply WaitForMessage Characteristics Synchronization via message queues No sharing of data structures/address space Number of processes static Message-oriented system

7.Canonical model begin Do forever WaitForMessages case port port 1: …; port 2: …; SendReply ; …; end case end loop end Message-oriented system

8.Message-oriented system

9.Large # of small processes Rapidly changing # of processes Communication using direct sharing and interlocking of data Identification of context of execution with function being executed Procedure-Oriented System (Thread)

10.Characteristics Synchronization and congestion control associates with waiting for locks Data is shared directly and lock lasts for short period of time Control of peripheral devices are in form of manipulating locks Priority is dynamically determined by the execution context Global naming and context is important Process-oriented system

11.Calls: Fork, Join (process) Wait, Signal (condition variables) Characteristics Synchronization via locks/monitors Share global address space/data structures Process (thread) creation very dynamic and low-overhead Process-oriented system

12.Canonical model Monitor -- global data and state info for the process proc1: ENTRY procedure proc2: ENTRY procedure returns begin If resourceExhausted then WAIT; …; RETURN result; …; end proc L: ENTRY procedure begin …; SIGNAL; … end; endloop ; initialize; end Process-oriented system

13.Process-oriented system

14.Dual Mapping Event Thread Processes: CreateProcess Monitors: NEW/START Message channel External procedure id Message port Entry procedure id Send msg (immediate ); AwaitReply Simple procedure call Send msg (delayed ); AwaitReply FORK; … JOIN Send reply Return from procedure Main loop of std resource manager, wait for message stmt, case stmt Monitor lock, ENTRY attribute Arms of case statement ENTRY proc declaration Selective waiting Condition vars , WAIT, SIGNAL

15.Performance characteristics Same execution time Same computational overhead Same queuing and waiting times Do you believe they are the same? What is the controversy? Preservation of Performance

16.20 to 30 years later, still controversy! Analyzes threads vs event-based systems, finds problems with both Suggests trade-off: stage-driven architecture Evaluated for two applications Easy to program and performs well SEDA: An Architecture for Well-Conditioned, Scalable Internet Services (Welsh, 2001)

17.Matt Welsh Cornell undergraduate Alum (Worked on U-Net) PhD from Berkeley (Worked on Ninja clustering) Prof. at Harvard (Worked on sensor networks) Currently at Google David Culler Faculty at UC Berkeley Eric Brewer Faculty at UC Berkeley ( currently VP at Google) SEDA: An Architecture for Well-Conditioned, Scalable Internet Services (Welsh, 2001)

18.A traditional “process” is an address space and a thread of control. Now add multiple thread of controls Share address space Individual program counters and stacks Same as multiple processes sharing an address space. What is a thread?

19.To switch from thread T1 to T2: Thread T1 saves its registers (including pc) on its stack Scheduler remembers T1’s stack pointer Scheduler restores T2’ stack pointer T2 restores its registers T2 resumes Thread Switching

20.Maintains the stack pointer of each thread Decides what thread to run next E.g., based on priority or resource usage Decides when to pre-empt a running thread E.g., based on a timer Needs to deal with multiple cores Didn’t use to be the case “fork” creates a new thread Thread Scheduler

21.Semaphores P(S): block if semaphore is “taken” V(S): release semaphore Monitors: Only one thread active in a module at a time Threads can block waiting for some condition using the WAIT primitive Threads need to signal using NOTIFY or BROADCAST Synchronization Primitives

22.To exploit CPU parallelism Run two threads at once in the same program To exploit I/O parallelism Run I/O while computing, or do multiple I/O I/O may be “remote procedure call” For program structuring E.g., timers Uses of threads

23.Priority Inversion High priority thread waits for low priority thread Solution: temporarily push priority up (rejected??) Deadlock X waits for Y, Y waits for X Incorrect Synchronization Forgetting to release a lock Failed “fork” Tuning E.g. timer values in different environment Common Problems

24.An object queued for some module Operations: create_event_queue(handler)  EQ enqueue_event(EQ, event-object) Invokes, eventually, handler(event-object) Handler is not allowed to block Blocking could cause entire system to block But page faults, garbage collection, … What is an Event?

25.(Also common in telecommunications industry, where it’s called “workflow programming”) Example Event System

26.Decides which event queue to handle next. Based on priority, CPU usage, etc. Never pre-empts event handlers! No need for stack / event handler May need to deal with multiple CPUs Event Scheduler

27.Handlers cannot block  no synchronization Handlers should not share memory At least not in parallel All communication through events Synchronization?

28.CPU parallelism Different handlers on different CPUs I/O concurrency Completion of I/O signaled by event Other activities can happen in parallel Program structuring Not so great… But can use multiple programming languages! Uses of Events

29.Priority inversion, deadlock, etc. much the same with events Stack ripping Common Problems