Categories of Processes
Process: program in execution
• Independent process do not affect others
• Cooperating process affect each other
– Share memory and/or resources.
– Overlap I/O and processing
– Communicate via message passing.
• I/O-bound – Short CPU bursts between I/O
• CPU-bound process – Long CPU bursts, little I/O
Note: The term, job, normally refers to a batch system process
A Process in Memory
Process States
• As a process executes, it changes state
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–
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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 process
terminated: The process has finished execution
What makes up a process?
• Process Control Block
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Process Id
Process State
Scheduling Information
Child and Parent data
Per Thread
• Program Counter
• CPU Registers
• Stack
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Allocated resources (file list)
Accounting information
I/O or wait status information
Memory-management data
• Program Instructions (text area)
• Program Data and Heap
Process States
Processing Management
Involves migrating processes between queues
Doubly Linked
Lists
Goal: Mix of I/O bound (filling I/O queues) and CPU bound (filling ready queue)
•
•
•
•
Job queue – All system processes
Ready queue – All processes in memory and ready execute
Device queues – All processes waiting for an I/O request completes
Process migrate between the various queues depending on their state
Process Schedulers
• Long-term (What multiprogramming degree?)
– Slow; runs infrequently in the background, when processes terminate
• Medium-term (Which to swap?)
– Efficient; runs roughly every second, when a process needs memory
• Short-Term (which to dispatch next?)
– Must be fast; runs often (i.e. every 100 ms), after every interrupt
Context Switches
Taking control from one process and giving it to another
• Save the old process
state and load the
saved new process
state
• Context-switch time
– pure overhead, no
useful work done
– Cost dependent on
hardware support
• Time slicing gives
CPU cycles in a
round-robin manner
Process Creation
• Parent spawn children, children spawn others
• Resource sharing options
– Parent and children share all resources
– Children share some parent resources
– No sharing
• Execution options
– Parent and children execute concurrently
– Parent waits until children terminate
• Address space options
– Child is a duplicate of the parent
– Child space has a program loaded into it
A Solaris process spawning tree
Root of all user
processes
File management
Support Remote
Telnet/FTP
Memory management
X Windows
POSIX
Example
fork: Child is a clone of the parent
exec: replace memory with new program
Win32
Example
Java Example
Runs separate process, which could be
a separate JVM
Get Process System.out.println output
Note
A JVM is a separate application, supporting multiple threads
Only one process resides within a single JVM
Process Termination
• Process tells OS that is done (exit(0) or System.exit(0))
– Resources are de-allocated
– Status value (usually an integer) is returned
• Parent may terminate child processes (abort())
– Child has exceeded allocated resources
– Child is no longer needed
– Some operating system perform cascading termination,
(automatic child process termination if a parent terminates)
• Parent may wait for child to terminate (wait())
– The child's pid is returned, facilitating process management
– Solaris: if a parent terminates, init becomes the parent
Cooperating Processes
Definition: Processes that affect each other's state
• Reasons
–
–
–
–
Share Data
Speedup: Breaking a task into pieces and execute in parallel
Increase modularity of a complex application
Enhance user convenience: Pipeline a series of algorithmic steps
• Modes of Communication
– Shared Memory:
• System call maps shared memory into logical space of each process
• Mutual exclusion techniques required
• Faster; Processes directly access shared memory without OS help
– Message Passing:
• Easier to program: No critical sections or locking mechanisms needed
• Slower: System calls required for send/receive operations
Inter-process Communication
Message Passing
Shared Memory
Producer-Consumer Problem
Example: Cooperating processes
• unbounded-buffer: No practical buffer size limit
• bounded-buffer: A limited fixed-sized buffer
Note: Java can share memory between threads, but
not among separate JVM processes
Shared-Memory Solution
public interface Buffer
{ public abstract void produce(Object item);
public abstract Object consume(); }
public class BoundedBuffer implements Buffer
{ private int count, in, out; private Object[] buffer;
public BoundedBuffer(int size)
{ count = in = out = 0;
buffer = new Object(size); }
public void produce(Object item)
{ while (count == buffer.length) ;
buffer[in] = item; in = (in + 1)%buffer.length; count++; }
public Object consume()
{ while (count == 0) ;
Object item = buffer[out];
out = (out + 1)%buffer.length; count--;
return item; }
}
Message Passing
• Message system – processes send and
receive to communicate
– send(P, message) // Send to process P
– receive(Q, message) // Receive from process Q
• To communicate, P and Q must:
– establish a communication link between them
– exchange messages via send/receive
• Communication link can be:
– physical (e.g., shared memory, hardware bus)
– logical (e.g., logical properties)
Implementation Questions
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•
•
•
•
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How to establish links? Network, memory, hardware, etc.?
Number of processes sharing a link?
Number of links per process?
Capacity? 0-length (no buffering), bounded queue length, unbounded?
Variable or fixed sized messages?
Unidirectional or bi-directional?
Synchronous/asynchronous? Blocking/non-blocking send/receive
Symmetry/Asymmetry? Sender and receivers name each other or not?
Direct/indirect communication? By hard-coded pid, or mailbox/port?
Copy message data or remap memory?
Communication standard? Protocol?
Persistent or transient? Messges lost after owner terminates?
Direct Communication
• Processes name each other explicitly:
– send (P, message) – send to process P
– receive(Q, message) – receive from process Q
• Properties of communication link
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–
–
–
Links are established automatically
A link connects exactly one pair processes
Between each pair there exists exactly one link
Links are usually bi-directional
Indirect Communication
• Messages sent/received using ports (mailboxes or ports)
– A mailbox has a unique id; processes communicate using the id
– Mailboxes may or may not persist when a processer terminates
– Mailboxes can be owned by a process or by the OS.
• Properties of communication links
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–
–
–
Processes share common mailbox links
A link may be associated with many processes
Processes may share many communication links
Link may be unidirectional or bi-directional
• Operations or OS system calls
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–
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create or destroy mailboxes
send and receive messages through mailbox
Delegate send and receive privileges
send(A, message) – send a message to mailbox A
receive(A, message) – receive a message from mailbox A
Indirect Communication Issue
• Mailbox sharing
– P1, P2, and P3 share mailbox A
– P1, sends; P2 and P3 receive
– Who gets the message?
• Possible Solutions
– Links shared by at most two processes
– Only one process can receive messages
– Arbitrarily select the receiver and notify sender
Synchronization
• Blocking: Synchronous
– Blocking send: The sender block until the
message is received
– Blocking receive: The receiver block until a
message is available
• Non-blocking: Asynchronous
– Non-blocking send has the sender send the
message and continue
– Non-blocking receive has the receiver
receive a valid message or null
Buffering
• Buffering: The link queues messages
• Queue length
1. Zero capacity – queue length = 0
Sender waits for receiver (rendezvous)
2. Bounded capacity – queue length=n
Sender must wait if the link is full
3. Unbounded capacity – infinite length
Sender never waits
Message Passing Solution
public class Unbounded
{ private Vector queue;
public Unbounded()
{ queue = new Vector(); }
public void send(Object item)
{ queue.addElement(item); }
public Object receive()
{ if (queue.size() == 0)
return null;
else return
queue.removeElementAt(0); }
}
// Producer
while(true)
{ send(new Date()); }
// Consumer
while(true)
{ Date msg = (Date)receive();
if (msg != null)
System.out.println(msg);
}
Message Passing in Windows XP
Server establishes a port
When client wants to
communicate, a
handle is sent to
server and client
Shared
memory
if >256 bytes
Small messages copied, larger messages use memory mapping
Socket Communication
Definition: A socket is an endpoint for communication
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Concatenation of IP address and port (ex: 161.25.19.8:1625)
Local host for loopback: 127.0.0.1
Socket port numbers below 1024 are considered well-known
Socket class for Connection-oriented (TCP) sockets, DatagramSocket
class or MulticastSocket class for connectionless (UDP) sockets,
Note: Communication occurs
between a pair of sockets
Java
Socket
Server
1.
2.
3.
4.
5.
6.
Establish a listening port number
Accept a client connection
Get the connection's output stream
Write the data
Close the connection
Continue listening for requests
Java
Socket
Client
1.
2.
3.
4.
Establish a connection to the server
Get the connection's output stream
Read the data
Close the connection
Remote Procedure Calls (RPC)
• Remote procedure call (RPC) abstracts procedure calls
between processes on networked systems
• Higher level abstraction on top of socket communication
• The data is very structured (function/method calling data)
• Implementation
– Client Side (issues an RPC call as if it were local)
1.
2.
3.
4.
Calls a stub (a proxy for the server side procedure)
The stub marshalls the parameters for communication
The message is sent to the server
The stub receives the result and returns to the caller
– Server-side (listens on a designated RPC port)
1.
2.
A stub receives request, un-marshalls data and calls procedure
The returned data is sent back to a waiting client
RPC Considerations
• Reliability: What happens when the server fails? Possible solution:
provide redundant servers
• Multiple calls: Retries trigger duplicate processing. Solution: Time
stamp messages/process duplicate requests "at most once"
• Port binding: Solution: Use fixed port numbers or provide a rendezview
operation to establish port connections
• Data representation
– Big endian (most significant byte first) versus little endian (least
significant byte first)
– Size and format of various data types
– Serializing memory addresses
– Solution: Machine independent external data representation (XDR)
• Disadvantage: Overhead compared to local procedure calls.
• Advantage: Flexibility and single-point hosting of data
RPC
Execution
Remote Method Invocation (RMI)
• Remote Method Invocation: Java-based mechanism
• Difference from RPC: Links to remote Objects, passing
serialized (java.io.Serializable) objects as parameters
Marshalling Parameters
Server Side: Define Remote Objects
• Declare an interface to:
– Specify the signatures for the accessible methods
– The interface extends java.rmi.RemoteException
• Implement a program that listens for RMI requests
– A main method creates an instance of the remote object and
registers it with an appropriate name so it can listen for RMI
requests through Java's socket scheme
– The main class implements the RMI interface and extends
java.rmi.rmi.server.UnicastRemoteObject
– A default constructor is necessary, throwing a
RemoteException if a network failure occurs
// The RMI interface
// The implementation
RMI
Server
RMI Client
// The same interface as on the server
Client RMI Call
1. Lookup and connect to the host
2. Call the method as if it were local
Implementation Steps
1. Compile the source files
2. Generate the stub
a. Before Java 1.5, rmic RemoteDateImpl
b. After Java 1.5, this is done automatically
3. Start the RMI registry in the background
a. Unix: rmiregistry &
b. Windows: start rmiregistry
4. Connects server RMI objects to registry: java RemoteDateImpl
5. Reference remote objects from client: java RMIClient
Advantages compared to Socket Programming
1. RMI is a high level implementation; the registry abstracts socket management
2. Clients do not have to package the data and deal with data representation issues
Threads (Linux: tasks)
A path of execution through a process
Motivation for Threads
• Responsiveness: An application continues
executing when a blocking call occurs
• Resource Sharing: All threads can share an
application's resources
• Economy: Creating new heavyweight processes is
expensive time wise and consumes extra memory
• Parallel Processing: Threads can simultaneously
execute on different cores
Note: Internal kernel threads concurrently perform OS functions.
Servers use threads to efficiently handle client requests
User and Kernel Threads
• User threads - Thread management done by user-level
threads library without OS support. Less system calls –
more efficient
• Kernel threads – Thread management directly
supported by the kernel. More OS overhead
• Tradeoffs: Kernel thread handling incurs more
overhead. User threads stops the application on every
blocking call.
• Most modern operating systems support kernel threads
(Windows, Solaris, Linux, UNIX, Mac OS).
Many-to-One Model
Thread managed by a run time library (more efficient)
• A blocking call will suspend
the application
• All threads run on a single
core
• Examples: Green threads
(on a virtual machine) and
GNU portable threads (OS
is not aware of the threads)
One to One
Thread management is done in the kernel
• Disadvantages
– Increased overhead
– Upper limit on the total
number of threads
• Advantage: Maximum
concurrency; blocking OS calls
don't suspend applications
• Examples: Windows
XP, Linux, Solaris
Many-to-Many
Thread management shared by kernel and user level libraries
• Kernel thread pool assigned to an
application and managed by a
thread library
• Advantages
– Eliminates user thread number limit
– Applications don't suspend on
blocking OS calls
– Increased thread efficiency while
maintaining concurrency
• Disadvantage: Up calls from the
kernel to the thread library
• Example: Windows XP Thread
Fiber library
Two level threads: A many-to-many model.
The kernel maps threads onto processors,
and the run-time thread library maps user
threads onto kernel threads
Many-to-many Thread Scheduling
Issue: How many kernel threads?
• Too many means extra OS overhead
• Too few means processes block
1. The kernel assigns a group of
kernel threads to a process
2. Up-calls: kernel -> thread library
a. If the process is about to block
b. If a blocked kernel thread becomes ready
c. Thread allocations to be released (freed)
Note: A Kernel process sitting between user and kernel
threads assist with thread management. These are often
called light weight processes (LWP)
Threading Issues
• Does spawning a new process spawn all threads or only
the one that is executing? Example: fork() duplicates all threads,
exec() replaces the process with a single thread
• How do we cancel a thread? What if it is working with
system resources? Approaches: asynchronous or Synchronous
cancellation
• How do we minimize overhead of continually creating
threads? Answer: Thread pools
• How do threads communicate? Linux: Signals to notify a
thread of an event, Windows: Asynchronous procedure calls that
function like callbacks. Linux: clone() options determine which
resources are shared between threads.
• How do we create data that is local to a specific thread?
Answer: Thread specific data
• How are threads scheduled for execution? One possibility:
Light weight processes
Pthreads Example (Sum numbers)
void main ( int argc , char argv[] )
{ thread_t[] handles;
int t, threads=strtoi(argv[1],NULL,10);
pthread_mutex_t mtx =
pthread_mutex_init(&mtx, NULL);
handles
= malloc(threads*sizeof(pthread_t ));
for (t=0;t<threads;t++)
pthread_create(&handles[t],
NULL, addThem, (void*)&t);
for ( t= 0 ; t < threads; t ++)
pthread_join(handles[t],NULL);
printf ( "Total = %d\n", sum);
free(handles) ;
pthread_mutex_destroy(&mtx);
}
void* addThem( void *rank )
{ int myRank = (int) (*rank) ;
double mySum = 0;
int i, myN = 10000/threads;
int first = myN*myRank;
int last = first+myN;
f o r (i=first; i<last ; i++)
{
mySum += i; }
pthread_mutex_lock(&mtx)
sum += mySum;
pthread_mutex_unlock(&mtx);
}
openMP Example (Sum numbers)
int main ( int argc , char argv[] )
{ double sum = 0.0 ,
int threads = strtoi(argv[1], NULL, 10);
#pragma omp parallel num_threads(threads) reduction(+:sum)
f o r (i=0; i<last ; i++)
{
sum+= i;
}
printf ( "Total = %d\n", sum);
}
Note: openMP is a popular industry-wide thread standard
Java Threads
• Java threads are managed by the JVM and generally utilize
an OS provided thread-based library
• Java threads may be created by:
– Implementing the Runnable interface
– Extending the Thread class
• Java threads start by calling the start method
– Allocate memory for the thread
– Call the start method
• Java threads terminate when they leave the run method
Java Thread States
• The isAlive() method returns true if a thread is not dead.
• Note: The getState() method returns values of DONE,
PENDING, STARTED
Java Threads (Sum numbers)
public class Driver extends Thread
{ private static double sum = 0.0;
private int upper;
public Driver(int upper)
{ this.upper = upper; this.start(); }
public static void main(String[] args)
{ Driver thread = new Driver(Integer.parseInt(args[0]));
thread.join(); System.out.println("Total = " + sum); }
public void run()
{ sum = 0; for (int i=0; i<upper; i++) sum += i; }
}
Java Producer/Consumer
class Producer implements Runnable
{ private Vector<Date> mbox;
public Producer(Vector<Date> mbox) { this.mbox = mbox; }
public void run()
{ while(true)
{ Thread.currentThread.sleep((int)Math.random(100));
mbox.add(new Date()); } } }
class Consumer implements Runnable
{ private Vector<Date> mbox;
public Consumer(Channel mbox) { this.mbox = mbox; }
public void run()
{ while(true)
{ Thread.currentThread.sleep((int)Math.random(100));
if ((!mbox.isEmpty()) System.out.println((Date)mbox.remove(0)); } }
public class Factory
{ public Factory()
{ Vector<Date> mailBox = new Vector<Date>();
new Producer(mailBox).start(); new Consumer(mailBox).start(); }
public static void main(String[] args) { Factory server = new Factory(); }
}
Java Thread Cancellation
Example: Kill the loading of a Web page in a browser
• Asynchronous: immediately cancel the thread. Can lead to
problems if the thread has partially completed a critical function and
thread owned resources may not be reclaimed (Java: stop())
• Deferred: A thread periodically checks for termination at
cancellation points. The thread then cancels itself.
Spawn the thread and then interrupt it
Thread thread = new MyThread().start(); { … } thread.interrupt();
Periodically check if interrupted in the thread's run method
Thread.currentThread.isInterrupted() // preserve interrupted signal
Thread.currentThread.interrupted() // reset interrupt signal
Example
Thread thread = new Thread(new InterruptibleThread());
thread.start; . . . thread.interrupt();
class InterruptibleThread implements Runnable
{ /** This thread runs till interrupted */
public void run()
{
while(true)
{ / ** do processing till reach a cancellable point */
if (Thread.currentThread().isInterrupted())
{
System.out.println("I'm interrupted!");
return;
}
}
}
Signal Handling
Example: Illegal memory access
• UNIX systems use signals to notify a process that a an
event has occurred
• Signal handler methods process signals
1. Signal generated by particular event
2. It is delivered to a process
3. It is handled
• Options:
–
–
–
–
Deliver the signal to the thread waiting for the signal (synchronous)
Deliver the signal to every thread in the process (ctrl-C)
Deliver the signal to selected threads in the process
Assign a specific thread to receive all signals
• User processes can override the kernel default handler
Thread Pools
A group of threads created in advance that await work to do
• Advantages
– Eliminates overhead thread creation and destruction overhead
– Applications can control the size of the pool
– Avoid creating an unlimited number of threads which can tax
system resources
• Java Options
– Single thread executor - pool of size 1.
Executors.newSingleThreadExecutor()
– Fixed thread executor - pool of fixed size.
Executors.newFixedThreadPool(int nThreads)
– Cached thread pool - pool of unbounded size
Executors.newCachedThreadPool()
Note: Dynamic thread pools adjust the number of threads based on system load
Thread Pool Example
Import java.util.concurrent
public class SomeThread implements Runnable
{ public void run()
{ System.out.println(new Date()); }
}
public class Pool
{ public static void main(String[] args)
{ int tasks=Integer.parseInt(args[0].trim());
ExecutorService pool =
Executors.newCachedThreadPool();
for (int i=0; i<numTasks; i++)
pool.execute(new SomeThread());
pool.shutdown();
}
Thread Specific Data
Each thread can have its own local data
• Motivation: Useful to avoid critical sections in thread pools
• Java scoping facilities
– Normal scoping: variables belong to instantiated objects
– Static scoping: variables belong to the class
– ThreadLocal: content of these objects belong to particular threads
using get and set methods. They are usually declared to be static
class Service
{ // Thread local objects associate contents with thread instances
private static ThreadLocal errorCode = new ThreadLocal();
public static void transaction()
{
try
{ // some operation } catch (Exception e) { errorCode.set(e); }
}
public static Object getErrorCode() { return errorCode.get(); }
}