Transcript Threads

Chapter 4: Threads
Operating System Concepts – 8th Edition,
Silberschatz, Galvin and Gagne ©2009
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, Win32, and Java thread libraries
 To examine issues related to multithreaded programming
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Threads Concept
 So far we assumed a process was an executing program with a single
thread of control.
 Motivating example - A web server accepts client requests for Web pages,
images, sound, and so forth (see example in next page)
 A thread is a basic unit of CPU utilization (why CPU? What if it differed just in a
specific device utilization?);

Thread ID

Program counter

Register set

Stack
it comprises:
 It shares with other threads belonging to the same process, its

Code section

Data section and

Other OS resources such as open files
 If a process has multiple threads of control, it can perform more than one
task at a time.
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Multithreaded Server Architecture
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Single and Multithreaded Processes
Example – word processor: (a) displaying graphics,
(b) responding to keystroke, (c) spell checker
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Benefits
 Responsiveness – allow a program to continue running even if
part of it is blocked or performing a lengthy operation (e.g., webbrowser loading an image)
 Resource Sharing – threads share the memory and resources of
the process (allows an application to have several threads of activity
within the same address space)
 Economy – it is more economical to create and context-switch
threads (because they share resources of the process to which they
belong)

In Solaris a process is thirty times slower to create and five times
slower to context-switch
 Scalability (utilizing multiprocessor architectures) – same
process can make use of several CPUs by using threads
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Multicore Programming
 Multicore systems putting pressure on programmers, challenges include:

Dividing activities –find areas that can be divided into separate,
concurrent tasks and thus can run in parallel on individual cores.

Balance – ensure tasks perform equal work of equal value

Data splitting – ensure that the data be divided to run on separate
cores just like the application is divided into separate tasks.

Data dependency – ensure that the execution of the tasks is
synchronized to accommodate data dependency.

Testing and debugging – more difficult than for single-threaded
applications since there are many different execution paths when a
program is running in parallel on multiple cores.
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Concurrent Execution on a Single/Multi-core System
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User and Kernel Threads
 Kernel thread (sometimes called a Lightweight Process - LWP) is created
and scheduled by the kernel:

More expensive to create than user threads
 User thread is created by a threading library and scheduling is managed by
the threading library itself (Which runs in user mode).

All user threads belong to process that created them.

Kernel is unaware of user-level threads so all thread
 The major difference is when using multiprocessor systems:

User threads completely managed by the threading library can't be ran
in parallel on the different CPUs (will run fine on uniprocessor systems)

Since kernel threads use the kernel scheduler, different kernel threads
can run on different CPUs.
 Programs can have user-space threads when threading with timers, signals,
or other methods to interrupt their own execution, performing a sort of adhoc time-slicing.
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User Threads
 Thread management done by user-level threads library
 Three primary thread libraries:

POSIX Pthreads

Win32 threads

Java threads
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Kernel Threads
 Supported by the Kernel
 Examples

Windows XP/2000

Solaris

Linux

Mac OS X
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Multithreading Models
 Many-to-One
 One-to-One
 Many-to-Many
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Many-to-One
 Many user-level threads mapped to single kernel thread
 Thread management is done by the thread library in user space, so it is
efficient.
 Drawback - the entire process will block if a thread makes a blocking
system call.
 Examples:

Solaris Green Threads

GNU Portable Threads
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One-to-One
 Each user-level thread maps to kernel thread
 More concurrency compared to many-to-one model since another thread
will be able to run when a thread makes a blocking system call.
 Allows multiple threads to run in parallel on multiprocessors.

Drawback:

Creating a user thread requires creating a corresponding kernel thread.

Performance will degrade and hence, most systems has a restriction on the number of
threads allowed.
 Examples

Windows NT/XP/2000

Linux

Solaris 9 and later
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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 threads
 Solaris prior to version 9
 Windows NT/2000 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
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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
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Pthreads
 May be provided either as user-level or kernel-level
 A POSIX standard (IEEE 1003.1c) API for thread creation
and synchronization
 API specifies behavior of the thread library, implementation
is up to development of the library (i.e. the OS designers)
 Common in UNIX operating systems (Solaris, Linux, Mac
OS X)
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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:

Extending Thread class (and override its run() method)

Implementing the Runnable interface
 Calling start()

Allocates memory and initializes a new thread in the JVM

Calls the run() method, making the thread eligible to run on
the JVM
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Threading Issues
 Semantics of fork() and exec() system calls
 Thread cancellation of target thread

Asynchronous or deferred
 Signal handling
 Thread pools
 Thread-specific data
 Scheduler activations
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Semantics of fork() and exec()
 Does fork() duplicate only the calling thread or all threads?
 If one thread in a program calls fork(), does the new process duplicate all
threads, or is the new process single-threaded? Unix has both versions.

When exec() system call is executed, the program specified in its
parameter will replace the entire process, including all the threads. Hence,
duplicating only the calling thread is appropriate.
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Thread Cancellation
 Terminating a thread before it has finished


Example: multiple threads concurrently searching
through a database and one thread returns the result
Stopping a webpage from loading any further
 Two general approaches:

Asynchronous cancellation terminates the target
thread immediately – may not free its resources

Deferred cancellation allows the target thread to
periodically check if it should be cancelled – checking a
flag
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Signal Handling

Signals are used in UNIX systems to notify a process that a
particular event has occurred

Example: illegal memory access, division by zero

A signal handler is used to process signals

1.
Signal is generated by particular event
2.
Signal is delivered to a process
3.
Signal is handled
Options:

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
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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
 Unlimited threads could exhaust system resources, such as CPU time
or memory
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Scheduler Activations
 Both M:M and Two-level models require communication to maintain
the appropriate number of kernel threads allocated to the application
 Such coordination allows the number of kernel threads to be
dynamically adjusted to help ensure the best performance
 Communication between the user-level thread library and the kernel
is known as Scheduler activations.
 Scheduler activations provide upcalls - a communication mechanism
from the kernel to the thread library
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