SRM Institute of Science and Technology, Ramapuram

21CSC202J – Operating Systems

Department & Semester: Computer Science and Engineering
YEAR-2 SEM-3
UNIT-II Process Management
SYLLABUS

Process: Process Concept, Process Scheduling, Operations on Processes, Interprocess

Communication, Communication in Client– Server Systems
Threads: Multicore Programming, Multithreading Models, Thread Libraries, Implicit
Threading, Threading Issues.
Process Synchronization: The Critical-Section Problem, Peterson’s Solution,
Synchronization Hardware, Mutex Locks, Semaphores, Classic Problems of
Synchronization, Monitors.

Processes
• Process Concept
• Process Scheduling
• Operations on Processes
• Interprocess Communication
• Examples of IPC Systems
• Communication in Client-Server Systems

Objectives
1. To introduce the notion of a process -- a program in execution, which forms the basis of all
computation
2. To describe the various features of processes, including scheduling, creation and
termination, and communication
3. To explore interprocess communication using shared memory and message passing
4. To describe communication in client-server systems

Process Concept
Program is passive entity stored on disk (executable file), process is active. Program becomes
process when executable file loaded into memory. Execution of program started via GUI mouse
clicks, command line entry of its name, etc One program can be several processes Consider
multiple users executing the same program.

An operating system executes a variety of programs: –

Batch system – jobs
Time-shared systems – user programs or tasks
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Textbook uses the terms job and process almost interchangeably

Process – a program in execution; process execution must progress in sequential fashion

Multiple parts
The program code, also called text section
Current activity including program counter, processor registers
Stack containing temporary data
Function parameters, return addresses, local variables – Data section containing global
variables.
Heap containing memory dynamically allocated during run time.

Process in Memory
Process State
As a process executes, it changes state

– new: The process is being created

– running: Instructions are being executed

– waiting: The process is waiting for some event to occur

– ready: The process is waiting to be assigned to a processor

– terminated: The process has finished execution.

–
– Diagram of Process State

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Process Control Block (PCB)
Information associated with each process(also called task control block)
Process state – running, waiting, etc
Program counter – location of instruction to next execute
CPU registers – contents of all process centric registers
CPU scheduling information- priorities, scheduling queue pointers
Memory-management information – memory allocated to the process
Accounting information – CPU used, clock time elapsed since start, time limits
I/O status information – I/O devices allocated to process, list of
open files

CPU Switch From Process to Process

Threads
So far, process has a single thread of execution
Consider having multiple program counters per process
Multiple locations can execute at once
Multiple threads of control -> threads
Must then have storage for thread details, multiple program counters in PCB.
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Process Representation in Linux
Represented by the C structure task_struct
pid t_pid; /* process identifier */ long state; /* state of the process */ unsigned
int time_slice /* scheduling information */ struct task_struct *parent; /* this
process’s parent */ struct list_head children; /* this process’s children */ struct
files_struct *files; /* list of open files */ struct mm_struct *mm; /* address space
of this process */

Process Scheduling
Maximize CPU use, quickly switch processes onto CPU for time sharing
Process scheduler selects among available processes for next execution on CPU
Maintains scheduling queues of processes
Job queue – set of all processes in the system
Ready queue – set of all processes residing in main memory, ready and waiting to execute
Device queues – set of processes waiting for an I/O device
Processes migrate among the various queues Ready Queue And Various I/O Device Queues

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Representation of Process Scheduling
Queueing diagram represents queues, resources, flows

Schedulers
• Short-term scheduler (or CPU scheduler) – selects which process should be
executed next and allocates CPU
Sometimes the only scheduler in a system
Short-term scheduler is invoked frequently (milliseconds) ⇒ (must be fast)
• Long-term scheduler (or job scheduler) – selects which processes should be
brought into the ready queue
Long-term scheduler is invoked infrequently (seconds, minutes) ⇒ (may be slow)
The long-term scheduler controls the degree of multiprogramming
Processes can be described as either:
I/O-bound process – spends more time doing I/O than computations, many short CPU
bursts
CPU-bound process – spends more time doing computations; few very long CPU bursts
Long-term scheduler strives for good process mix Addition of Medium Term Scheduling
● Medium-term scheduler can be added if degree of multiple programming
needs to decrease
Remove process from memory, store on disk, bring back in from disk to continue
execution: swapping

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Multitasking in Mobile Systems
Some mobile systems (e.g., early version of iOS) allow only one process to run, others
suspended
Due to screen real estate, user interface limits iOS provides for a Single foreground process-
controlled via user interface Multiple background processes– in memory, running, but not
on the display, and with limits
Limits include single, short task, receiving notification of events, specific long-running
tasks like audio playback
Android runs foreground and background, with fewer limits
Background process uses a service to perform tasks
Service can keep running even if background process is suspended
Service has no user interface, small memory use

Context Switch
When CPU switches to another process, the system must save the state of the old process and
load the saved state for the new process via a context switch
Context of a process represented in the PCB
Context-switch time is overhead; the system does no useful work while switching
The more complex the OS and the PCB - the longer the context switch
Time dependent on hardware support
Some hardware provides multiple sets of registers per CPU - multiple contexts loaded at once

Operations on Processes
System must provide mechanisms for:

– process creation,

– process termination,

– and so on as detailed next

Process Creation
• Parent process create children processes, which, in turn create other processes,
forming a tree of processes
• Generally, process identified and managed via a process identifier (pid)

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 • Resource sharing options

– Parent and children share all resources

– Children share subset of parent’s resources

–• Parent and child share no resources

Execution options

– Parent and children execute concurrently

– Parent waits until children terminate

A Tree of Processes in Linux

• Address space

– Child duplicate of parent

– Child has a program loaded into it

–
• UNIX examples

– fork() system call creates new process

– exec() system call used after a fork() to replace the process’ memory space with a
new program

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C Program Forking Separate Process

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Creating a Separate Process via Windows API

Process Termination
Process executes last statement and then asks the operating system to delete it using the exit()
system call.
➢ Returns status data from child to parent (via wait())
➢ Process’ resources are deallocated by operating system
Parent may terminate the execution of children processes using the abort() system call. Some
reasons for doing so:
➢ Child has exceeded allocated resources
➢ Task assigned to child is no longer required

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 ➢ The parent is exiting and the operating systems does not allow a child to continue if its
parent terminates

Process Termination
Some operating systems do not allow child to exists if its parent has terminated. If a process
terminates, then all its children must also be terminated.
➢ cascading termination. All children, grandchildren, etc. are terminated.
➢ The termination is initiated by the operating system.

The parent process may wait for termination of a child process by using the wait() system call.
The call returns status information and the pid of the terminated process
pid = wait(&status);
• If no parent waiting (did not invoke wait()) process is a zombie
• If parent terminated without invoking wait , process is an orphan

Multi-process Architecture – Chrome Browser

• Many web browsers ran as single process (some still do)

If one website causes trouble, entire browser can hang or crash

• Google Chrome Browser is multiprocess with 3 different types of processes: – Browser
process manages user interface, disk and network I/O
– Renderer process renders web pages, deals with HTML, Javascript. A new renderer created
for each website opened
• Runs in sandbox restricting disk and network I/O, minimizing effect of security exploits
– Plug-in process for each type of plug-in

Interprocess Communication
• Processes within a system may be independent or cooperating
• Cooperating process can affect or be affected by other processes, including sharing data
Reasons for cooperating processes:
– Information sharing
– Computation speedup
– Modularity
– Convenience

• Cooperating processes need interprocess communication (IPC)

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• Two models of IPC
– Shared memory
– Message passing

Communications Models
(a) Message passing. (b) shared memory.

Cooperating Processes

• Independent process cannot affect or be affected by the execution of another process

• Cooperating process can affect or be affected by the execution of another process

• Advantages of process cooperation

– Information sharing

– Computation speed-up

– Modularity

– Convenience
Producer-Consumer Problem

• Paradigm for cooperating processes, producer process produces information that is

consumed by a consumer process

– unbounded-buffer places no practical limit on the size of the buffer

– bounded-buffer assumes that there is a fixed buffer size

–
Bounded-Buffer – Shared-Memory Solution
• Shared data
#define BUFFER_SIZE 10 typedef
struct { . . . } item;
item buffer[BUFFER_SIZE]; int in = 0; int
out = 0;
• Solution is correct, but can only use BUFFER_SIZE-1 elements

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Bounded-Buffer – Producer
item
next_produce
d; while (true)
{
/* produce an item in next produced */ while
(((in + 1) % BUFFER_SIZE) == out)
; /* do nothing */ buffer[in] =
next_produced;
in = (in + 1) %
BUFFER_SIZE; }
Bounded Buffer – Consumer
item next_consumed; while
(true) { while (in == out)
; /* do nothing */ next_consumed = buffer[out]; out = (out
+ 1) % BUFFER_SIZE;
/* consume the item in next consumed */
}

Interprocess Communication – Shared Memory

• An area of memory shared among the processes that wish to communicate
• The communication is under the control of the users processes not the operating system.
• Major issues is to provide mechanism that will allow the user processes to synchronize their
actions when they access shared memory.

Interprocess Communication – Message Passing

• Mechanism for processes to communicate and to synchronize their actions
• Message system – processes communicate with each other without resorting to shared
variables
• IPC facility provides two operations:
– send(message)

– receive(message)
• The message size is either fixed or variable
• If processes P and Q wish to communicate, they need to:

– Establish a communication link between them

– Exchange messages via send/receive

• Implementation issues:

– How are links established?

– Can a link be associated with more than two processes?

– How many links can there be between every pair of communicating processes?

– What is the capacity of a link?

– Is the size of a message that the link can accommodate fixed or variable?

– Is a link unidirectional or bi-directional?

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Implementation of communication link – Physical:
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• Shared memory

• Hardware bus

• Network – Logical:

• Direct or indirect

• Synchronous or asynchronous

• Automatic or explicit buffering

Direct Communication

• Processes must name each other explicitly:

– send (P, message) – send a message to process P

– receive(Q, message) – receive a message from process Q

• Properties of communication link

– Links are established automatically

– A link is associated with exactly one pair of communicating processes

– Between each pair there exists exactly one link

– The link may be unidirectional, but is usually bidirectional

Indirect Communication

• Messages are directed and received from mailboxes

(also referred to as ports)

– Each mailbox has a unique id

– Processes can communicate only if they share a mailbox

• Properties of communication link

– Link established only if processes share a common mailbox

– A link may be associated with many processes

– Each pair of processes may share several communication links

– Link may be unidirectional or bi-directional

• Operations

– create a new mailbox (port)

– send and receive messages through mailbox

– destroy a mailbox

• Primitives are defined as:

send(A, message) – send a message to mailbox A receive(A, message) – receive a
message from mailbox A

• Mailbox sharing

– P1, P2, and P3 share mailbox A – P1, sends; P2 and P3 receive – Who gets
the message?

• Solutions

– Allow a link to be associated with at most two processes

– Allow only one process at a time to execute a receive operation

– Allow the system to select arbitrarily the receiver. Sender is notified

who the receiver was.

–
Synchronization

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Message passing may be either blocking or non-blocking

● Blocking is considered synchronous

o Blocking send -- the sender is blocked until the message is received
o Blocking receive -- the receiver is blocked until a message is available

● Non-blocking is considered asynchronous

o Non-blocking send -- the sender sends the message and continue
o Non-blocking receive -- the receiver receives:
o A valid message, or
o Null message
o Different combinations possible
o If both send and receive are blocking, we have a rendezvous

● Producer-consumer becomes trivial

message next_produced; while (true)
{
/* produce an item in next produced */ send(next_produced);
}
message next_consumed; while
(true) {
receive(next_consumed);
/* consume the item in next consumed */ }

Buffering
• Queue of messages attached to the link.
•Zeroimplemented in one of three ways
capacity – no messages are queued on a link. Sender must wait for receiver
(rendezvous)
Bounded capacity – finite length of n messages Sender must wait if link full
Unbounded capacity – infinite length Sender never waits

Examples of IPC Systems - POSIX

● POSIX Shared Memory
● Process first creates shared memory segment

shm_fd = shm_open(name, O CREAT | O

RDWR, 0666);
● Also used to open an existing segment to share it
● Set the size of the object
ftruncate(shm fd, 4096);

● Now the process could write to the shared memory

sprintf(shared
memory, "Writing to shared memory");

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IPC POSIX Producer

IPC POSIX Consumer

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Examples of IPC Systems – Mach

● Mach communication is message based

o Even system calls are messages
o Each task gets two mailboxes at creation- Kernel and Notify
o Only three system calls needed for message transfer
msg_send(), msg_receive(), msg_rpc()
o Mailboxes needed for commuication, created via port_allocate()
o Send and receive are flexible, for example four options if mailbox full:
● Wait indefinitely
● Wait at most n milliseconds
● Return immediately
• Temporarily cache a message
Examples of IPC Systems – Windows
● Message-passing centric via advanced local procedure call
● (LPC) facility
o Only works between processes on the same system
o Uses ports (like mailboxes) to establish and maintain communication channels
o Communication works as follows:
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● The client opens a handle to the subsystem’s connection port object.
● The client sends a connection request.
● The server creates two private communication ports and returns the handle to
one of them to the client.
● The client and server use the corresponding port handle to send messages or
callbacks and to listen for replies.
● Local Procedure Calls in Windows

Communications in Client-Server Systems

• Sockets

• Remote Procedure Calls

• Pipes

• Remote Method Invocation (Java)

Sockets
● A socket is defined as an endpoint for communication
● Concatenation of IP address and port – a number included at start of message packet to
differentiate network services on a host
● The socket 161.25.19.8:1625 refers to port 1625 on host 161.25.19.8
● Communication consists between a pair of sockets
● All ports below 1024 are well known, used for standard services
● Special IP address 127.0.0.1 (loopback) to refer to system on which process is running
● Socket Communication

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Sockets in JavaThree types of sockets

– Connectionoriented (TCP)

– Connectionless
(UDP) – MulticastSock et class– data can be sent to multiple recipients

• Consider this “Date” server:

Remote Procedure Calls

RPC stands for "Remote Procedure Call."
● It is a protocol that allows one computer program to request a service or procedure
to be executed on another remote computer or server.
● How RPC works:
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● Client Sends Request: The client program initiates an RPC request by calling a function or
method that is implemented on the remote server. This function call appears as if it were a local
call.
● Request Serialization: The parameters of the function call are serialized (converted into a
format that can be transmitted over the network). This includes the function name, parameters,
and any other necessary information.
● Network Transmission: The serialized request is sent over the network to the remote server
where the requested procedure will be executed.
● Server Receives Request: The remote server receives the serialized request and deserializes
it to extract the function name and parameters.
● Procedure Execution: The server looks up the requested function or method and executes it
using the provided parameters.
● Response Serialization: The server serializes the result of the function call (return value or
any output) and prepares to send it back to the client.
● Network Transmission: The serialized response is sent back over the network to the client.
● Client Receives Response: The client receives the response, deserializes it to extract the
result, and can then continue its execution based on the received information.
● RPC mechanisms and protocols, such as gRPC, CORBA (Common Object Request Broker
Architecture), Java RMI (Remote Method Invocation), SOAP (Simple Object Access
Protocol)Execution of RPC

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Pipes
● Acts as a conduit allowing two processes to communicate • Issues:
o Is communication unidirectional or bidirectional?
o In the case of two-way communication, is it half or fullduplex?
o Must there exist a relationship (i.e., parent-child) between the communicating
processes?
o Can the pipes be used over a network?
● Ordinary pipes – cannot be accessed from outside the process that created it.
Typically, a parent process creates a pipe and uses it to communicate with a child process
that it created.
● Named pipes – can be accessed without a parent-child relationship.
Ordinary Pipes
● Ordinary Pipes allow communication in standard producer-consumer style
● Producer writes to one end (the write-end of the pipe)
● Consumer reads from the other end (the read-end of the pipe)
● Ordinary pipes are therefore unidirectional
● Require parent-child relationship between communicating processes

● Windows calls these anonymous pipes

● Named Pipes
● Named Pipes are more powerful than ordinary pipes
● Communication is bidirectional
● No parent-child relationship is necessary between the communicating processes
● Several processes can use the named pipe for communication
● Provided on both UNIX and Windows systemsreads

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Threads
Overview
Multicore Programming
Multithreading Models
Thread Libraries
Implicit Threading
Threading Issues
Operating System Examples

Objectives
● To introduce the notion of a thread—a fundamental unit of CPU utilization that forms the
basis of multithreaded computer systems
● To discuss the APIs for the Pthreads, Windows, and Java thread libraries
● To explore several strategies that provide implicit threading
● To examine issues related to multithreaded programming
● To cover operating system support for threads in Windows and Linux
● Motivation
● Most modern applications are multithreaded
● Threads run within application
● Multiple tasks with the application can be implemented by separate threads
o Update display
o Fetch data
o Spell checking
o Answer a network request
● Process creation is heavy-weight while thread creation is light-weight
● Can simplify code, increase efficiency
● Kernels are generally multithreaded
● Multithreaded Server Architecture

Benefits
● Responsiveness – may allow continued execution if part of process is blocked, especially
important for user interfaces
● Resource Sharing – threads share resources of process, easier than shared memory or
message passing
● Economy – cheaper than process creation, thread switching lower overhead than context
switching
● Scalability – process can take advantage of multiprocessor architectures
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● Multicore Programming
● Multicore or multiprocessor systems putting pressure on programmers, challenges
include:
o Dividing activities
o Balance
o Data splitting
o Data dependency
o Testing and debugging

Parallelism implies a system can perform more than one task simultaneously
Concurrency supports more than one task making progress
o Single processor / core, scheduler providing concurrency

Multicore Programming

● Types of parallelism
o Data parallelism – distributes subsets of the same data across multiple cores, same operation
on each
o Task parallelism – distributes threads across cores, each thread performing unique operation
● As # of threads grows, so does architectural support for threading
o CPUs have cores as well as hardware threads
o Consider Oracle SPARC T4 with 8 cores, and 8 hardware threads per core
● Concurrency vs. Parallelism

Concurrent execution on single-core system:

Parallelism on a multi-core system:

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Single and Multithreaded Processes

Amdahl’s Law
● Identifies performance gains from adding additional cores to an application that has both
serial and parallel components
● S is serial portion
● N processing cores
●

● This formula states that the maximum improvement in speed of a process is limited by the
proportion of the program that can be made parallel.
● That is, if application is 75% parallel / 25% serial, moving from 1 to 2 cores results in
speedup of 1.6 times
● As N approaches infinity, speedup approaches 1 / S
● Serial portion of an application has disproportionate effect on performance gained by
adding additional cores
● But does the law take into account contemporary multicore systems?
● User Threads and Kernel Threads
● User threads - management done by user-level threads library

● Three primary thread libraries:

o POSIX Pthreads –
o Windows threads
o Java threads
● Kernel threads - Supported by the Kernel
● Examples – virtually all general purpose operating systems, including:
o Windows
o Solaris
o Linux
o Tru64 UNIX
o Mac OS X
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Multithreading Models
● Many-to-One
● One-to-One
● Many-to-Many

Many-to-One
● Many user-level threads mapped to single kernel thread
● One thread blocking causes all to block
● Multiple threads may not run in parallel on muticore system because only one may be in
kernel at a time
● Few systems currently use this model
● Examples:
o Solaris Green Threads
o GNU Portable Threads

One-to-One
● Each user-level thread maps to kernel thread
● Creating a user-level thread creates a kernel thread
● More concurrency than many-to-one
● Number of threads per process sometimes restricted due to overhead
● Examples
o Windows
o Linux
o Solaris 9

Many-to-Many Model
● Allows many user level threads to be mapped to many kernel threads
● Allows the operating system to create a sufficient number of kernel thread
● Solaris prior to version 9
● Windows with the ThreadFiber package

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Two-level Model
Similar to M:M, except that it allows a user thread to be bound to kernel thread
Examples – IRIX, HP-UX, Tru64 UNIX, Solaris 8 and earlier

Pthreads
● May be provided either as user-level or kernel-level
● A POSIX standard (IEEE 1003.1c) API for thread creation and synchronization
● Specification, not implementation

API specifies behavior of the thread library, implementation is up to development of the library
● Common in UNIX operating systems (Solaris, Linux, Mac OS X)
● Pthreads Example

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Thread Libraries

Thread library provides programmer with API for creating and managing threads

• Two primary ways of implementing

• Library entirely in user space

– Kernel-level library supported by the OS

–
Pthreads Example (Cont.)

Pthreads Code for Joining 10 Threads

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Windows Multithreaded C Program

Windows Multithreaded C Program

Java Threads

• Java threads are managed by the JVM

• Typically implemented using the threads model provided by underlying OS

• Java threads may be created by:

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– Extending Thread class

– Implementing the Runnable interface

–
Java Multithreaded Program

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Implicit Threading

•withGrowing in popularity as numbers of threads increase, program correctness more difficult

explicit threads
•programmers
Creation and management of threads done by compilers and run-time libraries rather than

• Three methods explored

– OpenMP
Thread Pools
– Grand Central Dispatch
– Other methods include Microsoft Threading Building Blocks (TBB), java.util.concurrent
•package
Thread Pools
• Create a number of threads in a pool where they await work • Advantages:
– Usually slightly faster to service a request with an existing thread than create a new thread
– Allows the number of threads in the application(s) to be bound to the size of the pool
– Separating task to be performed from mechanics of creating task allows different strategies
for running task
• i.e.Tasks could be scheduled to run periodically
• Windows API supports thread pools:

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OpenMP
•

• ProvidesSetsupport
of compiler directives and an API for C, C++, FORTRAN
• Identifies parallelfor parallel programming in shared-memory environments
•#pragma omp parallelregions – blocks of code that can run in parallel
Create as many threads as there are cores
#pragma omp parallel for for(i=0;i<N;i++) {
c[i] = a[i] + b[i];
}
Run for loop in parallel
Grand Central Dispatch
• Apple technology for Mac OS X and iOS operating systems
• Extensions to C, C++ languages, API, and run-time library
• Allows identification of parallel sections
• Manages most of the details of threading
• Block is in “^{ }” - ˆ{ printf("I am a block"); } • Blocks placed in dispatch queue
– Assigned to available thread in thread pool when removed from queue

Grand Central Dispatch

• Two types of dispatch queues:

– serial – blocks removed in FIFO order, queue is per process, called main queue

• Programmers can create additional serial queues within program

– concurrent – removed in FIFO order but several may be removed at a time
• Three system wide queues with priorities low, default, high

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Threading Issues

• Semantics of fork() and exec() system calls

• Signal handling

–
•
Synchronous and asynchronous
Thread cancellation of target thread

–
•
Asynchronous or deferred
Thread-local storage
• Scheduler Activations

Semantics of fork() and exec()

• Does fork()duplicate only the calling thread or all threads?
– Some UNIXes have two versions of fork
• exec() usually works as normal – replace the running process including all threads
Signal Handling
● Signals are used in UNIX systems to notify a process that a particular event
has occurred.
● A signal handler is used to process signals
1. Signal is generated by particular event
2. Signal is delivered to a process
Signal is handled by one of two signal handlers:
1. default
2. user-defined
● Every signal has default handler that kernel runs when handling signal
● User-defined signal handler can override default
● For single-threaded, signal delivered to process
Signal Handling (Cont.)
● Where should a signal be delivered for multithreaded?
● Deliver the signal to the thread to which the signal applies
● Deliver the signal to every thread in the process
● Deliver the signal to certain threads in the process
● Assign a specific thread to receive all signals for the process
Thread Cancellation
• Terminating a thread before it has finished • Thread to be canceled is target thread
• Two general approaches:

– Asynchronous cancellation terminates the target thread immediately

Deferred cancellation allows the target thread to periodically check if it should be cancelled

Pthread code to create and cancel a thread

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•depends onInvoking thread cancellation requests cancellation, but actual cancellation
thread state

•enables
If thread has cancellation disabled, cancellation remains pending until thread
it
•– Cancellation only occurs when thread reaches cancellation point
Default type is deferred

• I.e. pthread_testcancel()
• Then cleanup handler is invoked
• On Linux systems, thread cancellation is handled through signals

Thread-Local Storage
• Thread-local storage (TLS) allows each thread to have its own copy of data
• Useful when you do not have control over the thread creation process (i.e., when using a
thread pool)
• Different from local variables

– Local variables visible only during single function invocation

–
•
TLS visible across function invocations
Similar to static data

– TLS is unique to each thread

Scheduler Activations
Both M:M and Two-level models require communication to
maintain the appropriate number of kernel threads allocated to the
application

•process
Typically use an intermediate data structure between user and kernel threads – lightweight
(LWP)

32 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

– Appears to be a virtual processor on which process can schedule user thread to run – Each
LWP attached to kernel thread – How many LWPs to create?
•mechanism
Scheduler activations provide upcalls - a communication
from the kernel to the upcall handler in the thread
library
• This communication allows an application to maintain the
correct number kernel threads
Operating System Examples
• Windows Threads
• Linux Threads

Windows Threads

• Windows implements the Windows API – primary API for Win 98, Win NT, Win 2000,
Win XP, and Win 7
• Implements the one-to-one mapping, kernel-level
• Each thread contains

– A thread id

– Register set representing state of processor

– Separate user and kernel stacks for when thread runs in user mode or kernel mode

–
•
Private data storage area used by run-time libraries and dynamic link libraries (DLLs)
The register set, stacks, and private storage area are known as the context of the thread

• The primary data structures of a thread include:

– ETHREAD (executive thread block) – includes pointer to process to which thread

belongs and to KTHREAD, in kernel space

– KTHREAD (kernel thread block) – scheduling and synchronization info, kernel-

mode stack, pointer to TEB, in kernel space

– TEB (thread environment block) – thread id, user-mode stack, thread-local storage,
in user space

33 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Windows Threads Data Structures

Linux Threads

• Linux refers to them as tasks rather than threads

• Thread creation is done through clone() system call

• clone() allows a child task to share the address space of the parent task (process)
– Flags control behavior

• struct task_struct points to process data structures (shared or unique)

34 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Process Synchronization
• Background
• The Critical-Section Problem • Peterson’s Solution
• Synchronization Hardware
• Mutex Locks
• Semaphores
• Classic Problems of Synchronization
• Monitors
• Synchronization Examples
• Alternative Approaches
Objectives
• To present the concept of process synchronization.
• 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 examine several classical process-synchronization problems
• To explore several tools that are used to solve process synchronization problems
Background
• Processes can execute concurrently
– May be interrupted at any time, partially completing execution
• Concurrent access to shared data may result in data inconsistency
• Maintaining data consistency requires mechanisms to ensure the orderly execution
of cooperating processes

llustration of the problem:

Suppose that we wanted to provide a solution to the consumerproducer problem that
fills all the buffers. We can do so by having an integer counter that keeps track of the
number of full buffers. Initially, counter is set to 0. It is incremented by the producer
after it produces a new buffer and is decremented by the consumer after it consumes a
buffer.
Producer
while (true) {
/* produce an item in next produced
*/
while (counter == BUFFER_SIZE) ;
/* do nothing */ buffer[in] = next_produced; in = (in + 1)
% BUFFER_SIZE; counter++;
}
Consumer
while (true) { while (counter == 0)
35 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE
; /* do nothing */ next_consumed = buffer[out]; out = (out + 1) %
BUFFER_SIZE;
counter--;
/* consume the item in next consumed */
}

Race Condition
• counter++ could be implemented as
register1 = counter register1 =
register1 + 1 counter = register1
• counter-- could be implemented as
register2 = counter register2 =
register2 - 1 counter = register2

Consider this execution interleaving with “count = 5” initially:

S0: producer execute register1 = counter {register1 = 5}

S1: producer execute register1 = register1 + 1 {register1 = 6}
S2: consumer execute register2 = counter {register2 = 5}
S3: consumer execute register2 = register2 – 1 {register2 = 4} S4: producer execute
counter = register1 {counter = 6 }
S5: consumer execute counter = register2 {counter = 4}

Critical Section Problem

• Consider system of n processes {p0, p1, … pn-1}

• Each process has critical section segment of code

– Process may be changing common variables, updating table, writing file, etc

– When one process in critical section, no other may be in its critical section
• Critical section problem is to design protocol to solve this
• Each process must ask permission to enter critical section in entry section, may follow
critical section with exit section, then remainder section

Critical Section
General structure of process Pi

36 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Algorithm for Process Pi

do {
while (turn== j);
critical section
turn = j;
remainder section
} while (true);

Solution to Critical-Section Problem

1. Mutual Exclusion - If process Pi is executing in its critical section, then no other
processes can be executing in their critical sections
2. 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
3. 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

Critical-Section Handling in OS
Two approaches depending on if kernel is preemptive or non- preemptive

–
Preemptive– allows preemption of process when running in kernel mode

–
Non-preemptive – runs until exits kernel mode, blocks, or voluntarily yields CPU
• Essentially free of race conditions in kernel mode

Peterson’s Solution

• Good algorithmic description of solving the problem • Two process solution

•be interruptedthat the load and store machine-language instructions are atomic; that is, cannot
Assume

37 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

• The two processes share two variables:
– int turn;
– Boolean flag[2]
• The variable turn indicates whose turn it is to enter the critical section
• implies
The flag array is used to indicate if a process is ready to enter the critical section. flag[i] =
that process Pi is ready!
true

Algorithm for Process Pi

do {
flag[i] = true; turn = j;
while (flag[j] && turn = = j);
critical section
flag[i] = false;
remainder section
} while (true);
Provable that the three CS requirement are met:
1. Mutual exclusion is preserved
Pi enters CS only if:
either flag[j] = false or turn = i
2. Progress requirement is satisfied
3. Bounded-waiting requirement is met

Synchronization Hardware

• Many systems provide hardware support for implementing the critical section code.
• All solutions below based on idea of locking
– Uniprocessors – could disable interrupts
Protecting critical regions via locks
• Currently running code would execute without preemption
– Generally too inefficient on multiprocessor systems
– Operating systems using this not broadly scalable
• Modern machines provide special atomic hardware instructions
• Atomic = non-interruptible
• Either test memory word and set value
– Or swap contents of two memory words
–
Solution to Critical-section Problem Using Locks
do
{
acquire lock
}
critical section

38 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

release lock remainder
section
} while (TRUE);

39 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

test_and_set Instruction

Definition:
boolean test_and_set (boolean *target)
{ boolean rv = *target; *target =
TRUE; return rv: }
1. Executed atomically
2. Returns the original value of passed parameter
3. Set the new value of passed parameter to “TRUE”.
Solution using test_and_set()
● Shared Boolean variable lock, initialized to FALSE
● Solution:
do { while (test_and_set(&lock))
; /* do nothing */
/* critical section */ lock = false;
/* remainder section */
} while (true);

compare_and_swap Instruction

Definition:
int compare _and_swap(int *value, int expected, int new_value) { int temp = *value;
if (*value == expected)
*value = new_value;
return temp;
}
1. Executed atomically
2. Returns the original value of passed parameter “value”
3. Set the variable “value” the value of the passed parameter “new_value” but only if
“value” ==“expected”. That is, the swap takes place only under this condition.

Solution using compare_and_swap

• Shared integer “lock” initialized to 0;
• Solution:
do { while (compare_and_swap(&lock, 0, 1) != 0)
; /* do nothing */
/* critical section */ lock = 0;
/* remainder section */
} while (true);

Bounded-waiting Mutual Exclusion with test_and_set

do { waiting[i] = true; key = true;

40 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

while (waiting[i] &&
key) key =
test_and_set(&lock);
waiting[i] = false;
/* critical section */
j = (i + 1) % n;
while ((j != i) && !waiting[j]) j = (j + 1) % n;
if (j==i)
lock=false;
else
waiting[j
] = false;
/* remainder section */
} while (true);

Mutex Locks

● Previous solutions are complicated and generally inaccessible to application

programmers
● OS designers build software tools to solve critical section problem
● Simplest is mutex lock
● Protect a critical section by first acquire() a lock then release() the lock
● Boolean variable indicating if lock is available or not
● Calls to acquire() and release() must be atomic
● Usually implemented via hardware atomic instructions
● But this solution requires busy waiting
● This lock therefore called a spinlock
acquire() and release()
• acquire() { while (!available)
; /* busy wait */ available = false;;
}
• release() {
available = true;
}
• do {
acquire lock
critical section
release lock
remainder
section
} while (true);

Semaphore

41 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

• Synchronization tool that provides more sophisticated ways (than Mutex locks)
for process to synchronize their activities.
• Semaphore S – integer variable
• Can only be accessed via two indivisible (atomic) operations
– wait() and signal()
• Originally called P() and V()
• Definition of the wait() operation
wait(S) {
while (S <= 0)
; // busy wait
S--;
}
•Definition of the signal() operation
signal(S) {
S++;
}

Semaphore Usage
• Counting semaphore – integer value can range over an unrestricted domain
• Binary semaphore – integer value can range only between 0 and 1
– Same as a mutex lock
• Can solve various synchronization problems
• Consider P1 and P2 that require S1 to happen before S2
Create a semaphore “synch” initialized to 0
P1:
S1; signal(synch);
P2: wait(synch);
S2;
• Can implement a counting semaphore S as a binary semaphore
Semaphore Implementation
• Must guarantee that no two processes can execute the wait() and signal() on the
same semaphore at the same time
• Thus, the implementation becomes the critical section problem where the wait and
signal code are placed in the critical section
– Could now have busy waiting in critical section implementation
• But implementation code is short
• Little busy waiting if critical section rarely occupied
• Note that applications may spend lots of time in critical sections and therefore this
is not a good solution
Semaphore Implementation with no Busy waiting
• With each semaphore there is an associated waiting queue
• Each entry in a waiting queue has two data items:
– value (of type integer)

– pointer to next record in the list

42 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE
• Two operations:

– block – place the process invoking the operation on the appropriate waiting queue

–
•
wakeup – remove one of processes in the waiting queue and place it in the ready queue
typedef struct{ int value; struct process *list;
} semaphore;

Implementation with no Busy waiting (Cont.)

wait(semaphore *S) { S->value--;
if (S->value < 0) { add this process
to S->list; block();
}
}
signal(semaphore *S) { S->value++; if (S-
>value <= 0) { remove a process P from S-
>list; wakeup(P);
}
}

Deadlock and Starvation

•can be caused
Deadlock – two or more processes are waiting indefinitely for an event that
by only one of the waiting processes
•P0 Let
P1
S and Q be two semaphores initialized to 1

wait(S); wait(Q); wait(Q); wait(S);

... ...
signal(S); signal(Q);
signal(Q); signal(S);
• Starvation – indefinite blocking
–suspended
A process may never be removed from the semaphore queue in which it is

•lock neededPriority Inversion – Scheduling problem when lower-priority process holds a

by higher-priority process
– Solved via priority-inheritance protocol

Classical Problems of Synchronization

Classical problems used to test newly-proposed synchronization schemes

– Bounded-Buffer Problem

– Readers and Writers Problem

– Dining-Philosophers Problem

43 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Bounded-Buffer Problem
• n buffers, each can hold one item
• Semaphore mutex initialized to the value 1
• Semaphore full initialized to the value 0
• Semaphore empty initialized to the value n
The structure of the producer process
do {
...
/* produce an item in next_produced */ ...
wait(empty); wait(mutex);
...
/* add next produced to the buffer */ ...
signal(mutex); signal(full);
} while (true);
Bounded Buffer Problem (Cont.)
●The structure of the consumer process
Do { wait(full); wait(mutex);
...
/* remove an item from buffer to next_consumed */ ...
signal(mutex); signal(empty);
...
/* consume the item in next consumed */
...
} while (true);

Readers-Writers Problem
• A data set is shared among a number of concurrent processes
– Readers – only read the data set; they do not perform any updates
– Writers – can both read and write
• Problem – allow multiple readers to read at the same time
– Only one single writer can access the shared data at the same time
• Several variations of how readers and writers are considered – all involve some form
of priorities
• Shared Data
– Data set
– Semaphore rw_mutex
Semaphore initialized to 1
– Integer read_count
mutex initialized to 1
– initialized to 0

The structure of a writer process

do
{
wait(rw_mutex);
...
44 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE
/* writing is performed */ ...
signal(rw_mutex);
} while (true);
Readers-Writers Problem (Cont.)
• The structure of a reader process
do { wait(mutex);
read_count++; if (read_count
== 1)
wait(rw_mutex);
signal(mutex);
...
/* reading is performed */ ...
wait(mutex); read count--; if
(read_count == 0)
signal(rw_mutex); signal(mutex);
} while (true);

Readers-Writers Problem Variations

• First variation – no reader kept waiting unless writer has permission to use shared
object
• Second variation – once writer is ready, it performs the write ASAP
• Both may have starvation leading to even more variations
• Problem is solved on some systems by kernel providing reader-writer locks
Dining-Philosophers Problem

• Philosophers spend their lives alternating thinking and eating

• Don’t interact with their neighbors, occasionally try to pick up 2 chopsticks
(one at a time) to eat from bowl
– Need both to eat, then release both when done
• In the case of 5 philosophers
– Shared data
• Bowl of rice (data set)
• Semaphore chopstick [5] initialized to 1

45 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Dining-Philosophers Problem Algorithm
The structure of Philosopher i:

do { wait (chopstick[i] ); wait (chopStick[ (i + 1)

% 5] );
// eat
signal (chopstick[i] ); signal (chopstick[ (i + 1) % 5]
);
// think
} while (TRUE);
• What is the problem with this algorithm?
•
Dining-Philosophers Problem Algorithm (Cont.)
• Deadlock handling
– Allow at most 4 philosophers to be sitting simultaneously at the table.
– Allow a philosopher to pick up the forks only if both are available (picking must be
done in a critical section.
– Use an asymmetric solution -- an odd-numbered philosopher picks up first the left
chopstick and then the right chopstick. Even-numbered philosopher picks up first the
right chopstick and then the left chopstick.
Problems with Semaphores
• Incorrect use of semaphore operations:
– signal (mutex) …. wait (mutex)
– wait (mutex) … wait (mutex)
– Omitting of wait (mutex) or signal (mutex) (or both)
• Deadlock and starvation are possible.
Monitors

• A high-level abstraction that provides a convenient and effective mechanism for

process synchronization
• Abstract data type, internal variables only accessible by code within the procedure
• Only one process may be active within the monitor at a time
• But not powerful enough to model some synchronization schemes
monitor monitor-name
{
// shared variable declarations procedure P1
(…) { …. } procedure Pn (…) {……}
Initialization code (…) { … }
}
}

46 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Schematic view of a Monitor

Condition Variables
• condition x, y;
• Two operations are allowed on a condition variable:
– x.wait() – a process that invokes the operation is suspended until x.signal()

– x.signal() – resumes one of processes (if any) that invoked x.wait()

• If no x.wait() on the variable, then it has no effect on the variable

Monitor with Condition Variables

47 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

Condition Variables Choices
•x.wait(),
If process P invokes x.signal(), and process Q is suspended in
what should happen next?
– Both Q and P cannot execute in paralel. If Q is resumed, then P must wait
• Signal and
Options include
–condition
wait – P waits until Q either leaves the monitor or it waits for another

– Signal and continue – Q waits until P either leaves the monitor or it waits for another
condition
– Both have pros and cons – language implementer can decide
– P executing
Monitors implemented in Concurrent Pascal compromise
•other languagessignal immediately leaves the monitor, Q is resumed – Implemented in
including Mesa, C#, Java

Monitor Solution to Dining Philosophers

monitor DiningPhilosophers
{ enum { THINKING; HUNGRY, EATING) state [5] ;
condition self [5];
void pickup (int i) { state[i] = HUNGRY; test(i); if (state[i]
!= EATING) self[i].wait;
48 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE
}
void putdown (int i) { state[i] =
THINKING;
// test left and right neighbors test((i + 4) % 5); test((i + 1) % 5);
}
Solution to Dining Philosophers (Cont.)
void test (int i) { if ((state[(i + 4) % 5] != EATING) &&
(state[i] == HUNGRY) &&
(state[(i + 1) % 5] != EATING) ) { state[i] = EATING ;
self[i].signal () ;
}
}
initialization_code() { for (int i = 0; i < 5;
i++) state[i] = THINKING;
}
}

Solution to Dining Philosophers (Cont.)

• Each philosopher i invokes the operations pickup() and putdown() in the following sequence:
DiningPhilosophers.pickup(i);
EAT
DiningPhilosophers.putdown(i);
• No deadlock, but starvation is possible
Monitor Implementation Using Semaphores
•semaphoreVariables
mutex; // (initially = 1) semaphore next; //
(initially = 0) int next_count = 0;
•wait(mutex); Each procedure F will be replaced by

… body of F;
… if (next_count > 0) signal(next)
else signal(mutex);
•Monitor Implementation
Mutual exclusion within a monitor is ensured
– Condition Variables
•semaphore x_sem; // (initiallyvariable
For each condition x, we have:
= 0) int x_count = 0;
•x_count++; The operation
if
x.wait can be implemented as:

(next_count > 0)
signal(next);
else signal(mutex);
wait(x_sem); x_count--;
Monitor Implementation (Cont.)
• The operation x.signal can be implemented as:

49 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE

if (x_count > 0) { next_count++; signal(x_sem);
wait(next); next_count--;
}
Resuming Processes within a Monitor

• If several processes queued on condition x, and

x.signal() executed, which should be resumed?

• FCFS frequently not adequate

• conditional-wait construct of the form x.wait(c) – Where c is priority number

– Process with lowest number (highest priority) is scheduled next
Single Resource allocation

• Allocate a single resource among competing processes using priority

numbers that specify the maximum time a process plans to use the resource
R.acquire(t); ...
access the resurce; ...
R.release;

• Where R is an instance of type ResourceAllocator

A Monitor to Allocate Single Resource
monitor ResourceAllocator
{ boolean busy; condition x;
void acquire(int time) { if
(busy)
x.wait(time);
busy = TRUE;
} void release()
{ busy =
FALSE;
x.signal();
} initialization
code() { busy =
FALSE;
}
}

50 | Operating system- Unit 2 Prepared by: Ms. T. Archana AP/CSE