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Multiple Processor Systems Bits of Chapters 4, 10, 16 Operating Systems: Internals and Design Principles, 6/E William Stallings.

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Presentation on theme: "Multiple Processor Systems Bits of Chapters 4, 10, 16 Operating Systems: Internals and Design Principles, 6/E William Stallings."— Presentation transcript:

1 Multiple Processor Systems Bits of Chapters 4, 10, 16 Operating Systems: Internals and Design Principles, 6/E William Stallings

2 Parallel Processor Architectures

3 Multiprocessor Systems Continuous need for faster computers –shared memory model –message passing multiprocessor –wide area distributed system

4 Multiprocessors Definition: A computer system in which two or more CPUs share full access to a common RAM

5 Multiprocessor Hardware Bus-based multiprocessors

6 Non-blocking network UMA Multiprocessor using a crossbar switch

7 Blocking network Omega Switching Network

8 Master-Slave multiprocessors Bus

9 Symmetric Multiprocessors Bus

10 Symmetric Multiprocessor Organization

11 Multiprocessor Operating Systems Design Considerations Simultaneous concurrent processes or threads: reentrant routines, IPC Scheduling: on which processor a process should run Synchronization: locks Memory management: e.g. shared pages Reliability and fault tolerance: graceful degradation

12 Multiprocessor Synchronization TSL fails if bus is not locked

13 Spinning versus Switching In some cases CPU must wait –waits to acquire ready list In other cases a choice exists –spinning wastes CPU cycles –switching uses up CPU cycles also –possible to make separate decision each time locked mutex encountered (e.g. using history)

14 Scheduling Design Issues Assignment of processes to processors Use of multiprogramming on individual processors Actual dispatching of a process

15 Assignment of Processes to Processors Treat processors as a pooled resource and assign process to processors on demand Static assignment: Permanently assign process to a processor –Dedicate short-term queue for each processor –Less overhead –Processor could be idle while another processor has a backlog

16 Assignment of Processes to Processors (2) Dynamic assignment: Global queue –Schedule to any available processor – Process migration, cf. local cache

17 Master/slave architecture –Key kernel functions always run on a particular processor –Master is responsible for scheduling –Slave sends service request to the master –Disadvantages Failure of master brings down whole system Master can become a performance bottleneck

18 Peer architecture –Kernel can execute on any processor –Each processor does self-scheduling –Complicates the operating system Make sure two processors do not choose the same process

19 Traditional Process Scheduling Single queue for all processes Multiple queues are used for priorities All queues feed to the common pool of processors

20 Thread Scheduling An application can be a set of threads that cooperate and execute concurrently in the same address space True parallelism

21 Comparison One and Two Processors

22 Comparison One and Two Processors (2)

23 Multiprocessor Thread Scheduling Load sharing –Threads are not assigned to a particular processor Gang scheduling –A set of related threads is scheduled to run on a set of processors at the same time Dedicated processor assignment –Threads are assigned to a specific processor

24 Load Sharing Load is distributed evenly across the processors No centralized scheduler required Use global queues

25 Disadvantages of Load Sharing Central queue needs mutual exclusion Preemptive threads are unlikely to resume execution on the same processor If all threads are in the global queue, not all threads of a program will gain access to the processors at the same time

26 Multiprocessor Scheduling (3) Problem with communication between two threads –both belong to process A –both running out of phase

27 Gang Scheduling Simultaneous scheduling of threads that make up a single process Useful for applications where performance severely degrades when any part of the application is not running Threads often need to synchronize with each other

28 Dedicated Processor Assignment When application is scheduled, its threads are assigned to a processor Some processors may be idle No multiprogramming of processors

29 Application Speedup

30 Client/Server Computing Client machines are generally single-user PCs or workstations that provide a highly user-friendly interface to the end user Each server provides a set of shared services to the clients The server enables many clients to share access to the same database and enables the use of a high-performance computer system to manage the database

31 Generic Client/Server Environment

32 Client/Server Applications Basic software is an operating system running on the hardware platform Platforms and the operating systems of client and server may differ These lower-level differences are irrelevant as long as a client and server share the same communications protocols and support the same applications

33 Generic Client/Server Architecture

34 Middleware Set of tools that provide a uniform means and style of access to system resources across all platforms Enable programmers to build applications that look and feel the same Enable programmers to use the same method to access data

35 Role of Middleware in Client/Server Architecture

36 Distributed Message Passing

37 Basic Message-Passing Primitives

38 Reliability versus Unreliability Reliable message-passing guarantees delivery if possible –Not necessary to let the sending process know that the message was delivered Send the message out into the communication network without reporting success or failure –Reduces complexity and overhead

39 Blocking versus Nonblocking Nonblocking –Process is not suspended as a result of issuing a Send or Receive –Efficient and flexible –Difficult to debug

40 Blocking versus Nonblocking Blocking –Send does not return control to the sending process until the message has been transmitted –OR does not return control until an acknowledgment is received –Receive does not return until a message has been placed in the allocated buffer

41 Remote Procedure Calls Allow programs on different machines to interact using simple procedure call/return semantics Widely accepted Standardized –Client and server modules can be moved among computers and operating systems easily

42 Remote Procedure Call

43 Remote Procedure Call Mechanism

44 Client/Server Binding Binding specifies the relationship between remote procedure and calling program Nonpersistent binding –Logical connection established during remote procedure call Persistent binding –Connection is sustained after the procedure returns

45 Synchronous versus Asynchronous Synchronous RPC –Behaves much like a subroutine call Asynchronous RPC –Does not block the caller –Enable a client execution to proceed locally in parallel with server invocation

46 Clusters Alternative to symmetric multiprocessing (SMP) Group of interconnected, whole computers (nodes) working together as a unified computing resource –Illusion is one machine

47 No Shared Disks

48 Shared Disk

49 Clustering Methods: Benefits and Limitations


51 Operating System Design Issues Failure management –Highly available cluster offers a high probability that all resources will be in service No guarantee about the state of partially executed transactions if failure occurs –Fault-tolerant cluster ensures that all resources are always available

52 Operating System Design Issues (2) Load balancing –When new computer added to the cluster, the load-balancing facility should automatically include this computer in scheduling applications

53 Multicomputer Scheduling - Load Balancing (1) Graph-theoretic deterministic algorithm Process

54 Load Balancing (2) Sender-initiated distributed heuristic algorithm –overloaded sender

55 Load Balancing (3) Receiver-initiated distributed heuristic algorithm –under loaded receiver

56 Operating System Design Issues (3) Parallelizing Computation –Parallelizing compiler: determines at compile time which parts can be executed parallel –Parallelized application: by programmer, message passing for moving data –Parametric computing: several runs with different settings – simulation model

57 Clusters Compared to SMP SMP is easier to manage and configure SMP takes up less space and draws less power SMP products are well established and stable

58 Clusters Compared to SMP Clusters are better for incremental and absolute scalability Clusters are superior in terms of availability

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