Chapter 4: Threads

Operating System Concepts – 9th Silberschatz, Galvin and Gagne

 Chapter 4: Threads
● Overview
● Multicore Programming
● Multithreading Models
● Thread Libraries
● Implicit Threading
● Threading Issues
● Operating System Examples

Operating System Concepts – 9th 4.2 Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4.3 Silberschatz, Galvin and Gagne

 Motivation

● Most modern applications are multithreaded

● Threads run within application
● Multiple tasks with the application can be
implemented by separate threads
● Update display
● Fetch data
● Spell checking
● Answer a network request
● Process creation is heavy-weight while thread creation
is light-weight
● Can simplify code, increase efficiency
● Kernels are generally multithreaded

Operating System Concepts – 9th 4.4 Silberschatz, Galvin and Gagne

 Multithreaded Server Architecture

Operating System Concepts – 9th 4.5 Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4.6 Silberschatz, Galvin and Gagne

 Multicore Programming

● Multicore or multiprocessor systems putting pressure on

programmers, challenges include:
● Dividing activities
● Balance
● Data splitting
● Data dependency
● Testing and debugging
● Parallelism implies a system can perform more than one task
simultaneously
● Concurrency supports more than one task making progress
● Single processor / core, scheduler providing concurrency

Operating System Concepts – 9th 4.7 Silberschatz, Galvin and Gagne

 Multicore Programming (Cont.)

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

Operating System Concepts – 9th 4.8 Silberschatz, Galvin and Gagne

 Concurrency vs. Parallelism
● Concurrent execution on single-core system:

● Parallelism on a multi-core system:

Operating System Concepts – 9th 4.9 Silberschatz, Galvin and Gagne

 Single and Multithreaded Processes

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

● 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?

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 User Threads and Kernel Threads

● User threads - management done by user-level threads library

● Three primary thread libraries:
● POSIX Pthreads
● Windows threads
● Java threads
● Kernel threads - Supported by the Kernel
● Examples – virtually all general purpose operating systems,
including:
● Windows
● Solaris
● Linux
● Tru64 UNIX
● Mac OS X

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Multithreading Models

● Many-to-One

● One-to-One

● Many-to-Many

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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:
● Solaris Green Threads
● GNU Portable Threads

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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
● Windows
● Linux
● Solaris 9 and later

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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 with the ThreadFiber
package

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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)

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Pthreads Example

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Pthreads Example (Cont.)

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Pthreads Code for Joining 10 Threads

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Windows Multithreaded C Program

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Windows Multithreaded C Program (Cont.)

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

● Implementing the Runnable interface

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Java Multithreaded Program

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Java Multithreaded Program (Cont.)

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Implicit Threading

● Growing in popularity as numbers of threads increase,

program correctness more difficult with explicit threads
● Creation and management of threads done by
compilers and run-time libraries rather than
programmers
● Three methods explored
● Thread Pools
● OpenMP
● Grand Central Dispatch
● Other methods include Microsoft Threading Building
Blocks (TBB), java.util.concurrent package

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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
4 i.e.Tasks could be scheduled to run periodically
● Windows API supports thread pools:

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 OpenMP
● Set of compiler directives and
an API for C, C++, FORTRAN
● Provides support for parallel
programming in shared-
memory environments
● Identifies parallel regions –
blocks of code that can run in
parallel
#pragma omp 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Grand Central Dispatch

● Two types of dispatch queues:

● serial – blocks removed in FIFO order, queue is per
process, called main queue
4 Programmers can create additional serial queues
within program
● concurrent – removed in FIFO order but several may
be removed at a time
4 Three system wide queues with priorities low,
default, high

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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
3. 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Signal Handling (Cont.)
● Where should a signal be delivered for multi-
threaded?
● 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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:

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Thread Cancellation (Cont.)
● Invoking thread cancellation requests cancellation, but
actual cancellation depends on thread state

● If thread has cancellation disabled, cancellation remains

pending until thread enables it
● Default type is deferred
● Cancellation only occurs when thread reaches
cancellation point
4 I.e. pthread_testcancel()
4 Then cleanup handler is invoked
● On Linux systems, thread cancellation is handled through
signals

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Scheduler Activations
● Both M:M and Two-level models require
communication to maintain the
appropriate number of kernel threads
allocated to the application
● Typically use an intermediate data
structure between user and kernel
threads – lightweight process (LWP)
● 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?
● Scheduler activations provide upcalls - a
communication mechanism 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 Concepts – 9
th 4. Silberschatz, Galvin and Gagne
 Operating System Examples

● Windows Threads
● Linux Threads

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Windows Threads (Cont.)

● 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

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Windows Threads Data Structures

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 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)

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 Summary
● A thread represents a basic unit of CPU utilization, and threads
belonging to the same process share many of the process resources,
including code and data.
● There are four primary benefits to multithreaded applications: (1)
responsiveness, (2) resource sharing, (3) economy, and (4)
scalability.
● Concurrency exists when multiple threads are making progress,
whereas parallelism exists when multiple threads are making
progress simultaneously. On a system with a single CPU, only
concurrency is possible; parallelism requires a multicore system that
provides multiple CPUs.
● There are several challenges in designing multithreaded applications.
They include dividing and balancing the work, dividing the data
between the different threads, and identifying any data
dependencies. Finally, multithreaded programs are especially
challenging to test and debug.
● Data parallelism distributes subsets of the same data across different
computing cores and performs the same operation on each core.
Task parallelism distributes not data but tasks across multiple cores.
Each task is running a unique operation.
Operating System Concepts – 9
th 4. Silberschatz, Galvin and Gagne
 ● User applications create user-level threads, which must ultimately
be mapped to kernel threads to execute on a CPU. The many-to-
one model maps many user-level threads to one kernel thread.
Other approaches include the one-to-one and many-to-many
models.
● A thread library provides an API for creating and managing
threads. Three common thread libraries include Windows,
Pthreads, and Java threading. Windows is for the Windows system
only, while Pthreads is available for POSIX-compatible systems
such as UNIX, Linux, and macOS. Java threads will run on any
system that supports a Java virtual machine.
● Implicit threading involves identifying tasks—not threads—and
allowing languages or API frameworks to create and manage
threads. There are several approaches to implicit threading,
including thread pools, fork-join frameworks, and Grand Central
Dispatch. Implicit threading is becoming an increasingly common
technique for programmers to use in developing concurrent and
parallel applications.

Operating System Concepts – 9th 4. Silberschatz, Galvin and Gagne

 End of Chapter 4

Operating System Concepts – 9th Silberschatz, Galvin and Gagne