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Concurrent Programming in Java: Design Principles and Patterns

Authors:
Concurrent Programming in Java
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Concurrent
Programming in Java
Doug Lea
State University of New York at Oswego
dl@cs.oswego.edu
http://gee.cs.oswego.edu
Concurrent Programming in Java
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Topics
Concurrency
Models, design forces, Java
Designing objects for concurrency
Immutability, locking, state dependence, containment, splitting
Introducing concurrency into applications
Autonomous loops, oneway messages, interactive messages,
cancellation
Concurrent application architectures
Flow, parallelism, layering
Libraries
Using, building, and documenting reusable concurrent classes
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About These Slides ...
Some slides are based on joint presentations with David Holmes,
Macquarie University, Sydney Australia.
More extensive coverage of most topics can be found in the book
Concurrent Programming in Java
, Addison-Wesley
and the online supplement
http://gee.cs.oswego.edu/dl/cpj
The printed slides contain much more material than can be covered
in a tutorial. They include extra backgound, examples, and
extensions. They are not always in presentation order.
Java code examples often omit qualifiers, imports, etc for space
reasons. Full versions of most examples are available from the
CPJ online supplement.
None of this material should be construed as official Sun
information.
Java is a trademark of Sun Microsystems, Inc.
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Concurrency
Why?
Availability
Minimize response lag, maximize throughput
Modelling
Simulating autonomous objects, animation
Parallelism
Exploiting multiprocessors, overlapping I/O
Protection
Isolating activities in threads
Why Not?
Complexity
Dealing with safety, liveness, composition
Overhead
Higher resource usage
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Common Applications
I/O-bound tasks
Concurrently access web pages, databases, sockets ...
GUIs
Concurrently handle events, screen updates
Hosting foreign code
Concurrently run applets, JavaBeans, ...
Server Daemons
Concurrently service multiple client requests
Simulations
Concurrently simulate multiple real objects
Common examples
Web browsers, web services, database servers,
programming development tools, decision support tools
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Concurrent Programming
Concurrency is a
conceptual
property of software.
Concurrent programs might or might not:
Concurrent programming mainly deals with concepts and
techniques that apply even if not parallel or distributed.
Threads and related constructs run on any Java platform
This tutorial doesn’t dwell much on issues
specific
to
parallelism and distribution.
Operate across multiple CPUs
symmetric multiprocessor
(SMPs), clusters, special-
purpose architectures, ...
Share access to resources
objects, memory, displays,
file descriptors, sockets,
...
Parallel programming mainly
deals with mapping
software to multiple CPUs
to improve performance.
Distributed programming
mainly deals with
concurrent programs that
do
NOT
share system
resources.
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Concurrent Object-Oriented
Programming
Concurrency has always been a part of OOP (since Simula67)
Not a factor in wide-scale embrace of OOP (late 1980s)
Recent re-emergence, partly due to Java
Concurrent OO programming differs from ...
Sequential OO programming
Adds focus on safety and liveness
But uses and extends common design patterns
Single-threaded Event-based programming (as in GUIs)
Adds potential for multiple events occuring at same time
But uses and extends common messaging strategies
Multithreaded systems programming
Adds encapsulation, modularity
But uses and extends efficient implementations
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Object Models
Models describe how to think about objects (formally or informally)
Common features
Classes, state, references, methods, identity, constraints
Encapsulation
Separation between the insides and outsides of objects
Four basic computational operations
Accept a message
Update local state
Send a message
Create a new object
Models differ in rules for these operations. Two main categories:
Active vs Passive
Concurrent models include features of both
Lead to uniquely concurrent OO design patterns
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Active Object Models
Every object has a single thread of control (like a process) so can
do only one thing at a time.
Most actions are reactive responses to messages from objects
But actions may also be autonomous
But need not act on message immediately upon receiving it
All messages are oneway. Other protocols can be layered on.
Many extensions and choices of detailed semantics
Asynchronous vs synchronous messaging, queuing, pre-
emption and internal concurrency, multicast channels, ...
state, acquaintances
anAction {
update state
send a message
}
trigger
make an object
message
oneway
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Passive Object Models
In sequential programs, only the single Program object is active
Passive objects serve as the program’s data
In single-threaded Java, Program is the JVM (interpretor)
Sequentially simulates the objects comprising the program
All internal communication based on procedure calls
Program
a passive object
State: program counter, object addresses
main I/O
State: instance vars
Methods: byte codes
interpret() {
...
}
other passive objects
trigger
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Concurrent Object Models
Mixtures of active and passive objects
Normally many fewer threads than passive objects
Dumber Active Objects Smarter Passive Objects
Can perform only one
activity
in Java, ‘run()
Share most resources
with other threads
Require scheduling in
order to coexist
May simultaneously
participate in multiple
threads
Protect themselves
from engaging in
conflicting activities
Communicate with
objects participating
in other threads
Initiate and control
new threads
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Hardware Mappings
Shared memory multiprocessing
All objects visible in same (virtual) machine
Can use procedural message passing
Usually many more threads than CPUs
Remote message passing
Only access objects via Remote references or copying
Must marshal (serialize) messages
Mixed models including database mediation (‘‘three tier’’)
Cache
CPUCPU
Cache
memory cells
state of an object
state of
an object
remote messages remote messages
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Vertical Objects
Most OO systems and applications operate at multiple levels
Objects at each level manipulate, manage, and coordinate
lower-level ground objects as resources.
Once considered an arcane systems design principle.
But now applies to most applications
Concurrency
Thread-objects interpret passive objects
Networking and Distribution
Server-objects pass around resources
Persistence and Databases
Database-objects manage states of ground objects
Component Frameworks
Design tools build applications from JavaBeans, etc
Layered Applications
Design patterns based on reflection, interpretation, ...
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Design Forces
Three main aspects of concurrent OO design
Four main kinds of forces that must be addressed at each level
Safety — Integrity requirements
Liveness — Progress requirements
Efficiency — Performance requirements
Reusability — Compositional requirements
Policies & Protocol Object structures Coding techniques
System-wide
design rules Design patterns,
microarchitecture Idioms,
neat tricks,
workarounds
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Systems = Objects + Activities
Objects
ADTs, aggregate components, JavaBeans, monitors,
business objects, remote RMI objects, subsystems, ...
May be grouped according to structure, role, ...
Usable across multiple activities — focus on SAFETY
Activities
Messages, call chains, threads, sessions, scenarios,
scripts, workflows, use cases, transactions, data flows,
mobile computations, ...
May be grouped according to origin, function, ...
Span multiple objects — focus on LIVENESS
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Safe Objects
Perform method actions only when in consistent states
Usually impossible to predict consequences of actions attempted
when objects are in temporarily inconsistent states
Read/write and write/write conflicts
Invariant failures
Random-looking externally visible behavior
Must balance with liveness goals
Clients want simultanous access to services
method1
method2
method3
method4
legal temp
temp
??
transient
states
legal
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State Inconsistency Examples
A figure is drawn while it is in the midst of being moved
Could draw at new X-value, old Y-value
Draws at location that figure never was at
Withdraw from bank account while it is the midst of a transfer
Could overdraw account
Could lose money
A storage location is read in the midst of being written
Could result in reading some old bytes and some new
bytes
Normally, a nonsense value
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Live Activities
Every activity should progress toward completion
Every called method should eventually execute
Related to efficiency
Every called method should execute as soon as possible
An activity might not complete if
An object does not accept a message
A method blocks waiting for an event, message or
condition that should be, but isn’t produced by another
activity
Insufficient or unfairly scheduled resources
Failures and errors of various kinds
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Design Dualities
Two extreme approaches:
Effective, practical, middle-out approaches combine these.
For example, iteratively improving initial designs to be safe
and live across different contexts
Safety-first Liveness-first
Ensure that each class is
safe, then try to improve
liveness as optimization
measure.
Characteristic of top-
down OO Design
Can result in slow,
deadlock-prone code
Design live ground-level
code, then try to layer on
safety features such as
locking and guarding.
Characteristic of
multithreaded
systems
programming
Can result in buggy
code full of races
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Guaranteeing Safety
“Nothing bad ever happens”
Concurrent safety is an extended sense of type safety
Adds a temporal dimension
Not completely enforceable by compilers
Low-level view High-level view
Bits are never
misinterpreted
Protect against
storage conflicts on
memory cells
read/write and
write/write
conflicts
Objects are
accessible only when
in consistent states
Objects must maintain
state and
representation
invariants
Presents subclass
obligations
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Guaranteeing Liveness
“Something eventually happens”
Availability
Avoiding unnecessary blocking
Progress
Avoiding resource contention among activities
Avoiding deadlocks and lockouts
Avoiding unfair scheduling
Designing for fault tolerance, convergence, stability
Citizenship
Minimizing computational demands of sets of activities
Protection
Avoiding contention with other programs
Preventing denial of service attacks
Preventing stoppage by external agents
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Concurrency and Efficiency
Concurrency can be expensive
Performance profiles may vary across platforms
Resources
Threads, Locks, Monitors
Computation
Construction, finalization overhead for resources
Synchronization, context switching, scheduling overhead
Communication
Interaction overhead for threads mapped to different CPUs
Caching and locality effects
Algorithmic efficiency
Cannot use some fast but unsafe sequential algorithms
Paying for tunability and extensibility
Reduces opportunities to optimize for special cases
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Concurrency and Reusability
Added Complexity
More stringent correctness criteria than sequential code
Usually not automatically statically checkable
Nondeterminism impedes debuggability, understandability
Added Context Dependence (coupling)
Components only safe/live when used in intended contexts
Need for documentation
Can be difficult to extend via subclassing
“Inheritance anomalies”
Can be difficult to compose
Clashes among concurrency control techniques
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Reuse and Design Policies
Think locally. Act globally.
Example design policy domains
Combat complexity
High-level design rules and architectural constraints avoid
inconsistent case-by-case decisions
Policy choices are rarely ‘‘optimal’’, but often religiously
believed in anyway.
Maintain openness
Accommodate any component that obeys a given policy
Fail but don’t break if they do not obey policy
State-dependence Service availability Flow constraints
What to do if
a request
logically
cannot be
performed
Constraints on
concurrent
access to
methods
Establishing
message
directionality
and layering
rules
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Three Approaches to Reusability
Patterns Reusing design knowledge
Record best practices, refine them to essences
Analyze for safety, liveness, efficiency, extensibility, etc
Provide recipes for construction
Frameworks Reusing policies and protocols
Create interfaces and classes that establish policy choices
for a suite of applications
Provide utilities and support classes
Mainly use by creating application-dependent (sub)classes
Libraries Reusing code
Create interfaces that apply in many contexts
Provide high-quality implementations
Allow others to create alternative implementations
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Java Overview
Core Java is a relatively small, boring object-oriented language
Main differences from Smalltalk:
Static typing
Support for primitive data types (int,float, etc)
C-based syntax
Main differences from C++:
Run-time safety via Virtual Machine
No insecure low-level operations
Garbage collection
Entirely class-based: No globals
Relative simplicity: No multiple inheritance, etc
Object-based implementations of Array, String, Class, etc
Large predefined class library: AWT, Applets, net, etc
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Java Features
Java solves some software development problems
Packaging: Objects, classes, components, packages
Portability: Bytecodes, unicode, transports
Extensibility: Subclassing, interfaces, class loaders
Safety: Virtual machine, GC, verifiers
Libraries: java.* packages
Ubiquity: Run almost anywhere
But new challenges stem from new aspects of programming:
Concurrency: Threads, locks, ...
Distribution: RMI, CORBA, ...
Persistence: Serialization, JDBC, ...
Security: Security managers, Domains, ...
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Basic Java Constructs
Classes Descriptions of object features
Instance variables Fields representing object state
Methods Encapsulated procedures
Statics Per-class variables and methods
Constructors Operations performed upon object creation
Interfaces Sets of methods implemented by any class
Subclasses Single inheritance from class Object
Inner classes Classes within other classes and methods
Packages Namespaces for organizing sets of classes
Visibility control private, public, protected, per-package
Qualifiers Semantic control: final, abstract, etc
Statements Nearly the same as in C/C++
Exceptions Throw/catch control upon failure
Primitive types byte, short, int, long, float, char, boolean
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Particle Applet
import java.awt.*;
import java.applet.*;
public class ParticleApplet extends Applet {
public void init() {
add(new ParticleCanvas(10));
}
}
class ParticleCanvas extends Canvas {
Particle[] particles;
ParticleCanvas(int nparticles) {
setSize(new Dimension(100, 100));
particles = new Particle[nparticles];
for (int i = 0; i < particles.length; ++i) {
particles[i] = new Particle(this);
new Thread(particles[i]).start();
}
}
public void paint(Graphics g) {
for (int i = 0; i < particles.length; ++i)
particles[i].draw(g);
}
}// (needs lots of embellishing to look nice)
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Particle Class
public class Particle implements Runnable {
private int x = 0, y = 0;
private Canvas canvas;
public Particle(Canvas host) { canvas = host; }
synchronized void moveRandomly() {
x += (int) (((Math.random() - 0.5) * 5);
y += (int) (((Math.random() - 0.5) * 5);
}
public void draw(Graphics g) {
int lx, ly;
synchronized (this) { lx = x; ly = y; }
g.drawRect(lx, ly, 10, 10);
}
public void run() {
for(;;) {
moveRandomly();
canvas.repaint();
try { Thread.sleep((int)(Math.random()*10);}
catch (InterruptedException e) { return; }
}
}
}
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Java Concurrency Support
Thread class represents state of an independent activity
Methods to start, sleep, etc
Very weak guarantees about control and scheduling
Each Thread is a member of a ThreadGroup that is used
for access control and bookkeeping
Code executed in threads defined in classes implementing:
interface Runnable { public void run(); }
synchronized methods and blocks control atomicity via locks
Java automates local read/write atomicity of storage and
access of values of type byte,char,short,int,float,
and Object references, but not double and long
synchronized statement also ensures cache flush/reload
volatile keyword controls per-variable flush/reload
Monitor
methods in class Object control suspension and
resumption:
wait(), wait(ms), notify(), notifyAll()
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Class Thread
Constructors
Thread(Runnable r) constructs so run() calls r.run()
Other versions allow names, ThreadGroup placement
Principal methods
start() activates run() then returns to caller
isAlive() returns true if started but not stopped
join() waits for termination (optional timeout)
interrupt() breaks out of wait,sleep, or join
isInterrupted() returns interruption state
getPriority() returns current scheduling priority
setPriority(
int priorityFromONEtoTEN
) sets it
Static methods that can only be applied to current thread
currentThread() reveals current thread
sleep(ms) suspends for (at least) ms milliseconds
interrupted() returns and clears interruption status
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Designing Objects for
Concurrency
Patterns for safely representing and managing state
Immutability
Avoiding interference by avoiding change
Locking
Guaranteeing exclusive access
State dependence
What to do when you can’t do anything
Containment
Hiding internal objects
Splitting
Separating independent aspects of objects and locks
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Immutability
Synopsis
Avoid interference by avoiding change
Immutable objects never change state
Actions on immutable objects are always safe and live
Applications
Objects representing values
Closed Abstract Data Types
Objects maintaining state representations for others
Whenever object identity does not matter
Objects providing stateless services
Pure functional programming style
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Stateless Service Objects
class StatelessAdder {
int addOne(int i) { return i + 1; }
int addTwo(int i) { return i + 2; }
}
There are no special concurrency concerns:
There is no per-instance state
No storage conflicts
No representational invariants
No invariant failures
Any number of instances of addOne and/or addTwo can
safely execute at the same time. There is no need to
preclude this.
No liveness problems
The methods do not interact with any other objects.
No concurrent protocol design
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Freezing State upon Construction
class ImmutableAdder {
private final int offset_; // blank final
ImmutableAdder(int x) { offset_ = x; }
int add(int i) { return i + offset_; }
}
Still no safety or liveness concerns
Java (blank) finals enforce most senses of immutablity
Don’t cover cases where objects eventually latch into
values that they never change from
Immutability is often used for closed Abstract Data Types in Java
java.lang.String
java.lang.Integer
java.awt.Color
But not java.awt.Point or other AWT graphical
representation classes (A design error?)
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Applications of Immutability
Immutable references to mutable objects
class Relay {
private final Server delegate;
Relay(Server s) { delegate = s; }
void serve() { delegate.serve(); }
}
Partial immutability
Methods dealing with immutable aspects of state do not
require locking
class FixedList { // cells with fixed successors
private final FixedList next; // immutable
FixedList(FixedList nxt) { next = nxt; }
FixedList successor() { return next; }
private Object elem = null; // mutable
synchronized Object get() { return elem; }
synchronized void set(Object x) { elem = x; }
}
delegate
relay server
next next next
element element element
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Locking
Locking is a simple message accept mechanism
Acquire object lock on entry to method, release on return
Precludes storage conflicts and invariant failures
Can be used to guarantee atomicity of methods
Introduces potential liveness failures
Deadlock, lockouts
Applications
Fully synchronized (atomic) objects
Most other reusable objects with mutable state
client
client
internal state
host
lock action { ... }
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Synchronized Method Example
class Location {
private double x_, y_;
Location(double x, double y) { x_ = x; y_ = y; }
synchronized double x() { return x_; }
double y() {
synchronized (this) {
return y_;
}
}
synchronized void moveBy(double dx, double dy) {
x_ += dx;
y_ += dy;
}
}
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Java Locks
Every Java Object possesses one lock
Manipulated only via synchronized keyword
Class objects contain a lock used to protect statics
Scalars like int are not Objects so can only be locked via
their enclosing objects
Synchronized can be either method or block qualifier
synchronized void f() { body; } is equivalent to:
void f() { synchronized(this) { body; } }
Java locks are reentrant
A thread hitting synchronized passes if the lock is free or
it already possesses the lock, else waits
Released after passing as many }s as {’s for the lock
— cannot forget to release lock
Synchronized also has the side-effect of clearing locally cached
values and forcing reloads from main storage
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Storage Conflicts
class Even {
int n = 0;
public int next(){ // POST?: next is always even
++n;
++n;
return n;
}
}
Postcondition may fail due to storage conflicts. For example, one
possible execution trace when n starts off at 0 is:
Declaring next method as synchronized precludes conflicting
traces, as long as all other methods accessing n are also
synchronized
Thread 1
read 0
write 1
read 2
write 3
Thread 2
read 1
write 2
read 2
write 3
return 3
return 3
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Locks and Caching
Locking generates messages between threads and memory
Lock acquisition forces reads from memory to thread cache
Lock release forces writes of cached updates to memory
Without locking, there are NO promises about if and when caches
will be flushed or reloaded
Can lead to unsafe execution
Can lead to nonsensical execution
Cache
CPUCPU
Cache
memory cells
state of object
unlock lock
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Memory Anomalies
Should acquire lock before use of any field of any object, and
release after update
If not, the following are possible:
Seeing stale values that do not reflect recent updates
Seeing inconsistent states due to out-of-order writes
during flushes from thread caches
Seeing incompletely initialized new objects
Can declare volatile fields to force per-variable load/flush.
Has very limited utility.
volatile never usefully applies to reference variables
The referenced object is not necessarily loaded/
flushed, just the reference itself.
Instead, should use synchronization-based
constructions
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Fully Synchronized Objects
Objects of classes in which all methods are synchronized
Always safe, but not always live or efficient
Only process one request at a time
All methods are locally sequential
Accept new messages only when ready
No other thread holds lock
Not engaged in another activity
But methods may make self-calls to
other methods during same activity
without blocking (due to reentrancy)
Constraints
All methods must be synchronized: Java unsynchronized
methods execute even when lock held.
No public variables or other encapsulation violations
Methods must not suspend or infinitely loop
Re-establish consistent state after exceptions
return
client host
... actions..
.
Ready
aMessage
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Deadlock
class Cell {
private long value_;
synchronized long getValue() { return value_;}
synchronized void setValue(long v) {value_ = v;}
synchronized void swapValue(Cell other) {
long t = getValue();
long v = other.getValue();
setValue(v);
other.setValue(t);
}
}
SwapValue is a transactional method. Can deadlock in trace:
thread1
enter
cell1.swapValue
t = getValue()
v = other.getValue()
thread2
enter
cell2.swapValue
t = getValue()
v = other.getValue()
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Lock Precedence
Can prevent deadlock in transactional methods via resource-
ordering based on Java hash codes (among other solutions)
class Cell {
long value;
void swapValue(Cell other) {
if (other == this) return; // alias check
Cell fst = this; // order via hash codes
Cell snd = other;
if (fst.hashCode() > snd.hashCode()) {
fst = other; snd = this;
}
synchronized(fst) {
synchronized (snd) {
long t = fst.value;
fst.value = snd.value;
snd.value = t;
}
}
}
}
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Holding Locks
class Server {
double state;
Helper helper;
public synchronized void svc() {
state = illegalValue;
helper.operation();
state = legalValue;
}
}
Potential problems with holding locks during downstream calls
Safety: What if helper.operation throws exceptions?
Liveness: What if helper.operation causes deadlock?
Availability: Cannot accept new svc requests during helper op
Rule of Thumb (with many variants and exceptions):
Always lock when updating state
Never lock when sending message
Redesign methods to avoid holding locks during downstream calls,
while still preserving safety and consistency
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Synchronization of Accessor Methods
class Queue {
private int sz_ = 0; // number of elements
public synchronized void put(Object x) {
// ... increment sz_ ...
}
public synchronized Object take() {
// ... decrement sz_ ...
}
public int size() { return sz_; } // synch?
}
Should size() method be synchronized?
Pro:
Prevents clients from obtaining stale cached values
Ensures that transient values are never returned
For example, if put temporarily set sz_ = -1 as flag
Con:
What could a client ever do with this value anyway?
Sync always needed for accessors of mutable reference variables
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Locking and Singletons
Every Java Class object has a lock. Both static and instance
methods of Singleton classes should use it.
public class Singleton { // lazy initialization
private int a;
private Singleton(){ a = 1;}
private static Class lock = Singleton.class;
private static Singleton ref = null;
public static Singleton instance(){
synchronized(lock) {
if (ref == null) ref = new Singleton();
return ref;
}
}
public int getA() {
synchronized(lock) { return a; }
}
public void setA(int v){
synchronized(lock) { a = v; }
}
}
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State Dependence
Two aspects of action control:
•Amessage from a client
The internal state of the host
Design Steps:
Choose policies for dealing with actions that can succeed
only if object is in particular logical state
Design interfaces and protocols to reflect policy
Ensure objects able to assess state to implement policy
There is not a
separate
accept
mechanism in
Java. So must
implement policies
in action methods
themselves.
state, acquaintances
anAction {
accept ... }
message
policy control
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Examples of State-Dependent Actions
Operations on collections, streams, databases
Remove an element from an empty queue
Operations on objects maintaining constrained values
Withdraw money from an empty bank account
Operations requiring resources
Print a file
Operations requiring particular message orderings
Read an unopened file
Operations on external controllers
Shift to reverse gear in a moving car
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Policies for State Dependent Actions
Some policy choices for dealing with pre- and post- conditions
Blind action Proceed anyway; no guarantee of outcome
Inaction Ignore request if not in right state
Balking Fail (throw exception) if not in right state
Guarding Suspend until in right state
Trying Proceed, check if succeeded; if not, roll back
Retrying Keep trying until success
Timing out Wait or retry for a while; then fail
Planning First initiate activity that will achieve right state
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Interfaces and Policies
Boring running example
interface BoundedCounter {
static final long MIN = 0;
static final long MAX = 10;
long value(); // INV: MIN <= value() <= MAX
// INIT: value() == MIN
void inc(); // PRE: value() < MAX
void dec(); // PRE: value() > MIN
}
Interfaces alone cannot convey policy
But can suggest policy
For example, should inc throw exception? What kind?
Different methods can support different policies
But can use manual annotations
Declarative constraints form basis for implementation
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Balking
Check state upon method entry
Must not change state in course
of checking it
Relevant state must be explicitly
represented, so can be checked
upon entry
Exit immediately if not in right state
Throw exception or return special
error value
Client is responsible for handling
failure
The simplest policy for fully synchronized objects
Usable in both sequential and concurrent contexts
Often used in Collection classes (Vector, etc)
In concurrent contexts, the host must always take
responsibility for entire check-act/check-fail sequence
Clients cannot preclude state changes between check
and act, so host must control
return
client host
... actions..
.
!inRightState
throw
inRightState
aMessage
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Balking Counter Example
class Failure extends Exception { }
class BalkingCounter {
protected long count_ = MIN;
synchronized long value() { return count_;}
synchronized void inc() throws Failure {
if (count_ >= MAX) throw new Failure();
++count_;
}
synchronized void dec() throws Failure {
if (count_ <= MIN) throw new Failure();
--count_;
}
}
// ...
void suspiciousUsage(BalkingCounter c) {
if (c.value() > BalkingCounter.MIN)
try { c.dec(); } catch (Failure ignore) {}
}
void betterUsage(BalkingCounter c) {
try { c.dec(); } catch (Failure ex) {cope();}
}
Concurrent Programming in Java
56
Collection Class Example
class Vec { // scaled down version of Vector
protected Object[] data_; protected int size_=0;
public Vec(int cap) { data_=new Object[cap]; }
public int size() { return size_; }
public synchronized Object at(int i)
throws NoSuchElementException {
if (i < 0 || i >= size_ )
throw new NoSuchElementException();
return data_[i];
}
public synchronized void append(Object x) {
if (size_ >= data_.length) resize();
data_[size_++] = x;
}
public synchronized void removeLast()
throws NoSuchElementException {
if (size_ == 0)
throw new NoSuchElementException();
data_[--size_] = null;
}
}
Concurrent Programming in Java
57
Policies for Collection Traversal
How to apply operation to collection elements without interference
Balking iterators
Throw exception on access if collection was changed.
Implement via version numbers updated on each change
Used in JDK1.2 collections
But can be hard to recover from exceptions
Snapshot iterators
Make immutable copy of base collection elements. Or
conversely, copy-on-write during each update.
But can be expensive
Indexed traversal
Clients externally synchronize when necessary
But coupled to particular locking policies
Synchronized aggregate methods
Support apply-to-all methods in collection class
But deadlock-prone
Concurrent Programming in Java
58
Synchronized Traversal Examples
interface Procedure { void apply(Object obj); }
class XVec extends Vec {
synchronized void applyToAll(Procedure p) {
for (int i=0;i<size_;++i) p.apply(data_[i]);
}
}
class App {
void printAllV1(XVec v) { // aggregate synch
v.applyToAll(new Procedure() {
public void apply(Object x) {
System.out.println(x);
}});
}
void printAllV2(XVec v) { // client-side synch
synchronized (v) {
for (int i = 0; i < v.size(); ++i)
System.out.println(v.at(i));
}
}
}
Concurrent Programming in Java
59
Guarding
Generalization of locking for state-dependent actions
Locked: Wait until ready (not engaged in other methods)
Guarded: Wait until an arbitrary state predicate holds
Check state upon entry
If not in right state, wait
Some other action in some
other thread may eventually
cause a state change that
enables resumption
Introduces liveness concerns
Relies on actions of other
threads to make progress
Useless in sequential
programs
aMessage inRightState
return
client host
... actions...
Concurrent Programming in Java
60
Guarding via Busy Waits
class UnsafeSpinningBoundedCounter { // don’t use
protected volatile long count_ = MIN;
long value() { return count_; }
void inc() {
while (count_ >= MAX); // spin
++count_;
}
void dec() {
while (count_ <= MIN); // spin
--count_;
}
}
Unsafe — no protection from read/write conflicts
Wasteful — consumes CPU time
But busy waiting can sometimes be useful; generally when
The conditions latch
— once set true, they never become false
You are sure that threads are running on multiple CPUs
Java doesn’t provide a way to determine or control this
Concurrent Programming in Java
61
Guarding via Suspension
class GuardedBoundedCounter {
protected long count_ = MIN;
synchronized long value() { return count_; }
synchronized void inc()
throws InterruptedException {
while (count_ >= MAX) wait();
++count_;
notifyAll();
}
synchronized void dec()
throws InterruptedException {
while (count_ <= MIN) wait();
--count_;
notifyAll();
}
}
Each wait relies on a balancing notification
Generates programmer obligations
Must recheck condition upon resumption
Concurrent Programming in Java
62
Java Monitor Methods
Every Java Object has a wait set
Accessed only via monitor methods, that can only be
invoked under synchronization of target
wait()
Suspends thread
Thread is placed in wait set for target object
Synch lock for target is released
notify()
If one exists, any thread T is chosen from target’s wait set
Tmust re-acquire synch lock for target
Tresumes at wait point
notifyAll() is same as notify() except all threads chosen
wait(ms)is same as wait() except thread is automatically notified
after ms milliseconds if not already notified
Thread.interrupt causes a wait (also sleep,join) to abort.
Same as notify except thread resumed at the associated catch
Concurrent Programming in Java
63
Monitors and Wait Sets
class X {
synchronized void w() {
before(); wait(); after();
}
synchronized void n() { notifyAll(); }
}
One possible trace for three threads accessing instance x:
before();
wait();
after();
enter
x.w()
before();
wait();
after();
enter
x.n()
notifyAll();
T1 T2 T3
x
waitset
T1 T2
enter
x.w()
release lock
release lock
acquire lock acquire lock
Concurrent Programming in Java
64
Interactions with Interruption
Effect of Thread.interrupt():
If thread not waiting, set the isInterrupted() bit
If thread is waiting, force to exit wait and throw
InterruptedException upon resumption
Acquiring Running Waiting
Acquiring
Lock +
Interrupted
Running
interrupted
Interrupt Thread.interrupted, wait
Interrupt
wait
enterAcquire
notify, notifyAll, timeout, interrupt
exitAcquire
enterAcquire
exitAcquire
interrupt interrupt
+
Lock
Concurrent Programming in Java
65
Fairness in Java
Fairness is a system-wide progress property:
Each blocked activity will eventually continue when its
enabling condition holds.
(Many variants of definition)
Threads waiting for lock eventually enter when lock free
Guarded wait loops eventually unblock when condition true
Usually implemented via First-in-First-Out scheduling policies
FIFO lock and wait queues
Sometimes, along with preemptive time-slicing
Java does not guarantee fairness
Potential starvation
A thread never gets a chance to continue because other
threads are continually placed before it in queue
FIFO usually not strictly implementable on SMPs
But JVM implementations usually approximate fairness
Manual techniques available to improve fairness properties
Concurrent Programming in Java
66
Timeouts
Intermediate points between balking and guarding
Can vary timeout parameter from zero to infinity
Useful for heuristic detection of failures
Deadlocks, crashes, I/O problems, network disconnects
But cannot be used for high-precision timing or deadlines
Time can elapse between wait and thread resumption
Java implementation constraints
wait(ms)does not automatically tell you if it returns
because of notification vs timeout
Must check for both. Order and style of checking can
matter, depending on
If always OK to proceed when condition holds
If timeouts signify errors
Concurrent Programming in Java
67
Timeout Example
class TimeOutBoundedCounter {
protected long TIMEOUT = 5000;
// ...
synchronized void inc() throws Failure {
if (count_ >= MAX) {
long start = System.currentTimeMillis();
long waitTime = TIMEOUT;
for (;;) {
if (waitTime <= 0) throw new Failure();
try { wait(waitTime); }
catch (InterruptedException e) {
throw new Failure();
}
if (count_ < MAX) break;
long now = System.currentTimeMillis();
waitTime = TIMEOUT - (now - start);
}
}
++count_;
notifyAll();
}
synchronized void dec() throws Failure;//similar
}
Concurrent Programming in Java
68
Buffer Supporting Multiple Policies
class BoundedBuffer {
Object[] data_;
int putPtr_ = 0, takePtr_ = 0, size_ = 0;
BoundedBuffer(int capacity) {
data_ = new Object[capacity];
}
protected void doPut(Object x){ // mechanics
data_[putPtr_] = x;
putPtr_ = (putPtr_ + 1) % data_.length;
++size_;
notifyAll();
}
protected Object doTake() { // mechanics
Object x = data_[takePtr_];
data_[takePtr_] = null;
takePtr_ = (takePtr_ + 1) % data_.length;
--size_;
notifyAll();
return x;
}
boolean isFull(){ return size_ == data_.length;}
boolean isEmpty(){ return size_ == 0; }
Concurrent Programming in Java
69
Buffer (continued)
synchronized void put(Object x)
throws InterruptedException {
while (isFull()) wait();
doPut(x);
}
synchronized Object take() {
throws InterruptedException {
while (isEmpty()) wait();
return doTake();
}
synchronized boolean offer(Object x) {
if (isFull()) return false;
doPut(x);
return true;
}
synchronized Object poll() {
if (isEmpty()) return null;
return doTake();
}
Concurrent Programming in Java
70
Buffer (continued)
synchronized boolean offer(Object x, long ms) {
if (isFull()) {
if (ms <= 0) return false;
long start = System.currentTimeMillis();
long waitTime = ms;
for (;;) {
try { wait(waitTime); }
catch (InterruptedException e) {
return false;
}
if (!isFull()) break;
long now = System.currentTimeMillis();
waitTime = ms - (now - start);
if (waitTime <= 0) return false;
}
}
return doTake();
}
synchronized Object poll(long ms); // similar
}
Concurrent Programming in Java
71
Containment
Structurally guarantee exclusive access to internal objects
Control their visibility
Provide concurrency control for their methods
Applications
Wrapping unsafe sequential code
Eliminating need for locking ground objects and variables
Applying special synchronization policies
Applying different policies to the same mechanisms
outer part2
subpart1
part1
client
client
lock
Concurrent Programming in Java
72
Containment Example
class Pixel {
private final java.awt.Point pt_;
Pixel(int x, int y) { pt_ = new Point(x, y); }
synchronized Point location() {
return new Point(pt_.x, pt_.y);
}
synchronized void moveBy(int dx, int dy){
pt_.x += dx; pt_.y += dy;
}
}
Pixel provides synchronized access to Point methods
The reference to Point object is immutable, but its fields
are in turn mutable (and public!) so is unsafe without
protection
Must make copies of inner objects when revealing state
This is the most common way to use java.awt.Point,
java.awt.Rectangle, etc
Concurrent Programming in Java
73
Implementing Containment
Strict containment creates islands of isolated objects
Applies recursively
Allows inner code to run faster
Inner code must be communication-closed
No unprotected calls in to or out from island
Outer objects must never leak identities of inner objects
Can be difficult to enforce and check
Outermost objects must synchronize access
Otherwise, possible thread-caching problems
Seen in concurrent versions of many delegation-based patterns
Adapters, decorators, proxies
Concurrent Programming in Java
74
Hierarchical Locking
Applies when logically contained parts are not hidden from clients
Avoids deadlocks that could occur if parts fully synchronized
Can eliminate this potential deadlock if all locking in all
methods in all Parts relies on the common owner’s lock.
Extreme case: one Giant Lock for entire subsystem
Can use either internal or external conventions
owner
part2
subpart1
part1
client
client
part1 part2
m()
part1 part2
m()
part1 holds self lock
needs part2 lock
part2 holds self lock
needs part1 lock
Concurrent Programming in Java
75
Internal Hierarchical Locking
Visible components protect themselves using their owners’ locks:
class Part {
protected Container owner_; // never null
public Container owner() { return owner_; }
void bareAction() { /* ... unsafe ... */ }
public void m() {
synchronized(owner()) { bareAction(); }
}
}
Or implement using inner classes — Owner is outer class:
class Container {
class Part {
public void m() {
synchronized(Container.this){ bareAction();}
} } }
Can extend to frameworks based on shared Lock objects,
transaction locks, etc rather than synchronized blocks
Concurrent Programming in Java
76
External Hierarchical Locking
Rely on callers to provide the locking
class Client {
void f(Part p) {
synchronized (p.owner()) { p.bareAction(); }
}
}
Used in AWT
java.awt.Component.getTreeLock()
Can sometimes avoid more locking overhead, at price of fragility
Can manually minimize use of synchronized
Requires that all callers obey conventions
Effectiveness is context dependent
Breaks encapsulation
Doesn’t work with fancier schemes that do not directly
rely on synchronized blocks or methods for locking
Concurrent Programming in Java
77
Containment and Monitor Methods
class Part {
protected boolean cond_ = false;
synchronized void await() {
while (!cond_)
try { wait(); }
catch(InterruptedException ex) {}
}
synchronized void signal(boolean c) {
cond_ = c; notifyAll();
}
}
class Whole {
final Part part_ = new Part();
synchronized void rely() { part_.await(); }
synchronized void set(boolean c){
part_.signal(c); }
}
What happens when Whole.rely() called?
Concurrent Programming in Java
78
Nested Monitors
If thread T calls whole.rely
•Itwaits within part
The lock to whole is retained while T is suspended
No other thread will ever unblock it via whole.set
Nested Monitor Lockout
Policy clash between guarding by Part and containment by Whole
Never wait on a hidden contained object in Java while holding lock
whole
part
wait set:
T ...
holds lock to
Concurrent Programming in Java
79
Avoiding Nested Monitors
Adapt internal hierarchical locking pattern
Can use inner classes, where Part waits in Wholes monitor
class Whole { // ...
class Part { // ...
public void await() {
synchronized (Whole.this) {
while (...) Whole.this.wait() // ...
} } }
Create special Condition objects
Condition methods are never invoked while holding locks
Some concurrent languages build in special support for
Condition objects
But generally only deal with one-level nesting
Can build Condition class library in Java
Concurrent Programming in Java
80
Splitting Objects and Locks
Synopsis
Isolate independent aspects of state and/or behavior of a
host object into helper objects
The host object delegates to helpers
The host may change which helpers it uses dynamically
Applications
Atomic state updates
Conservative and optimistic techniques
Avoiding deadlocks
Offloading locks used for status indicators, etc
Improving concurrency
Reducing lock contention for host object
Reducing granularity
Enabling fine-grained concurrency control
Concurrent Programming in Java
81
Isolating Dependent Representations
Does Location provide strong enough semantic guarantees?
class Location { // repeated
private double x_, y_;
synchronized double x() { return x_; }
synchronized double y() { return y_; }
synchronized void moveBy(double dx, double dy) {
x_ += dx; y_ += dy;
}
}
No protection from interleaving problems such as:
Thread 1: x=loc.x(); ...............; y=loc.y();
Thread 2: .........; loc.moveBy(1,6);.........;
Thread 1 can have incorrect view (old x, new y)
Avoid by splitting out dependent representations in separate class
Location
XY xy()
XY
x()
xy
moveBy(dx, dy)
y()
Concurrent Programming in Java
82
Conservative Representation Updates
class XY { // immutable
private final double x_, y_;
XY(double x, double y) { x_ = x; y_ = y; }
double x() { return x_; }
double y() { return y_; }
}
class LocationV2 {
private XY xy_;
LocationV2(double x, double y) {
xy_ = new XY(x, y);
}
synchronized XY xy() { return xy_; }
synchronized void moveBy(double dx,double dy) {
xy_ = new XY(xy_.x() + dx, xy_.y() + dy);
}
}
Locking moveBy() ensures that the two accesses of xy_ do not
get different points
Locking xy() avoids thread-cache problems by clients
Concurrent Programming in Java
83
Optimistic Representation Updates
class LocationV3 {
private XY xy_;
private synchronized boolean commit(XY oldp,
XY newp){
boolean success = (xy_ == oldp);
if (success) xy_ = newp;
return success;
}
LocationV3(double x,double y){xy_=new XY(x,y);}
synchronized XY xy() { return xy_; }
void moveBy(double dx,double dy) {
while (!Thread.interrupted()){
XY oldp = xy();
XY newp = new XY(oldp.x()+dx, oldp.y()+dy);
if (commit(oldp, newp)) break;
Thread.yield();
}
}
}
Concurrent Programming in Java
84
Optimistic Update Techniques
Every public state update method has four parts:
Record current version
Easiest to use reference to immutable representation
Or can assign version numbers, transaction IDs, or time
stamps to mutable representations
Build new version, without any irreversible side effects
All actions before commit must be reversable
Ensures that failures are clean (no side effects)
No I/O or thread construction unless safely cancellable
All internally called methods must also be reversable
Commit to new version if no other thread changed version
Isolation of state updates to single atomic commit method
can avoid potential deadlocks
Otherwise fail or retry
Retries can livelock unless proven
wait-free
in given
context
Concurrent Programming in Java
85
Optimistic State-Dependent Policies
As with optimistic updates, isolate state
into versions, and isolate state
changes to commit method
In each method:
Record current version
Build new version
Commit to version if success and
no one changed version
Otherwise fail or retry
Retry policy is a tamed busy wait. Can be
more efficient than guarded waits if
Conflicts are rare
Guard conditions usually hold
Running on multiple CPUs
aMessage
return
client host
... actions...
throw
inRightState
!inRightState
... undo...
Concurrent Programming in Java
86
Optimistic Counter
class OptimisticBoundedCounter {
private Long count_ = new Long(MIN);
long value() { return count().longValue(); }
synchronized Long count() { return count_;}
private synchronized boolean commit(Long oldc,
Long newc){
boolean success = (count_ == oldc);
if (success) count_ = newc;
return success;
}
public void inc() throws InterruptedException{
for (;;) { // retry-based
if (Thread.interrupted())
throw new InterruptedException();
Long c = count();
long v = c.longValue();
if (v < MAX && commit(c, new Long(v+1)))
break;
Thread.yield();
}
}
public void dec() // symmetrical
}
Concurrent Programming in Java
87
Splitting Locks and Behavior
Associate a helper object with an independent subset of state and
functionality.
Delegate actions to helper via pass-through method
class Shape {
// Assumes size & dimension are independent
int height_ = 0;
int width_ = 0;
synchronized void grow() { ++height_; ++width_;}
Location l = new Location(0,0); // fully synched
void shift() { l.moveBy(1, 1); } // Use l’s synch
}
grow and shift can execute simultaneously
When there is no existing object to delegate independent actions:
Use an arbitrary Object as a lock, and protect associated
methods using synchronized block on that lock
Useful for concurrent data structures
Concurrent Programming in Java
88
Concurrent Queue
class TwoLockQueue {
final static class Node {
Object value; Node next = null;
Node(Object x) { value = x; }
}
private Node head_ = new Node(null); // dummy hdr
private Node last_ = head_;
private Object lastLock_ = new Object();
void put(Object x) {
synchronized (lastLock_) {
last_ = last_.next = new Node(x);
}
}
synchronized Object poll() { // null if empty
Object x = null;
Node first = head_.next; // only contention pt
if (first != null) {
x = first.value; first.value = null;
head_ = first; // old first becomes header
}
return x;
}
}
Concurrent Programming in Java
89
Concurrent Queue (continued)
puts and polls can run concurrently
The data structure is crafted to avoid contending access
Rely on Java atomicity guarantees at only potential
contention point
But multiple puts and multiple polls disallowed
Weakens semantics
poll may return null if another thread is in midst of put
Balking policy for poll is nearly forced here
But can layer on blocking version
next
head last
hdr first
value
(null)
queue
... (null)
Concurrent Programming in Java
90
Introducing Concurrency into
Applications
Three sets of patterns
Each associated with a reason to introduce concurrency
Autonomous Loops
Establishing independent cyclic behavior
Oneway messages
Sending messages without waiting for reply or termination
Improves availability of sender object
Interactive messages
Requests that later result in reply or callback messages
Allows client to proceed concurrently for a while
Most design ideas and semantics stem from active object models.
Concurrent Programming in Java
91
Autonomous Loops
Simple non-reactive active objects contain a run loop of form:
public void run() {
while (!Thread.interrupted())
doSomething();
}
Normally established with a constructor containing:
new Thread(this).start();
Perhaps also setting priority and daemon status
Normally also support other methods called from other threads
Requires standard safety measures
Common Applications
Animations
Simulations
Message buffer Consumers
Polling daemons that periodically sense state of world
Concurrent Programming in Java
92
Autonomous Particle Class
public class Particle implements Runnable {
private int x = 0, y = 0;
private Canvas canvas;
public Particle(Canvas host) { canvas = host; }
synchronized void moveRandomly() {
x += (int) (((Math.random() - 0.5) * 5);
y += (int) (((Math.random() - 0.5) * 5);
}
public void draw(Graphics g) {
int lx, ly;
synchronized (this) { lx = x; ly = y; }
g.drawRect(lx, ly, 10, 10);
}
public void run() {
for(;;) {
moveRandomly();
canvas.repaint();
try { Thread.sleep((int)(Math.random()*10);}
catch (InterruptedException e) { return; }
}
}
}
Concurrent Programming in Java
93
Particle Applet
import java.awt.*;
import java.applet.*;
public class ParticleApplet extends Applet {
public void init() {
add(new ParticleCanvas(10));
}
}
class ParticleCanvas extends Canvas {
Particle[] particles;
ParticleCanvas(int nparticles) {
setSize(new Dimension(100, 100));
particles = new Particle[nparticles];
for (int i = 0; i < particles.length; ++i) {
particles[i] = new Particle(this);
new Thread(particles[i]).start();
}
}
public void paint(Graphics g) {
for (int i = 0; i < particles.length; ++i)
particles[i].draw(g);
}
}// (needs lots of embellishing to look nice)
Concurrent Programming in Java
94
Oneway Messages
Conceptually oneway messages are sent with
No need for replies
No concern about failure (exceptions)
No dependence on termination of called method
No dependence on order that messages are received
But may sometimes want to cancel messages or resulting activities
state, acquaintances
react {
update state
send message
}
accept oneway
Client
Handler
Host
Concurrent Programming in Java
95
Oneway Message Styles
Some semantics choices
Asynchronous: Entire message send is independent
By far, most common style in reactive applications
Synchronous: Caller must wait until message is
accepted
Basis for rendezvous protocols
Multicast: Message is sent to group of recipients
The group might not even have any members
Events Mouse clicks, etc
Notifications Status change alerts, etc
Postings Mail messages, stock quotes, etc
Activations Applet creation, etc
Commands Print requests, repaint requests, etc
Relays Chain of responsibility designs, etc
Concurrent Programming in Java
96
Messages in Java
Direct method invocations
Rely on standard call/return mechanics
Command strings
Recipient parses then dispatches to underlying method
Widely used in client/server systems including HTTP
EventObjects and service codes
Recipient dispatches
Widely used in GUIs, including AWT
Request objects, asking to perform encoded operation
Used in distributed object systems — RMI and CORBA
Class objects (normally via .class files)
Recipient creates instance of class
Used in Java Applet framework
Runnable commands
Basis for thread instantiation, mobile code systems
Concurrent Programming in Java
97
Design Goals for Oneway Messages
Object-based forces
Safety
Local state changes should be atomic (normally, locked)
Typical need for locking leads to main differences vs
single-threaded Event systems
Safe guarding and failure policies, when applicable
Availability
Minimize delay until host can accept another message
Activity-based forces
Flow
The activity should progress with minimal contention
Performance
Minimize overhead and resource usage
Concurrent Programming in Java
98
Design Patterns for Oneway Messages
Thread-per-Message
Thread-per-Activity via Pass-throughs
Thread-per-Object via Worker Threads (variants: Pools, Listeners)
client handler
start
host
new thread
client host handler
same thread
client handler
host
channel
put take
worker thread
Concurrent Programming in Java
99
Reactive Methods
Code scaffolding for illustrating patterns:
class Host {
// ...
private long localState_; // Or any state vars
private Handler handler_; // Message target
public void react(...) {
updateState(...);
sendMessage(...);
}
private synchronized void updateState(...) {
// Assign to localState_;
}
private void sendMessage(...) {
// Issue handler.process(...)
}
}
react() may be called directly from client, or indirectly after
decoding command, event, etc
Concurrent Programming in Java
100
Thread-per-Message
class Host { //...
public void react(...) {
updateState(...);
sendMessage(...);
}
synchronized void sendMessage(...) {
Runnable command = new Runnable() { // wrap
final Handler dest = handler_;
public void run() {
dest.process(...);
}
};
new Thread(command).start(); // run
}
}
Runnable is the standard Java interface describing argumentless,
resultless command methods (aka
closures
,
thunks
)
Synchronization of sendMessage desirable if handler_ or
process() arguments not fixed/final
Variants: Thread-per-connection (sockets)
Concurrent Programming in Java
101
Thread-per-Message Protocol
client host command
start/run
handler
... updateState...
react
process
Concurrent Programming in Java
102
Multicast TPM
Multicasts can either
Generate one thread per message, or
Use a single thread for all messages
Depends on whether OK to wait each one out before sending
next one
client host handlers
react
return
Concurrent Programming in Java
103
TPM Socket-based Server
class Server implements Runnable {
public void run() {
try {
ServerSocket socket = new ServerSocket(PORT);
for (;;) {
final Socket connection = socket.accept();
new Thread(new Runnable() {
public void run() {
new Handler().process(connection);
}}).start();
}
}
catch(Exception e) { /* cleanup; exit */ }
}
}
class Handler {
void process(Socket s) {
InputStream i = s.getInputStream();
OutputStream o = s.getOutputStream();
// decode and service request, handle errors
s.close();
}
}
Concurrent Programming in Java
104
Thread Attributes and Scheduling
Each Thread has an integer priority
•FromThread.MIN_PRIORITY to Thread.MAX_PRIORITY
(currently 1 to 10)
Initial priority is same as that of the creating thread
Can be changed at any time via setPriority
ThreadGroup.setMaxPriority establishes a ceiling for
all threads in the group
JVM schedulers give preference to threads with higher priority
But
preference
is left vague, implementation-dependent
No guarantees about fairness for equal-priority threads
Time-slicing is permitted but not required
No guarantees whether highest-priority or longest-waiting
threads acquire locks or receive notifications before others
Priorities can only be used heuristically
Build custom Queues to control order of sequential tasks
Build custom Conditions to control locking and notification
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Adding Thread Attributes
Thread objects can hold non-public Thread-Specific contextual
attributes for all methods/objects running in that thread
Normally preferable to static variables
Useful for variables that apply per-activity, not per-object
Timeout values, transaction IDs, Principals, current
directories, default parameters
Useful as tool to eliminate need for locking
Used internally in JVMs to optimize memory allocation,
locks, etc via per-thread caches
Thread
specific
attributes
Thread
specific
attributes
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Implementing Thread-Specific Storage
class GameThread extends Thread { // ...
private long movementDelay_ = 3;
static GameThread currentGameThread() {
return (GameThread)(Thread.currentThread());
}
static long getDelay() {
return currentGameThread().movementDelay_;
}
static long setDelay(long t) {
currentGameThread().movementDelay_ = t;
}
}
class Ball { // ...
void move() { // ...
Thread.sleep(GameThread.getDelay()));
}
}
class Main { ... new GameThread(new Game()) ... }
Define contextual attributes in special Thread subclasses
Can be accessed without locking if all accesses are always
via Thread.currentThread()
Enforce via static methods in Thread subclass
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Using ThreadLocal
java.lang.ThreadLocal available in JDK1.2
An alternative to defining special Thread subclasses
Uses internal hash table to associate data with threads
Avoids need to make special Thread subclasses when
adding per-thread data
Trade off flexibility vs strong typing and performance
class Ball {
static ThreadLocal delay = new ThreadLocal();
void move() { // ...
if (delay.get()==null) delay.set(new Long(3));
long d = ((Long)(delay.get())).longValue();
Thread.sleep(d);
}
}
Can extend to implement inherited Thread contexts
Where new threads by default use attributes of the parent
thread that constructed them
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Other Scoping Options
Choices for maintaining context information
per Object
per Method
per Class
per Principal
per Application
per Session
per System
per Group
per Thread
per Aggregate
per Role
per Block per Domain
per Version
per Site
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Choosing among Scoping Options
Reusability heuristics
Responsibility-driven design
Factor commonalities, isolate variation
Simplify Programmability
Avoid long parameter lists
Avoid awkward programming constructions
Avoid opportunities for errors due to policy conflicts
Automate propagation of bindings
Conflict analysis
Example: Changing per-object bindings via tuning interfaces
can lead to conflicts when objects support multiple roles
Settings made by one client impact others
Common error with Proxy objects
Replace with per-method, per-role, per-thread
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Thread-per-Activity via Pass-Throughs
class Host { //...
void reactV1(...) { // no synch
updateState(); // isolate in synched method
sendMessage(...);
}
void sendMessage(...) { // no synch
handler_.process(...); // direct call
}
}
A kind of forwarding — conceptually removing host from call chain
Callers of react must wait
for handler.process
to terminate, or
generate their own
threads
Host can respond to
another react call from
another thread
immediately after
updating state
client host
process
handler
... updateState...
react
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Using Pass-Throughs
Common approach to writing AWT Event handlers, JavaBeans
methods, and other event-based components.
But somewhat fragile:
There is no “opposite” to synchronized
Avoid self calls to react from synchronized methods
Need care in accessing representations at call-point
—Ifhandler_ variable or process arguments not fixed,
copy values to locals while under synchronization
Callers must be sure to create thread around call if they
cannot afford to wait or would lock up
Variants
Bounded Thread-per-Message
Keep track of how many threads have been created. If too
many, fall back to pass-through.
Mediated
Register handlers in a common mediator structured as a
pass-through.
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Multicast Pass-Throughs
class Host { //...
CopyOnWriteSet handlers_;
synchronized void addHandler(Handler h) {
handlers_.add(h); // copy
}
void sendMessage(...) {
Iterator e = handlers_.iterator();
while (e.hasNext())
((Handler)(e.next())).process(...);
}
}
Normally use copy-on-write to implement target collections
Additions are much less common than traversals
AWT uses java.awt.AWTEventMulticaster class
Employs variant of FixedList class design
But coupled to AWT Listener framework, so cannot be
used in other contexts
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Thread-Per-Object via Worker Threads
Establish a producer-consumer chain
Producer
Reactive method just places message in a channel
Channel might be a buffer, queue, stream, etc
Message might be a Runnable command, event, etc
Consumer
Host contains an autonomous loop thread of form:
while (!Thread.interrupted()) {
m = channel.take();
process(m);
}
Common variants
Pools
Use more than one worker thread
Listeners
Separate producer and consumer in different objects
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Worker Thread Example
interface Channel { // buffer, queue, stream, etc
void put(Object x);
Object take();
}
class Host { //...
Channel channel_ = ...;
void sendMessage(...) {
channel_.put(new Runnable() { // enqueue
public void run(){
handler_.process(...);
}});
}
Host() { // Set up worker thread in constructor
// ...
new Thread(new Runnable() {
public void run() {
while (!Thread.interrupted())
((Runnable)(channel_.take())).run();
}
}).start();
}
}
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Worker Thread Protocol
client host command
put
handler
... updateState...
react
process
channel
take
run
!empty
run
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116
Channel Options
Unbounded queues
Can exhaust resources if clients faster than handlers
Bounded buffers
Can cause clients to block when full
Synchronous channels
Force client to wait for handler to complete previous task
Leaky bounded buffers
For example, drop oldest if full
Priority queues
Run more important tasks first
Streams or sockets
Enable persistence, remote execution
Non-blocking channels
Must take evasive action if put or take fail or time out
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Example: The AWT Event Queue Thread
AWT uses one thread and a single java.awt.EventQueue
Single thread makes visual updates appear more coherent
Browsers
may
add per-Applet threads and queues
Events implement java.util.EventObject
Include both ‘‘Low-level’’ and ‘‘Semantic’’ events
Event dequeuing performed by AWT thread
repaint() places drawing request event in queue.
The request may beoptimized away if one already there
update/paint is called when request dequeued
Drawing is done by AWT thread, not your threads
mouseEvent
click
AWT queue
actionPerformed(e) {
applet
dequeue button ... dispatch ...
}
anEvent
anEvent
AWT Thread
pass-through
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AWT Example
class MyApplet extends Applet
implements ActionListener {
Button button = new Button(“Push me”);
boolean onOff = false;
public void init() {
button.addActionListener(this); // attach
add(button); // add to layout
}
public void ActionPerformed(ActionEvent evt) {
if (evt.getSource() == button) // dispatch
toggle(); // update state
repaint(); // issue event(not necessary here)
}
synchronized void toggle() {
onOff = !onOff;
}
}
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Using AWT in Concurrent Programs
Most conservative policy is to perform all GUI-related state updates
in event handling methods
Define and generate new EventObjects if necessary
Consider splitting GUI-related state into separate classes
Do not rely on thread-safety of GUI components
Define drawing and event handling methods in reactive form
Do not hold locks when sending messages
Do not block or delay caller thread (the AWT thread)
Generate threads to arrange GUI-unrelated processing
Explicitly set their ThreadGroups
Generate events to arrange GUI-related asynch processing
Swing
includes some utility classes to make this easier
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Thread Pools
Use a collection of worker threads, not just one
Can limit maximum number and priorities of threads
Often faster than thread-per-message
But slower than single thread working off a multislot buffer
unless handler actions permit parallelism
Often works well for I/O-bound actions
handler
channel
put
take
handler
client
handler
handler
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Listeners
House worker thread in a different object
Even in a different process, connected via socket
But full support for remote listeners requires frameworks for
Naming remote acquaintances (via registries, jndi etc)
Failure, reliability, fault tolerance
Security, protocol conformance, ...
Can make more transparent via Proxies
Channels/Listeners that duplicate interface of Handler, but
wrap each message as queued command for later
execution
client handler
host
channel
put take
worker thread
listener
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122
Remote Worker Threads
class Host { // ...
ObjectOutputStream c; // connected to a Socket
void sendMessage(...) {
c.writeObject(new SerializableRunnable() {
public void run(){
new Handler().process(...);
}
});
}
}
class Listener { // instantiate on remote machine
ObjectInputStream c; // connected to a Socket
Listener() {
c = new ...
Thread me = new Thread(new Runnable() {
public void run() {
for (;;) {
((Runnable)(c.readObject())).run();
}}});
me.start();
}
}
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Synchronous Channels
Synchronous oneway messages same as asynchronous, except:
Caller must wait at least until message is accepted
Simplest option is to use synchronized methods
Caller must wait out all downstream processing
Increase concurrency via synchronous channel to worker thread
Every put must wait for take
Every take must wait for put
Basis for synchronous message passing frameworks (CSP etc)
Enables more precise, deterministic, analyzable, but
expensive flow control measures.
Relied on in part because CSP-inspired systems did not
allow dynamic construction of new threads, so required
more careful management of existing ones.
Variants
Barrier: Threads wait but do not exchange information
Rendezvous: Bidirectional message exchange at wait
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Synchronous Channel Example
class SynchronousChannel {
Object item_ = null;
boolean putting_ = false;//disable multiple puts
synchronized void put(Object e) {
if (e == null) return;
while (putting_) try { wait(); } catch ...
putting_ = true;
item_ = e;
notifyAll();
while (item_ != null) try { wait(); } catch ...
putting_ = false;
notifyAll();
}
synchronized Object take() {
while (item_ == null) try { wait(); } catch ...
Object e = item_;
item_ = null;
notifyAll();
return e;
}
}
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Some Pattern Trade-Offs
Thread-per-
Message Pass-Through Worker Threads
+ Simple
semantics:
When in doubt,
make a new
thread
- Can be hard to
limit resource
usage
- Thread start-up
overhead
+ Low overhead
- Fragile
- No within-activity
concurrency
+ Tunable
semantics and
structure
+ Can bound
resource
usage
- Higher overhead
- Can waste
threads
- May block caller
(if buffer full
etc)
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126
Interactive Messages
Synopsis
Client activates Server with a oneway message
Server later invokes a callback method on client
Callback can be either oneway or procedural
Callback can instead be sent to a helper object of client
Degenerate case: inform only of task completion
Applications
Observer designs
Completion indications from file and network I/O
Threads performing computations that yield results
client server
oneway
callback
client server
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Observer Designs
The oneway calls are change
notifications
The callbacks are state queries
Examples
Screen updates
Constraint frameworks
Publish/subscribe
Hand-built variants of
wait and notifyAll
Notifications must use oneway
design pattern
Otherwise:
changeNotification
currentValue
display
changeValue(v)
return
subject
val==v
cache == val
observer
return(val)
changeNotification
currentValue
val==v
thread1
thread2
can deadlock against:
Concurrent Programming in Java
128
Observer Example
class Subject {
protected double val_ = 0.0; // modeled state
public synchronized double getValue(){
return val_;}
protected synchronized void setValue(double d){
val_ = d;}
protected CopyOnWriteSet obs_ = new COWImpl();
public void attach(Observer o) { obs_.add(o); }
public void changeValue(double newstate) {
setValue(newstate);
Iterator it = obs_.iterator();
while (it.hasNext()){
final Observer o = (Observer)(it.next());
new Thread(new Runnable() {
public void run() {
o.changeNotification(this);
}
}).start();
}
}
}// More common to use pass-through calls instead of threads
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Observer Example (Continued)
class Observer {
protected double cachedState_;//last known state
protected Subject subj_; // only one here
Observer(Subject s) {
subj_ = s; cachedState_ = s.getValue();
display();
}
synchronized void changeNotification(Subject s){
if (s != subj_) return; // only one subject
double oldState = cachedState_;
cachedState_ = subj_.getValue(); // probe
if (oldState != cachedState_) display();
}
synchronized void display() { // default version
System.out.println(cachedState_);
}
}
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Completion Callbacks
The asynch messages are service
activations
The callbacks are continuation
calls that transmit results
May contain a message
ID or completion token to
tell client which task has
completed
Typically two kinds of callbacks
Success – analog of return
Failure – analog of throw
Client readiness to accept
callbacks may be state-
dependent
For example, if client can
only process callbacks in
a certain order
app
client
start/run
server
return
completed
failed
success
failure
return
return
... try action...
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131
Completion Callback Example
Callback interface
interface FileReaderClient {
void readCompleted(String filename);
void readFailed(String filename,IOException ex);
}
Sample Client
class FileReaderApp implements FileReaderClient {
private byte[] data_;
void readCompleted(String filenm) {
// ... use data ...
}
void readFailed(String fn, IOException e){
// ... deal with failure ...
}
void app() {
new Thread(new FileReader(“file”,
data_,this)).start();
}
}
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132
Completion Callbacks (continued)
Sample Server
class FileReader implements Runnable {
final String nm_;
final byte[] d_;
final FileReaderClient client_; // allow null
public FileReader(String name, byte[] data,
FileReaderClient c) {
nm_ = name; d_ = data; client_ = c;
}
void run() {
try {
// ... read...
if (client_ != null)
client_.readCompleted(nm_);
}
catch (IOException ex) {
if (client_ != null)
client_.readFailed(nm_, ex);
}
}
}
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133
Threads and I/O
Java I/O calls generally block
Thread.interrupt causes them to unblock
(This is broken in many Java implementations)
Time-outs are available for some Socket operations
Socket.setSoTimeOut
Can manually set up classes to arrange time-out interrupts
for other kinds of I/O
Common variants of I/O completion callbacks
Issue callback whenever there is enough data to process,
rather than all at once
Send a Runnable completion action instead of callback
Use thread pools for either I/O or completion actions
Alternatives
Place the I/O and the subsequent actions all in same
method, run in same thread.
Read into a buffer serviced by a worker thread
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Rerouting Exceptions
Callbacks can be used instead of exceptions in any asynchronous
messaging context, not just those directly constructing threads
Variants seen in Adaptors that call methods throwing exceptions
that clients do not know how to handle:
interface Server { void svc() throws SException; }
interface EHandler { void handle(Exception e); }
class SvcAdapter {
Server server = new ServerImpl();
EHandler handler;
void attachHandler(EHandler h) { handler = h; }
public void svc() { // no throw clause
try { server.svc(); }
catch (SException e) {
if (handler != null) handler.handle(e); }
}
}
Pluggable Handlers can do anything that a normal catch clause can
Including cancelling all remaining processing in any thread
But are less structured and sometimes more error-prone
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135
Joining Threads
Thread.join() may be used instead of callbacks when
Server does not need to call back client with results
But client cannot continue until service completion
Usually the easiest way to express termination dependence
No need to define callback interface or send client ref as
argument
No need for server to explicitly notify or call client
Internally implemented in java by
t.join() calls t.wait()
terminating threads call notifyAll()
Can use to simulate futures and deferred calls found in other
concurrent OO languages
But no syntactic support for futures
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Join Example
public class PictureDisplay {
private final PictureRenderer myRenderer_;
// ...
public void show(final byte[] rawPic) {
class Waiter implements Runnable {
Picture result = null;
public void run() {
result = myRenderer_.render(rawPic); }
};
Waiter waiter = new Waiter();
Thread t = new Thread(waiter);
t.start();
displayBorders(); // do other things
displayCaption(); // while rendering
try { t.join(); }
catch(InterruptedException e) { return; }
displayPicture(waiter.result);
}
}
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137
Join Protocol
show
picturedisplay waiter renderer
return(im)
join
return
displayPicture(result)
start thread
run
render
... other actions...
return
isAlive
!isAlive
!isAlive
...
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138
Futures
Encapsulate waits for results of operations performed in threads
Futures are ‘‘data’’ types that wait until results ready
Normally requires use of interfaces for types
Clients wait only upon trying to use results
interface Pic { byte[] getImage(); }
interface Renderer { Pic render(byte[] raw); }
class AsynchRenderer implements Renderer {
static class FuturePic implements Pic { //inner
byte[] img_ = null;
synchronized void setImage(byte[] img) {
img_ = img;
notifyAll();
}
public synchronized byte[] getImage() {
while (img_ == null)
try { wait(); }
catch (InterruptedException e) { ... }
return img_;
}
} // continued
Concurrent Programming in Java
139
Futures (continued)
// class AsynchRender, continued
public Pic render(final byte[] raw) {
final FuturePic p = new FuturePic();
new Thread(new Runnable() {
public void run() {
p.setImage(doRender(raw));
}
}).start();
return p;
}
private Pic doRender(byte[] r); // ...
}
class App { // sample usage
void app(byte[] r) {
Pic p = new AsynchRenderer().render(r);
doSomethingElse();
display(p.getImage()); // wait if not yet ready
}
}
Could alternatively write join-based version.
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140
Cancellation
Threads normally terminate after completing their run methods
May need to cancel asynchronous activities before completion
Applet.stop() called
User hits a
CANCEL
button
Threads performing computations that are not needed
I/O or network-driven activites that encounter failures
Options
Asynchronous cancellation: Thread.stop
Polling and exceptions: Thread.interrupt
Terminating program: System.exit
Minimizing contention: setPriority(MIN_PRIORITY)
Revoking permissions: SecurityManager methods
Unlinking resources known to cause failure exceptions
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Asynchronous Cancellation
Thread.stop stops thread by throwing ThreadDeath exception
Deprecated in JDK1.2 because it can corrupt object state:
class C {
private int v; // invariant: v >= 0
synchronized void f() {
v = -1; // temporarily set to illegal value
compute(); // call some other method
v = 1; // set to legal value
}
synchronized void g() { // depend on invariant
while (v != 0) { --v; something(); } }
}
What happens if stop occurs during compute()?
In principle, could catch(ThreadDeath)
But this would only work well if done after just about every
line of code in just about every Java class. Impractical.
Most other thread systems (including POSIX) either do not
support or severely restrict asynchronous cancellation
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142
Interruption
Safety can be maintained by each object checking cancellation
status only when in an appropriate state to do so, relying on:
thread.isInterrupted
Returns current interruption status.
(static) Thread.interrupted
Clears
status for current thread, returning previous status.
thread.interrupt
Sets interrupted status, and also causes applicable
methods to throw InterruptedException
Threads that are blocked waiting for synchronized
method or block entry are NOT awakened by interrupt
InterruptedException
Thrown by Thread.sleep,Thread.join,Object.wait
if blocked during interruption, also clearing status
Blocking IO methods in the java.io package respond to
interrupt by throwing InterruptedIOException
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143
Implementing a Cancellation Policy
Best-supported policy is:
Thread.isInterrupted() means cancelled
Any method sensing interruption should
Assume current task is cancelled.
Exit as quickly and cleanly as possible.
Ensure that callers are aware of cancellation. Options:
Thread.currentThread().interrupt()
throw new InterruptedException()
Alternatives
Local recovery and continuation
Centralized error recovery objects
Always ignoring/resetting status
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144
Detecting Cancellation
Cancellation can be checked as a precondition for any method
if (Thread.currentThread().isInterrupted())
cancellationCode();
Also in loop headers of looping methods, etc
Can be caught, thrown, or rethrown as an exception
try { somethingThrowingInterruptedException(); }
catch (InterruptedException ex) {
cancellationCode();
}
Or as a subclass of a general failure exception, as in
InterruptedIOException
Placement, style, and poll frequency require engineering tradeoffs
How important is it to stop now?
How hard is it to stop now?
Will another object detect and deal with at a better time?
Is it too late to stop an irreversable action?
Does it really matter if the thread is stopped?
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145
Responses to Cancellation
Early return
Clean up and exit without producing or signalling errors —
May require rollback or recovery
Callers can poll status if necessary to find out why action
was not carried out.
Reset (if necessary) interruption status before return:
Thread.currentThread().interrupt()
Continuation (ignoring cancellation status)
When it is too dangerous to stop
When partial actions cannot be backed out
When it doesn’t matter (but consider lowering priority)
Throwing InterruptedException
When callers must be alerted on method return
Throwing a general failure Exception
When interruption is one of many reasons method can fail
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Multiphase Cancellation
Foreign code running in thread might not respond to cancellation.
Dealing with this forms part of any security framework. Example:
static boolean terminate(Thread t) {
if (!t.isAlive()) return true; // already dead
// phase 1 -- graceful cancellation
t.interrupt();
try { t.join(maxWaitToDie); }
catch(InterruptedException e){} // ignore
if (!t.isAlive()) return true; // success
// phase 2 -- trap all security checks
theSecurityMgr.denyAllChecksFor(t); // made-up
try { t.join(maxWaitToDie); }
catch(InterruptedException ex) {}
if (!t.isAlive()) return true;
// phase 3 -- minimize damage
t.setPriority(Thread.MIN_PRIORITY);
// or even unsafe last-resort t.stop()
return false;
}
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147
Shutting Down Applets
Applets can create threads
usually in Applet.start
and terminate them
usually in Applet.stop
These threads should be cancellable
Otherwise, it is impossible to
predict lifecycle
No guarantees about when
browsers will destroy, or
whetherthreadsautomatically
killed when unloading
Guidelines
Explicitly cancel threads (normally in Applet.stop)
Ensure that activities check cancellation often enough
Consider last-resort Thread.stop in Applet.destroy
init
start
stop
destroy
move
off/on
page
invoke on load
main action
leave page
finalization
revisit/reload
after
finalized
instantiate
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Concurrent Application
Architectures
Establishing application- (or subsystem-) wide Policies
Communication directionality, synchronization
Avoid inconsistent case-by-case decisions
Samplings from three styles
Flow systems
Wiring together processing stages
Illustrated with Push Flow designs
Parallel execution
Partitioning independent tasks
Illustrated with Group-based designs
Layered services
Synchronization and control of ground objects
Illustrated with Before/After designs
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Push Flow Systems
Systems in which (nearly) all activities are performed by objects
issuing oneway messages along paths from sources to sinks
Each message transfers information and/or objects
Examples
Control systems
Assembly systems
Workflow systems
Event processing
Chain of command
Pipeline algorithms
Requires common directionality and locality constraints
Precludes many safety and liveness problems
Success relies on adherence to design rules
— potentially formally checkable
The simplest and sometimes best open systems protocol
supplier
invoices
approval
payment
returns
contractor
invoices
tempSensor comparator heater
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Stages in Flow Systems
Every stage is a producer and/or consumer
Stages implement common interface
with method of form
void put(Object item)
May have multiple successors
Outgoing elements may be
multicasted or
routed
May have multiple predecessors
Incoming elements may be
combined or
collected
Normally require explicit linkages
— only one stage per connection
Each stage can define put using any appropriate oneway message
implementation pattern — may differ across stages
consumer
producer put
splitter
merger
put
put
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Exclusive Ownership of Resources
Elements in most flow systems act like physical resources in that
If you have one, then you can do something (with it) that
you couldn’t do otherwise.
If you have one, then no one else has it.
If you give it to someone else, then you no longer have it.
If you destroy it, then no one will ever have it.
Examples
Invoices
Network packets
File and socket handles
Tokens
Mail messages
Money
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Accessing Resources
How should stages manage resource objects?
class Stage {
Resource res;
void put(Resource r) { /* ... */ }
}
Both reference-passing ‘‘shared memory’’ and copy-based
‘message passing’’ policies can encounter problems:
stage2
stage1 put(r) stage2
stage1 put(r)
resource resource copy
access access access access
Synchronize access to resource Deal with identity differences
Shared memory Message passing
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153
Ownership Transfer
Transfer policy
At most one stage refers to any resource at any time
Require each owner to forget about each resource after revealing it
to any other owner as message argument or return value
Implement by nulling out instance variables refering to
resources after hand-off
Or avoiding such variables
Resource Pools can be used to hold unused resources
Or just let them be garbage collected
stage2
stage1 put(r) stage2
stage1 put(r)
resource resource
access access
Before message After message
(null)
(null)
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154
Assembly Line Example
Boxes are flow elements
Have adjustable dimension and color
Can clone and draw themselves
Sources produce continuous stream of BasicBoxes
Boxes are pushed through stages
Stages paint, transform, combine into composite boxes
A viewer applet serves as the sink
See CPJ p233-248 for most code omitted here
Some code here differs in minor ways for sake of
illustration
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155
Interfaces
interface PushSource { void start(); }
interface PushStage { void putA(Box p); }
interface DualInputPushStage extends PushStage {
public void putB(Box p);
}
PushSource
start
PushStage
putA
DualInput
PushStage
putA
putB
Concurrent Programming in Java
156
Adapters
class DualInputAdapter implements PushStage {
protected final DualInputPushStage stage_;
DualInputAdapter(DualInputPushStage stage) {
stage_ = stage;
}
void putA(Box p) { stage_.putB(p); }
}
Allows all other stages to issue putA
Use adapter when necessary to convert to putB
Simplifies composition
Alternatively, could have used a single put(command) interface
Would require each stage to decode type/sense of
command
putA putB
DualInput
Adapter
Concurrent Programming in Java
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Connections
class SingleOutputPushStage {
protected PushStage next1_= null;
void attach1(PushStage s) { next1_ = s; }
}
class DualOutputPushStage
extends SingleOutputPushStage {
protected PushStage next2_ = null;
void attach2(PushStage s) { next2_ = s; }
}
Alternatively, could have used a collection (Vector etc) of nexts
We assume/require all attaches to be performed before any puts
SingleOutput
PushStage next1
DualOutput
PushStage
next1
next2
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Linear Stages
class Painter extends SingleOutputPushStage
implements PushStage {
protected final Color color_;
public Painter(Color c) {
super();
color_ = c;
}
public void putA(Box p) {
p.color(color_);
next1_.putA(p);
}
}
Painter is immutable after initialization
Painter
putA putA next1
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Dual Input Stages
public class Collector
extends SingleOutputPushStage
implements DualInputPushStage {
public synchronized void putA(Box p) {
next1_.putA(p);
}
public synchronized void putB(Box p) {
next1_.putA(p);
}
}
Synchronization used here to illustrate flow control, not safety
Collector putA
putA
putB
next1
Concurrent Programming in Java
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Joiners
class Joiner extends SingleOutputPushStage
implements DualInputPushStage {
protected Box a_ = null; // incoming from putA
protected Box b_ = null; // incoming from putB
protected abstract Box join(Box p, Box q);
protected synchronized Box joinFromA(Box p) {
while (a_ != null) // wait until last consumed
try { wait(); }
catch (InterruptedException e){return null;}
a_ = p;
return tryJoin();
}
protected synchronized Box tryJoin() {
if (a_ == null || b_ == null) return null;
Box joined = join(a_, b_); // make combined box
a_ = b_ = null; // forget old boxes
notifyAll(); // allow new puts
return joined;
}
void putA(Box p) {
Box j = joinFromA(p);
if (j != null) next1_.putA(j);
}
} // (mechanics for putB are symmetrical)
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Dual Output Stages
class Cloner extends DualOutputPushStage
implements PushStage {
protected synchronized Box dup(Box p) {
return p.duplicate();
}
public void putA(final Box p) {
Box p2 = dup(p); // synched update (not nec.)
Runnable r = new Runnable() {
public void run() { next1_.putA(p); }
};
new Thread(r).start(); // use new thread for A
next2_.putA(p2); // current thread for B
}
}
Using second thread for second output maintains liveness
Cloner
putA putA next1
next2
putA
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Configuration
All setup code is of form
Stage aStage = new Stage();
aStage.attach(anotherStage);
Would be nicer with a visual scripting tool
BBSource Painter Alternator
BBSource Painter
HorizJoin Collector
DIAdaptor
DIAdaptor
Concurrent Programming in Java
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Parallel Execution
Classic parallel programming deals with
Tightly coupled, fine-grained multiprocessors
Large scientific and engineering problems
Speed-ups from parallelism are possible in less exotic settings
SMPs, Overlapped I/O
Key to speed-up is independence of tasks
Minimize thread communication and synchronization
Minimize sharing of resource objects
Rely on groups of thread-based objects
Worker thread designs
Scatter/gather designs
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Interacting with Groups
Group Proxies encapsulate a group of workers and protocol
class GroupProxy implements Service {
public Result serve(Data data) {
split the data into parts;
for each part p
start up a thread to process p;
for each thread t {
collect results from t;//via callback or join
if (have enough results) // one, all, or some
return aggegrate result;
}
}
client proxy members
scatter
gather
serve
return
Concurrent Programming in Java
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Group Service Example
public class GroupPictureRenderer {
public Picture[] render(final byte[][] data)
throws InterruptedException {
int n = data.length;
Thread threads[] = new Thread[n];
final Picture results[] = new Picture[n];
for (int k = 0; k < n; k++) {
final int i = k; // inner vars must be final
threads[i] = new Thread(new Runnable() {
public void run() {
PictureRenderer r = new PictureRenderer();
results[i] = r.render(data[i]);
}
};
threads[i].start();
}
// block until all are finished
for (int k = 0; k < n; k++) threads[k].join();
return results;
}
}
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Iteration using Cyclic Barriers
CyclicBarrier is synchronization tool for iterative group algorithms
Initialize count with number of members
synch() waits for zero, then resets to initial count
class PictureProcessor { // ...
public void processPicture(final byte[][] data){
final CyclicBarrier barrier =
new CyclicBarrier(NWORKERS);
for (int ii = 0; ii < NWORKERS; ++ii) {
final int i = ii;
Runnable worker = new Runnable() {
public void run() {
while (!done()) {
transform(data[i]);
try { barrier.barrier(); }
catch(InterruptedException e){return;}
combine(data[i],data[(i+1)%NWORKERS]);
} } };
new Thread(worker).start();
}
}
}
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Implementing Cyclic Barriers
class CyclicBarrier {
private int count_;
private int initial_;
private int resets_ = 0;
CyclicBarrier(int c) { count_ = initial_ = c; }
synchronized boolean barrier() throws Inte...{
if (--count_ > 0) { // not yet tripped
int r = resets_; // wait until next reset
do { wait(); } while (resets_ == r);
return false;
}
else {
count_ = initial_;
++resets_;
notifyAll();
return true; // return true if caller tripped
}
}
}
Concurrent Programming in Java
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Layered Services
Providing concurrency control for methods of internal objects
Applying special synchronization policies
Applying different policies to the same mechanisms
Requires visibility control (containment)
Inner code must be communication-closed
No unprotected calls in to or out from island
Outer objects must never leak identities of inner objects
Can be difficult to enforce and check
Usually based on before/after methods
part2
subpart1
part1
client
client
Control
Concurrent Programming in Java
169
Three-Layered Application Designs
Common across many concurrent applications
Generally easy to design and implement
Maintain directionality of control and locking
Interaction with external world
generating threads
Basic mechanisms
Concurrency Control
locking, waiting, failing
Concurrent Programming in Java
170
Before/After Control
Control access to contained object/action via a method of the form
void controlled() {
pre();
try { action(); }
finally { post(); }
}
Used by built-in Java synchronized(obj) {action(); }
Pre: ‘{‘ obtains lock ... Post: ‘}’ releases lock
Control code must be separable from ground action code
Control code deals only with execution state
Ground code deals only with intrinsic state
Basis for many delegation-based designs
ControlledService
service() {
GroundService
action() { ... }
delegate
pre();
delegate.action();
post();
}
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Template Method Before/After Designs
Subclassing is one way to implement
before/after containment designs
Superclassinstancevariables
and methods are “contained”
in subclass instances
Template methods
Isolate ground code and
control code in overridable
protected methods
Public methods call control
and ground code in an
established fashion
Can provide default versions
in abstract classes
Can override the control code
and/or the ground code in
subclasses
AbstractService
public service() {
protected pre();
protected action();
protected post();
ConcreteService
override
pre() or action() or post();
pre();
action();
post();
}
Concurrent Programming in Java
172
Readers & Writers Policies
Apply when
Methods of ground class can be separated into readers
(accessors) vs writers (mutators)
For example, controlling access to data repository
Any number of reader threads can run simultanously, but
writers require exclusive access
Many policy variants possible
Mainly surrounding precedence of waiting threads
Readers first? Writers first? FIFO?
write
read
threads
data
Concurrent Programming in Java
173
Readers & Writers via Template Methods
public abstract class RW {
protected int activeReaders_ = 0; // exec state
protected int activeWriters_ = 0;
protected int waitingReaders_ = 0;
protected int waitingWriters_ = 0;
public void read() {
beforeRead();
try { doRead(); } finally { afterRead(); }
}
public void write(){
beforeWrite();
try { doWrite(); } finally { afterWrite(); }
}
protected boolean allowReader() {
return waitingWriters_ == 0 &&
activeWriters_ == 0;
}
protected boolean allowWriter() {
return activeReaders_ == 0 &&
activeWriters_ == 0;
}
Concurrent Programming in Java
174
Readers & Writers (continued)
protected synchronized void beforeRead() {
++waitingReaders_;
while (!allowReader())
try { wait(); }
catch (InterruptedException ex) { ... }
--waitingReaders_;
++activeReaders_;
}
protected abstract void doRead();
protected synchronized void afterRead() {
--activeReaders_;
notifyAll();
}
Concurrent Programming in Java
175
Readers & Writers (continued)
protected synchronized void beforeWrite() {
++waitingWriters_;
while (!allowWriter())
try { wait(); }
catch (InterruptedException ex) { ... }
--waitingWriters_;
++activeWriters_;
}
protected abstract void doWrite();
protected synchronized void afterWrite() {
--activeWriters_;
notifyAll();
}
}
Concurrent Programming in Java
176
Using Concurrency Libraries
Library classes can help separate responsibilities for
Choosing a policy; for example
Exclusive versus shared access
Waiting versus failing
Use of privileged resources
Applying a policy in the course of a service or transaction
These decisions can occur many times within a method
Standard libraries can encapsulate intricate synchronization code
But can add programming obligations
Correctness relies on all objects obeying usage policy
Cannot automatically enforce
Examples
Synchronization, Channels, Transactions
Concurrent Programming in Java
177
Interfaces
Sync encompasses many concurrency control policies
public interface Sync {
// Serve as a gate, fail only if interrupted
void acquire() throws InterruptedException;
// Possibly allow other threads to pass the gate
void release();
// Try to pass for at most timeout msecs,
// return false if fail
boolean attempt(long timeOut);
}
Service
service(...) {
ConcreteSync
implementations
cond
cond.acquire();
Sync
void acquire()
void release()
boolean attempt(long timeOut)
try { action(); }
finally { cond.release(); }
}
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178
Synchronization Libraries
Semaphores
Maintain count of the number of threads allowed to pass
Latches
Boolean conditions that are set once, ever
Barriers
Counters that cause all threads to wait until all have
finished
Reentrant Locks
Java-style locks allowing multiple acquisition by same
thread, but that may be acquired and released as needed
Mutexes
Non-reentrant locks
Read/Write Locks
Pairs of conditions in which the readLock may be shared,
but the writeLock is exclusive
Concurrent Programming in Java
179
Semaphores
Conceptually serve as permit holders
Construct with an initial number of permits (usually 0)
require waits for a permit to be available, then takes one
release adds a permit
But in normal implementations, no actual permits change hands.
The semaphore just maintains the current count.
Enables very efficient implementation
Applications
Isolating wait sets in buffers, resource controllers
Designs that would otherwise encounter missed signals
Where one thread signals before the other has even
started waiting
Semaphores ‘remember’ how many times they were
signalled
Concurrent Programming in Java
180
Counter Using Semaphores
class BoundedCounterUsingSemaphores {
long count_ = MIN;
Sync decPermits_= new Semaphore(0);
Sync incPermits_= new Semaphore(MAX-MIN);
synchronized long value() { return count_; }
void inc() throws InterruptedException {
incPermits_.acquire();
synchronized(this) { ++count_; }
decPermits_.release();
}
void dec() throws InterruptedException {
decPermits_.acquire();
synchronized(this) { --count_; }
incPermits_.release();
}
}
This uses native synch for update protection, but only inside permit
blocks. This avoids nested monitor lockouts
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181
Semaphore Synchronous Channel
class SynchronousChannelVS {
Object item = null;
Semaphore putPermit = new Semaphore(1);
Semaphore takePermit = new Semaphore(0);
Semaphore ack = new Semaphore(0);
void put(Object x) throws InterruptedException {
putPermit.acquire();
item = x;
takePermit.release();
ack.acquire();
}
Object take() throws InterruptedException {
takePermit.acquire();
Object x = item;
putPermit.release();
ack.release();
return x;
}
}
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182
Using Latches
Conditions starting out false, but once set true, remain true forever
Initialization flags
End-of-stream conditions
Thread termination
Event occurrences
class Worker implements Runnable {
Latch go;
Worker(Latch l) { go = l; }
public void run() {
go.acquire();
doWork();
}
}
class Driver { // ...
void main() {
Latch go = new Latch();
for (int i = 0; i < N; ++i) // make threads
new Thread(new Worker(go)).start();
doSomethingElse(); // don’t let run yet
go.release(); // let all threads proceed
} }
Concurrent Programming in Java
183
Using Barrier Conditions
Count-based latches
Initialize with a fixed count
Each release monotonically decrements count
All acquires pass when count reaches zero
class Worker implements Runnable {
Barrier done;
Worker(Barrier d) { done = d; }
public void run() {
doWork();
done.release();
}
}
class Driver { // ...
void main() {
Barrier done = new Barrier(N);
for (int i = 0; i < N; ++i)
new Thread(new Worker(done)).start();
doSomethingElse();
done.acquire(); // wait for all to finish
} }
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184
Using Lock Classes
class HandSynched {
private double state_ = 0.0;
private Sync lock_;
HandSynched(Sync l) { lock_ = l; }
void changeState(double d) {
try {
lock_.acquire();
try { state_ = d; }
finally { lock_.release(); }
} catch(InterruptedException ex) { }
}
double getState() {
double d = 0.0;
try {
lock_.acquire();
try { d = state_; }
finally { lock_.release(); }
} catch(InterruptedException ex){}
return d;
}
}
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185
Wrapper Classes
Standardize common client usages of custom locks using wrappers
Wrapper class supports perform method that takes care
of all before/after control surrounding a Runnable
command sent as a parameter
Can also standardize failure control by accepting
Runnable action to be performed on acquire failure
Alternative perform methods can accept blocks that return results
and/or throw exceptions
But need to create new interface type for each kind of block
Similar to macros in other languages
But implement more safely via inner classes
Wrappers are composable
Adds noticeable overhead for simple usages
Most useful for controlling “heavy” actions
Concurrent Programming in Java
186
Before/After Wrapper Example
class WithLock {
Sync cond;
public WithLock(Sync c) { cond = c; }
public void perform(Runnable command)
throws InterruptedException {
cond.acquire();
try { command.run(); }
finally { cond.release(); }
}
public void perform(Runnable command,
Runnable onInterrupt) {
try { perform(command); }
catch (InterruptedException ex) {
if (onInterrupt != null)
onInterrupt.run();
else // default
Thread.currentThread().interrupt();
}
}
}
Concurrent Programming in Java
187
Using Wrappers
class HandSynchedV2 { // ...
private double state_ = 0.0;
private WithLock withlock_;
HandSynchedV2(Sync l) {
withlock_ = new WithLock(l);
}
void changeState(double d) {
withlock_.perform(
new Runnable() {
public void run() { state_ = d; } },
null); // use default interrupt action
}
double getState() {
// (need to define interface & perform version)
try {
return withLock_.perform(new DoubleAction(){
public void run() { return state_; } });
}
catch(InterruptedException ex){return 0.0;}
}
}
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188
Using Conditional Locks
Sync.attempt can be used in conditional locking idioms
Back-offs
Escape out if a lock not available
Can either retry or fail
Reorderings
Retry lock sequence in different order if first attempt fails
Heuristic deadlock detection
Back off on time-out
Precise deadlock detection
Implement Sync via lock manager that can detect cycles
Concurrent Programming in Java
189
Back-off Example
class Cell {
long value;
Sync lock = new SyncImpl();
void swapValue(Cell other) {
for (;;) {
try {
lock.acquire();
try {
if (other.lock.attempt(100)) {
try {
long t = value; value = other.value;
other.value = t;
return;
}
finally { other.lock.release(); }
}
}
finally { lock.release(); }
}
catch (InterruptedException ex) { return; }
}
}
}
Concurrent Programming in Java
190
Lock Reordering Example
class Cell {
long value;
Sync lock = new SyncImpl();
private static boolean trySwap(Cell a, Cell b) {
a.lock.acquire();
try {
if (!b.lock.attempt(0)) return false;
try {
long t = a.value;
a.value = b.value;
b.value = t;
return true;
}
finally { other.lock.release(); }
}
finally { lock.release(); }
return false;
}
void swapValue(Cell other) {
while (!trySwap(this, other) &&
!tryswap(other, this)) Thread.yield();
}
}
Concurrent Programming in Java
191
Using Read/Write Locks
public interface ReadWriteLock {
Sync readLock();
Sync writeLock();
}
Sample usage using wrapper
class WithRWLock {
ReadWriteLock rw;
public WithRWLock(ReadWriteLock l) { rw = l; }
public void performRead(Runnable readCommand)
throws InterruptedException {
rw.readLock().acquire();
try { readCommand.run(); }
finally { rw.readlock().release(); }
}
public void performWrite(...) // similar
}
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192
Transaction Locks
Associate keys with locks
Each key corresponds to a different transaction.
Thread.currentThread() serves as key in reentrant
Java synchronization locks
Supply keys as arguments to gating methods
Security frameworks can use similar interfaces, adding
mechanisms and protocols so keys serve as capabilities
Sample interface
interface TransactionLock {
void begin(Object key); // bind key with lock
void end(Object key); // get rid of key
void acquire(Object key)
throws InterruptedException;
void release(Object key);
}
Concurrent Programming in Java
193
Transactional Classes
Implement a common transaction control interface, for example:
interface Transactor {
// enter a new transaction
void join(Object key) throws Failure;
// return true if transaction can be committed
boolean canCommit(Object key);
// update state to reflect current transaction
void commit(Object key) throws Failure;
// roll back state
void abort(Object key);
}
Transactors must ensure that all objects they communicate with
are also Transactors
Control arguments must be propagated to all participants
Concurrent Programming in Java
194
Per-Method Transaction Control
Add transaction control argument to each method.
For example:
interface TransBankAccount extends Transactor {
long balance(Object key)
throws InterruptedException;
void deposit(Object key, long amount)
throws InsufficientFunds,
InterruptedException;
void withdraw(Object key, long amount)
throws InsufficientFunds,
InterruptedException;
}
The same interfaces can apply to optimistic transactions
Use interference detection rather than locking.
They are generally interoperable
Concurrent Programming in Java
195
Per -ThreadGroup Transaction Control
Assumes each transaction established in own ThreadGroup
class Context { // ...
Object get(Object name);
void bind(Object name, Object val);
}
class XTG extends ThreadGroup { // ...
Context getContext();
}
class Account extends Transactor {
private long balance_;
private TransactionLock tlock_;
// ...
void deposit(long amount) throws ... {
tlock_.acquire(((XTG)
(Thread.currentThread().getThreadGroup()))
.getContext().get("TransactionID"));
synchronized (this) {
if (amount >= 0) balance_ += amount; else ...
}
}
}
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196
Integrating Control Policies
Dealing with multiple contextual domains, including
Security: Principal identities, keys, groups, etc
Synchronization: Locks, conditions, transactions, ...
Scheduling: Priorities, timing, checkpointing, etc
Environment: Location, computational resources
Dealing with multiple outcomes
Block, fail, proceed, save state, commit state, notify, ...
Encapsulating associated policy control information
For example access control lists, lock dependencies
Introducing new policies in sub-actions
New threads, conditions, rights-transfers, subtransactions
Avoiding policy conflicts: policy compatibility matrices, ...
Avoiding excessive programming obligations for developers
Tool-based code generation, layered virtual machines
Concurrent Programming in Java
197
Using Integrated Control
Methods invoke helpers to make control decisions as needed
class Account { // ...
void deposit(long amount, ...) {
authenticator.authenticate(clientID);
accessController.checkAccess(clientID, acl);
logger.logDeposit(clientID, transID, amount);
replicate.shadowDeposit(...);
db.checkpoint(this);
lock.acquire();
balance += amount;
lock.release();
db.commit(balance, ...);
UIObservers.notifyOfChange(this);
}
}
Not much fun to program.
Concurrent Programming in Java
198
Implementing Library Classes
Classes based on Java monitor methods can be slow
Involve context switch, locking, and scheduling overhead
Relative performance varies across platforms
Some performance enhancements
State tracking
Only notify when state changes known to unblock waits
Isolating wait sets
Only wake up threads waiting for a particular state change
Single notifications
Only wake up a single thread rather than all waiting threads
Avoiding locks
Don’t lock if can be sure won’t wait
Can lead to significantly faster, but more complex and fragile code
Concurrent Programming in Java
199
Tracking State in Guarded Methods
Partition action control state into categories with
same enabling properties
Only provide notifications when making a state
transition that can ever unblock another thread
Here, on exit from top or bottom
When count goes up from MIN or down from MAX
Still need notifyAll unless add instrumentation
State tracking leads to faster but more fragile code
Usually many fewer notification calls
Harder to change guard conditions
Harder to add subclasses with different conditions
State Condition inc dec
top value == MAX no yes
middle MIN < value < MAX yes yes
bottom value == MIN yes no
top
middle
bottom
dec inc
inc
dec
from
MAX to
MAX
to
MIN from
MIN
Concurrent Programming in Java
200
Counter with State Tracking
class FasterGuardedBoundedCounter {
protected long count_ = MIN;
synchronized long value() { return count_; }
synchronized void inc()
throws InterruptedException {
while (count_ == MAX) wait();
if (count_++ == MIN) notifyAll();
}
synchronized void dec()
throws InterruptedException {
while (count_ == MIN) wait();
if (count_-- == MAX) notifyAll();
}
}
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201
Buffer with State Tracking
class BoundedBufferVST {
Object[] data_;
int putPtr_ = 0, takePtr_ = 0, size_ = 0;
protected void doPut(Object x){
data_[putPtr_] = x;
putPtr_ = (putPtr_ + 1) % data_.length;
if (size_++ == 0) notifyAll();
}
protected Object doTake() {
Object x = data_[takePtr_];
data_[takePtr_] = null;
takePtr_ = (takePtr_ + 1) % data_.length;
if (size_-- == data_.length) notifyAll();
return x;
}
synchronized void put(Object x) throws Inte... {
while (isFull()) wait();
doPut(x);
}
// ...
}
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202
Inheritance Anomaly Example
class XBuffer extends BoundedBufferVST {
synchronized void putPair(Object x, Object y)
throws InterruptedException {
put(x);
put(y);
}
}
PutPair does not guarantee that the pair is inserted contiguously
To ensure contiguity, try adding guard:
while (size_ > data_.length - 2) wait();
But doTake only performs notifyAll when the buffer transitions
from full to not full
The wait may block indefinitely even when space available
•Somust rewrite doTake to change notification condition
Would have been better to factor out the notification conditions in a
separate overridable method
Most inheritance anomalies can be avoided by fine-grained
(often tedious) factoring of methods and classes
Concurrent Programming in Java
203
Isolating Waits and Notifications
Mixed condition problems
Threads that wait in different methods in the same object
may be blocked for different reasons — for example,
not
Empty
vs
not Full
for buffer
notifyAll wakes up all threads, even those waiting for
conditions that could not possibly hold
Can isolate waits and notifications for different conditions in
different objects — an application of splitting
Thundering herd problems
notifyAll may wake up many threads
Often, at most one of them will be able to continue
Can solve by using notify instead of notifyAll only when
All threads wait on same condition
At most one thread could continue anyway
That is, when it doesn’t matter which one is woken, and it
doesn’t matter that others aren’t woken
Concurrent Programming in Java
204
Implementing Reentrant Locks
final class ReentrantLock implements Sync {
private Thread owner_ = null;
private int holds_ = 0;
synchronized void acquire() throws Interru... {
Thread caller = Thread.currentThread();
if (caller == owner_) ++holds_;
else {
try { while (owner_ != null) wait(); }
catch (InterruptedException e) {
notify(); throw e;
}
owner_ = caller; holds_ = 1;
}
}
synchronized void release() {
Thread caller = Thread.currentThread();
if (caller != owner_ || holds_ <= 0)
throw new Error("Illegal Lock usage");
if (--holds_ == 0) {
owner_ = null;
notify();
}
}}
Concurrent Programming in Java
205
Implementing Semaphores
final class Semaphore implements Sync {
int permits_; int waits_ = 0;
Semaphore(int p) { permits_ = p; }
synchronized void acquire() throws Interrup.. {
if (permits_ <= waits_) {
++waits_;
try {
do { wait(); } while (permits_ == 0);
}
catch(InterruptedException ex) {
--waits_;notify(); throw ex;
}
--waits_;
}
--permits_;
}
synchronized void release() {
++permits_;
notify();
}
}
Concurrent Programming in Java
206
Implementing Latches
Exploit set-once property to avoid locking using double-check:
Check status without even locking
If set, exit — no possibility of conflict or stale read
Otherwise, enter standard locked wait
But can have surprising effects if callers expect locking for sake of
memory consistency.
final class Latch implements Sync {
private boolean latched_ = false;
void acquire() throws InterruptedException {
if (!latched_)
synchronized(this) {
while (!latched_) wait();
}
}
synchronized void release() {
latched_ = true;
notifyAll();
}
}
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Implementing Barrier Conditions
Double-check can be used for any monotonic variable that is tested
only for a threshold value
CountDown Barriers monotonically decrement counts
Tests against zero cannot encounter conflict or staleness
(This technique does not apply to Cyclic Barriers)
class CountDown implements Sync {
private int count_;
CountDown(int initialc) { count_ = initialc; }
void acquire() throws InterruptedException {
if (count_ > 0)
synchronized(this) {
while (count_ > 0) wait();
}
}
synchronized void release() {
if (--count_ == 0) notifyAll();
}
}
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Implementing Read/Write Locks
class SemReadWriteLock implements ReadWriteLock {
// Provide fair access to active slot
Sync active_ = new Semaphore(1);
// Control slot sharing by readers
class ReaderGate implements Sync {
int readers_ = 0;
synchronized void acquire()
throws InterruptedException {
// readers pile up on lock until first passes
if (readers_++ == 0) active_.acquire();
}
synchronized void release() {
if (--readers_ == 0) active_.release();
}
}
Sync rGate_ = new ReaderGate();
public Sync writeLock() { return active_; }
public Sync readLock() { return rGate_; }
}
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Documenting Concurrency
Make code understandable
To developers who use components
To developers who maintain and extend components
To developers who review and test components
Avoid need for extensive documentation by adopting:
Standard policies, protocols, and interfaces
Standard design patterns, libraries, and frameworks
Standard coding idioms and conventions
Document decisions
Use javadoc to link to more detailed descriptions
Use naming and signature conventions as shorthand clues
Explain deviations from standards, usage limitations, etc
Describe necessary data invariants etc
Use checklists to ensure minimal sanity
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Sample Documentation Techniques
Patlet references
/** ... Uses
* <a href=”tpm.html”>Thread-per-Message</a> **/
void handleRequest(...);
Default naming and signature conventions
Sample rule: Unless specified otherwise, methods that can
block have signature
... throws InterruptedException
Intentional limitations, and how to work around them
/** ... NOT Threadsafe, but can be used with
* @see XAdapter to make lockable version. **/
Decisions impacting potential subclassers
/** ... Always maintains a legal value,
* so accessor method is unsynchronized **/
protected int bufferSize;
Certification
/** Passed safety review checklist 11Nov97 **/
Concurrent Programming in Java
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Semiformal Annotations
PRE — Precondition (normally unchecked)
/** PRE: Caller holds synch lock ...
WHEN Guard condition (always checked)
/** WHEN not empty return oldest ...
POST — Postcondition (normally unchecked)
/** POST: Resource r is released...
OUT — Guaranteed message send (relays, callbacks, etc)
/** OUT: c.process(buff) called after read...
RELY — Required property of other objects/methods
/** RELY: Must be awakened by x.signal()...
INV — Object constraint true at start/end of every activity
/** INV: x,y are valid screen coordinates...
INIT — Object constraint that must hold upon construction
/** INIT: bufferCapacity greater than zero...
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Safety Problem Checklist
Storage conflicts
Failure to ensure exclusive access; race conditions
Atomicity errors
Breaking locks in the midst of logically atomic operations
Representation inconsistencies
Allowing dependent representations to vary independently
Invariant failures
Failing to re-establish invariants within atomic methods
for example failing to clean up after exceptions
Semantic conflicts
Executing actions when they are logically prohibited
Slipped Conditions
A condition stops holding in the midst of an action
requiring it to hold
Memory ordering and visibility
Using stale cached values
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Liveness Problems
Lockout
A called method never becomes available
Deadlock
Two or more activities endlessly wait for each other
Livelock
A retried action never succeeds
Missed signals
A thread starts waiting after it has already been signalled
Starvation
A thread is continually crowded out from passing gate
Failure
A thread that others are waiting for stops
Resource exhaustion
Exceeding memory, bandwidth, CPU limitations
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214
Efficiency Problems
Too much locking
Cost of using synchronized
Cost of blocking waiting for locks
Cost of thread cache flushes and reloads
Too many threads
Cost of starting up new threads
Cost of context switching and scheduling
Cost of inter-CPU communication, cache misses
Too much coordination
Cost of guarded waits and notification messages
Cost of layered concurrency control
Too many objects
Cost of using objects to represent state, messages, etc
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Reusability Problems
Context dependence
Components that are not safe/live outside original context
Policy breakdown
Components that vary from system-wide policies
Inflexibility
Hardwiring control, premature optimization
Policy clashes
Components with incompatible concurrency control
strategies
Inheritance anomalies
Classes that are difficult or impossible to subclass
Programmer-hostile components
Components imposing awkward, implicit , and/or error-prone
programming obligations
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... Colt [Shacham et al., 2011] and ICFinder [Liu et al., 2013] test atomicity of, and Snowflake [Lesani et al., 2014] automatically verifies, composed methods that extend the interface of an already linearizable data structure [Lea, 2000]. Our framework includes tactics that can automatically verify a strict superset of the above use cases. ...
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Interaction trees are a representation of effectful and reactive systemsdesigned to be implemented in a proof assistant such as Coq. They are equipped with a rich algebra of combinators to construct recursive and effectful computations and to reason about them equationally. Interaction trees are also an executable structure, notably via extraction, which enables testing and directly developing executable programs in Coq. To demonstrate the usefulness of interaction trees, two applications are presented. First, I develop a novel approach to verify a compiler from a simple imperative language to assembly, by proving a semantic preservation theorem which is termination-sensitive, using an equational proof. Second, I present a framework of concurrent objects, inheriting the modularity, compositionality, and executability of interaction trees. Leveraging that framework, I formally prove the correctness of a transactionally predicated map, using a novel approach to reason about objects combining the notions of linearizability and strict serializability, two well-known correctness conditions for concurrent objects.
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