Figure 5.01
Threads
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Threads
Overview
Multithreading Models
Thread Libraries
Threading Issues
Operating System Examples
Windows XP Threads
Linux Threads
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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
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
Motivation
Multithreaded Server Architecture
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
Benefits
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
Multicore Programming
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
Multicore Programming (Cont.)
Concurrency vs. Parallelism
Concurrent execution on single-core system:
Parallelism on a multi-core system:
Single and Multithreaded Processes
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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?
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
Tru64 UNIX
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
Examples:
Solaris Green Threads
GNU Portable Threads
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Many-to-One Model
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One-to-One
Each user-level thread maps to kernel thread
Examples
Windows NT/XP/2000
Linux
Solaris 9 and later
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One-to-one Model
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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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Many-to-Many Model
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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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Two-level Model
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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
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
Common in UNIX operating systems (Solaris, Linux, Mac OS X)
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Pthreads Example
Pthreads Example (Cont.)
Pthreads Code for Joining 10 Threads
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:
Extending Thread class
Implementing the Runnable interface
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Java Multithreaded Program
Java Multithreaded Program (Cont.)
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
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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
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:
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