concurrency gpars
TRANSCRIPT
© AS
ER
T 2006-2013
Concurrency with GPars
Dr Paul King@paulk_asert
http:/slideshare.net/paulk_asert/concurrency-gpars
https://github.com/paulk-asert/concurrency-gpars
TopicsIntro• Useful Groovy features for Concurrency• GPars• Case Studies• More Info• Bonus Material
GPars - 2
© ASERT 2006-
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"Andy giveth and Bill taketh away"
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Why is it hard?• Many issues to deal with:
– Doing things in parallel, concurrently, asynchronously• Processes, Threads, Co-routines, Events, Scheduling
– Sharing/Synchronization Mechanisms• shared memory, locks, transactions, wait/notify, STM,
message passing, actors, serializability, persistence, immutability
– Abstractions• Shared memory on top of messaging passing• Message passing on top of shared memory• Dataflow, Selective Communication, Continuations
– Data Structures and Algorithms• Queues, Heaps, Trees• Sorting, Graph Algorithms
GPars - 4
Java Concurrency Best Practice?• Java Concurrency in Practice:
–“If multiple threads access thesame mutable state variablewithout appropriate synchronization,your program is broken”
–“When designing thread-safe classes, good object-oriented techniques – encapsulation, immutability, and clear specification of invariants – are your best friends”
GPars - 5
Ralph Johnson: Parallel Programming
• Styles of parallel programming– Threads and locks
– Asynchronous messages e.g. Actors – no or limited shared memory
– Sharing with deterministic restrictions e.g. Fork-join
– Data parallelism
GPars - 6
© ASERT 2006-
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http://strangeloop2010.com/talk/presentation_file/14485/Johnson-DataParallelism.pdf
Increasin
g A
bstractio
n
Ralph Johnson: Parallel Programming
• Styles of parallel programming– Threads and locks
• Nondeterministic, low-level, rumored humans can do this
– Asynchronous messages e.g. Actors –no or limited shared memory
• Nondeterministic, ok for I/O but be careful with side-effects
– Sharing with deterministic restrictionse.g. Fork-join
• Hopefully deterministic semantics, not designed for I/O
– Data parallelism• Deterministic semantics, easy, efficient, not designed for I/O
GPars - 7
© ASERT 2006-
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http://strangeloop2010.com/talk/presentation_file/14485/Johnson-DataParallelism.pdf
Each approach has some caveats
GPars• http://gpars.codehaus.org/• Library classes and DSL sugar providing
intuitive ways for Groovy developers tohandle tasks concurrently. Logical parts:– Data Parallelism features use JSR-166y Parallel Arrays
to enable multi-threaded collection processing– Asynchronous functions extend the Java built-in support
for executor services to enable multi-threaded closure processing
– Dataflow Concurrency supports natural shared-memory concurrency model, using single-assignment variables
– Actors provide an implementation of Erlang/Scala-like actors including "remote" actors on other machines & CSP
– Safe Agents provide a non-blocking mt-safe reference to mutable state; inspired by "agents" in Clojure
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© ASERT 2006-
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Choosing approaches
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For
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e de
tails
see
: ht
tp:/
/gpa
rs.c
odeh
aus.
org/
Con
cept
s+co
mpa
red
ParallelCollections
Data Parallelism
TaskParallelism
Streamed DataParallelism
Fork/Join
Dataflowoperators
CSP
Actors
Dataflow tasksActors
Asynch fun’sCSP
Fork/Join
ImmutableStm, Agents
Special collectionsSynchronization
Linear Recursive
Linear
Recursive
SharedData
IrregularRegular
Coordination approaches
GPars - 10
Sou
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ReG
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– G
roov
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Act
ion,
2nd
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tion
Data Parallelism:Fork/Join
Map/Reduce
Fixed coordination(for collections)
Actors Explicit coordination
Safe Agents Delegated coordination
Dataflow Implicit coordination
Groovy concurrency value add
GPars - 11
JVM ConcurrencyThreads, synchronization, locks, semaphores, Phaser,
executor, fork-join, concurrent collections, atomic objects
GParsMap/reduce, fork/join,
asynchronous closures, actors, CSP, agents, dataflow concurrency
Your Application
GroovyThread & process
enhancements, immutability, laziness, @WithReadLock, @WithWriteLock, @Lazy,
@Synchronized
Immutable Classes• Some Rules
– Don’t provide mutators– Ensure that no methods can
be overridden• Easiest to make the class final• Or use static factories & non-public
constructors
– Make all fields final– Make all fields private
• Avoid even public immutable constants
– Ensure exclusive access to any mutable components• Don’t leak internal references• Defensive copying in and out
– Optionally provide equals and hashCode methods– Optionally provide toString method
@Immutable...• Java Immutable Class
– As per Joshua BlochEffective Java
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public final class Person { private final String first; private final String last;
public String getFirst() { return first; }
public String getLast() { return last; }
@Override public int hashCode() { final int prime = 31; int result = 1; result = prime * result + ((first == null) ? 0 : first.hashCode()); result = prime * result + ((last == null) ? 0 : last.hashCode()); return result; }
public Person(String first, String last) { this.first = first; this.last = last; } // ...
// ... @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (getClass() != obj.getClass()) return false; Person other = (Person) obj; if (first == null) { if (other.first != null) return false; } else if (!first.equals(other.first)) return false; if (last == null) { if (other.last != null) return false; } else if (!last.equals(other.last)) return false; return true; }
@Override public String toString() { return "Person(first:" + first + ", last:" + last + ")"; }
}
...@Immutable...• Java Immutable Class
– As per Joshua BlochEffective Java
© ASERT 2006-
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public final class Person { private final String first; private final String last;
public String getFirst() { return first; }
public String getLast() { return last; }
@Override public int hashCode() { final int prime = 31; int result = 1; result = prime * result + ((first == null) ? 0 : first.hashCode()); result = prime * result + ((last == null) ? 0 : last.hashCode()); return result; }
public Person(String first, String last) { this.first = first; this.last = last; } // ...
// ... @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (getClass() != obj.getClass()) return false; Person other = (Person) obj; if (first == null) { if (other.first != null) return false; } else if (!first.equals(other.first)) return false; if (last == null) { if (other.last != null) return false; } else if (!last.equals(other.last)) return false; return true; }
@Override public String toString() { return "Person(first:" + first + ", last:" + last + ")"; }
}
boilerplate
...@Immutable© ASERT 2006-
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@Immutable class Person { String first, last}
Approaches to managing collection storage• Mutable • Persistent
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• Immutable
‘c’ ‘a’ ‘c’ ‘a’
Add ‘t’ Add ‘t’ Add ‘t’
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ArrayList, HashSet, HashMap asImmutable(), Guava, mop tricks fj, clj-ds, pcollections, totallylazy
Topics• Intro• Useful Groovy features for ConcurrencyGPars• Case Studies• More Info• Bonus Material
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© ASERT 2006-
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Choosing approaches
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For
mor
e de
tails
see
: ht
tp:/
/gpa
rs.c
odeh
aus.
org/
Con
cept
s+co
mpa
red
ParallelCollections
Data Parallelism
TaskParallelism
Streamed DataParallelism
Fork/Join
Dataflowoperators
CSP
Actors
Dataflow tasksActors
Asynch fun’sCSP
Fork/Join
ImmutableStm, Agents
Special collectionsSynchronization
Linear Recursive
Linear
Recursive
SharedData
IrregularRegular
Groovy Sequential Collection
GPars - 19
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def oneStarters = (1..30) .collect { it ** 2 } .findAll { it ==~ '1.*' } assert oneStarters == [1, 16, 100, 121, 144, 169, 196]
assert oneStarters.max() == 196 assert oneStarters.sum() == 747
GPars Parallel Collections…
GPars - 20
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import static groovyx.gpars.GParsPool.withPool
withPool { def oneStarters = (1..30) .collectParallel { it ** 2 } .findAllParallel { it ==~ '1.*' } assert oneStarters == [1, 16, 100, 121, 144, 169, 196]
assert oneStarters.maxParallel() == 196 assert oneStarters.sumParallel() == 747}
…GPars Parallel Collections
• Suitable when– Each iteration is independent, i.e. not:
fact[index] = index * fact[index - 1]– Iteration logic doesn’t use non-thread safe code– Size and indexing of iteration are important
GPars - 21
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import static groovyx.gpars.GParsPool.withPool
withPool { def oneStarters = (1..30) .collectParallel { it ** 2 } .findAllParallel { it ==~ '1.*' } assert oneStarters == [1, 16, 100, 121, 144, 169, 196]
assert oneStarters.maxParallel() == 196 assert oneStarters.sumParallel() == 747}
Parallel Collection Variations• Apply some Groovy metaprogramming
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import static groovyx.gpars.GParsPool.withPool
withPool { def oneStarters = (1..30).makeConcurrent() .collect { it ** 2 } .findAll { it ==~ '1.*' } .findAll { it ==~ '...' } assert oneStarters == [100, 121, 144, 169, 196]}
import groovyx.gpars.ParallelEnhancer
def nums = 1..5ParallelEnhancer.enhanceInstance(nums)assert [1, 4, 9, 16, 25] == nums.collectParallel{ it * it }
GPars parallel methods for collectionsTransparent Transitive? Parallel Lazy?
any { ... } anyParallel { ... } yes
collect { ... } yes collectParallel { ... }
count(filter) countParallel(filter)
each { ... } eachParallel { ... }eachWithIndex { ...
} eachWithIndexParallel
{ ... }every { ... } everyParallel { ... } yes
find { ... } findParallel { ... }
findAll { ... } yes findAllParallel { ... }
findAny { ... } findAnyParallel { ... }
fold { ... } foldParallel { ... }fold(seed) { ... }
foldParallel(seed) { ... }
grep(filter) yes grepParallel(filter)
groupBy { ... } groupByParallel { ... }
max { ... } maxParallel { ... }
max() maxParallel()
min { ... } minParallel { ... }
min() minParallel()
split { ... } yes splitParallel { ... }
sum sumParallel // foldParallel +
GPars - 23Transitive means result is automatically transparent; Lazy means fails fast
For
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ars
docu
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tatio
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GPars: Map-Reduce
GPars - 24
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import static groovyx.gpars.GParsPool.withPool
withPool { def oneStarters = (1..30).parallel .map { it ** 2 } .filter { it ==~ '1.*' }
assert oneStarters.collection == [1, 16, 100, 121, 144, 169, 196]
// aggregations/reductions assert oneStarters.max() == 196 assert oneStarters.reduce { a, b -> a + b } == 747 assert oneStarters.sum() == 747}
GPars parallel array methods
Method Return Typecombine(initValue) { ... } Mapfilter { ... } Parallel arraycollection CollectiongroupBy { ... } Mapmap { ... } Parallel arraymax() Tmax { ... } Tmin() Tmin { ... } Treduce { ... } Treduce(seed) { ... } Tsize() intsort { ... } Parallel arraysum() Tparallel // on a Collection Parallel array
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For
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Parallel Collections vs Map-Reduce
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Fork Fork
JoinJoin
Map
Map
ReduceMap
Map
Reduce
Reduce
Map
Filter
Filter Map
Concurrency challenge…• Suppose we have the following
calculation involving several functions:
• And we want to use our available cores …
GPars - 27
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// example adapted from Parallel Programming with .Netdef (f1, f2, f3, f4) = [{ sleep 1000; it }] * 3 + [{ x, y -> x + y }]
def a = 5
def b = f1(a)def c = f2(a)def d = f3(c)def f = f4(b, d)
assert f == 10
…Concurrency challenge…• We can analyse the example’s task graph:
GPars - 28
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// example adapted from Parallel Programming with .Netdef (f1, f2, f3, f4) = [{ sleep 1000; it }] * 3 + [{ x, y -> x + y }]
def a = 5
def b = f1(a)def c = f2(a)def d = f3(c)def f = f4(b, d)
assert f == 10
f2
f3
f1
f4
aa
b
c
d
f
…Concurrency challenge…• Manually using asynchronous functions:
GPars - 29
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// example adapted from Parallel Programming with .Netdef (f1, f2, f3, f4) = [{ sleep 1000; it }] * 3 + [{ x, y -> x + y }]
import static groovyx.gpars.GParsPool.withPool
withPool(2) { def a = 5
def futureB = f1.callAsync(a) def c = f2(a) def d = f3(c) def f = f4(futureB.get(), d)
assert f == 10}
f2
f3
f1
f4
aa
b
c
d
f
…Concurrency challenge• And with GPars Dataflows:
GPars - 30
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def (f1, f2, f3, f4) = [{ sleep 1000; it }] * 3 + [{ x, y -> x + y }]
import groovyx.gpars.dataflow.Dataflowsimport static groovyx.gpars.dataflow.Dataflow.task
new Dataflows().with { task { a = 5 } task { b = f1(a) } task { c = f2(a) } task { d = f3(c) } task { f = f4(b, d) } assert f == 10}
f2
f3
f1
f4
aa
b
c
d
f
…Concurrency challenge• And with GPars Dataflows:
GPars - 31
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def (f1, f2, f3, f4) = [{ sleep 1000; it }] * 3 + [{ x, y -> x + y }]
import groovyx.gpars.dataflow.Dataflowsimport static groovyx.gpars.dataflow.Dataflow.task
new Dataflows().with { task { f = f4(b, d) } task { d = f3(c) } task { c = f2(a) } task { b = f1(a) } task { a = 5 } assert f == 10}
f2
f3
f1
f4
aa
b
c
d
f
GPars: Dataflows...
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© ASERT 2006-
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import static groovyx.gpars.dataflow.DataFlow.task
final flow = new DataFlows()task { flow.result = flow.x + flow.y }task { flow.x = 10 }task { flow.y = 5 }assert 15 == flow.result
new DataFlows().with { task { result = x * y } task { x = 10 } task { y = 5 } assert 50 == result}
510
yx
*
...GPars: Dataflows...• Evaluating:
GPars - 33
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import groovyx.gpars.dataflow.DataFlowsimport static groovyx.gpars.dataflow.DataFlow.task
final flow = new DataFlows()task { flow.a = 10 }task { flow.b = 5 }task { flow.x = flow.a - flow.b }task { flow.y = flow.a + flow.b }task { flow.result = flow.x * flow.y }assert flow.result == 75
b
10 5
a
+-
*
result = (a – b) * (a + b)
x y
Question: what happens if I change the order of the task statements here?
...GPars: Dataflows...• Naive attempt for loops
GPars - 34
© ASERT 2006-
2013 import groovyx.gpars.dataflow.Dataflowsimport static groovyx.gpars.dataflow.Dataflow.task
final flow = new Dataflows()[10, 20].each { thisA -> [4, 5].each { thisB -> task { flow.a = thisA } task { flow.b = thisB } task { flow.x = flow.a - flow.b } task { flow.y = flow.a + flow.b } task { flow.result = flow.x * flow.y } println flow.result }}// => java.lang.IllegalStateException: A DataflowVariable can only be assigned once.
... task { flow.a = 10 } ... task { flow.a = 20 }
Don’t do this!
X
...GPars: Dataflows...
GPars - 35
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import groovyx.gpars.dataflow.DataflowStreamimport static groovyx.gpars.dataflow.Dataflow.*
final streamA = new DataflowStream()final streamB = new DataflowStream()final streamX = new DataflowStream()final streamY = new DataflowStream()final results = new DataflowStream()
operator(inputs: [streamA, streamB], outputs: [streamX, streamY]) { a, b -> streamX << a - b; streamY << a + b}operator(inputs: [streamX, streamY], outputs: [results]) { x, y -> results << x * y }
[[10, 20], [4, 5]].combinations().each{ thisA, thisB -> task { streamA << thisA } task { streamB << thisB }}4.times { println results.val }
b
10102020
4545
a
+-
*
8475
384375
...GPars: Dataflows• Suitable when:
– Your algorithms can be expressed as mutually-independent logical tasks
• Properties:– Inherently safe and robust (no race conditions or
livelocks)– Amenable to static analysis– Deadlocks “typically” become repeatable– “Beautiful” (declarative) code
GPars - 36
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import groovyx.gpars.dataflow.Dataflowsimport static groovyx.gpars.dataflow.Dataflow.task
final flow = new Dataflows()task { flow.x = flow.y }task { flow.y = flow.x }
GPars: Dataflow Sieve
GPars - 37
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final int requestedPrimeNumberCount = 1000final DataflowStream initialChannel = new DataflowStream()
task { (2..10000).each { initialChannel << it }}
def filter(inChannel, int prime) { def outChannel = new DataflowStream() operator([inputs: [inChannel], outputs: [outChannel]]) { if (it % prime != 0) { bindOutput it } } return outChannel}
def currentOutput = initialChannelrequestedPrimeNumberCount.times { int prime = currentOutput.val println "Found: $prime" currentOutput = filter(currentOutput, prime)}
Source: http://groovyconsole.appspot.com/script/235002
GPars: Actors...• Actors provide explicit coordination: they
don’t share state, instead coordinating via asynchronous messages– Contrasting with predefined coordination for fork/join &
map/filter/reduce & implicit coordination for dataflow– Messages are processed one at a time normally in the
order they were sent (which is non-deterministic due to asynchronous nature)
– Some actor systems allowing message delivery to be prioritised; others allow for sharing some (readonly) state; some allow remote actors for load balancing/robustness
• Not new in concept– But has received recent publicity due to special
support in Erlang, Scala and other languages GPars - 38
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…GPars: Actors...• Class with the following lifecycle &
methods– But also DSL sugar & enhancements
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start()stop()act()send(msg)sendAndWait(msg)loop { }react { msg -> }msg.reply(replyMsg)receive()join()
…GPars: Actors...
GPars - 40
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import groovyx.gpars.actor.DynamicDispatchActor
class VotingActor extends DynamicDispatchActor { void onMessage(String language) { processVote(language) } void onMessage(List languages) { languages.each{ processVote it } } private processVote(language) { if (language.startsWith('G')) println "You voted for $language" else println 'Sorry, please try again' }}
final votes = new VotingActor().start()votes << 'Groovy'votes << 'C++'votes << ['Groovy', 'Go', 'Dart']votes.stop()votes.join()
You voted for GroovySorry, please try againYou voted for GroovyYou voted for GoSorry, please try again
…GPars: Actors...
GPars - 41
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import static groovyx.gpars.actor.Actors.*
def votes = reactor { it.endsWith('y') ? "You voted for $it" : "Sorry, please try again"}
println votes.sendAndWait('Groovy')println votes.sendAndWait('JRuby')println votes.sendAndWait('Go')
def languages = ['Groovy', 'Dart', 'C++']def booth = actor { languages.each{ votes << it } loop { languages.size().times { react { println it } } stop() }}
booth.join(); votes.stop(); votes.join()
You voted for GroovyYou voted for JRubySorry, please try againYou voted for GroovySorry, please try againSorry, please try again
…GPars: Actors
GPars - 42
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import groovyx.gpars.activeobject.*
@ActiveObjectclass VotingActiveObject { @ActiveMethod vote(String language) { processVote(language) } @ActiveMethod vote(List<String> languages) { languages.collect{ processVote it } } private processVote(language) { if (language.size() == 6) "You voted for $language" else 'Sorry, please try again' }}
def voter = new VotingActiveObject()def result1 = voter.vote('Scala')def result2 = voter.vote('Groovy')def result3 = voter.vote(['Pascal', 'Clojure', 'Groovy'])[result1.get(), result2.get(), *result3.get()].each{ println it }
Sorry, please try againYou voted for GroovyYou voted for PascalSorry, please try againYou voted for Groovy
Agents...• Agents safeguard non-thread safe objects• Only the agent can update the underlying
object• “Code” to update the protected object is
sent to the agent• Can be used with other approaches
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…Agents…
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def random = new Random()def randomDelay = { sleep random.nextInt(10) }String result = ''('a'..'z').each { letter -> Thread.start{ randomDelay() result += letter }}sleep 100 // poor man's join
println resultprintln result.size()
Unsafe!
…Agents…
GPars - 45
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import groovyx.gpars.agent.Agent
def random = new Random()def randomDelay = { sleep random.nextInt(10) }def agent = new Agent<String>('')('a'..'z').each { letter -> Thread.start{ randomDelay() agent.send{ updateValue it + letter } }}sleep 100 // poor man's joinString result = agent.valprintln resultprintln result.size()
…Agents
GPars - 46
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import groovyx.gpars.agent.Agent
def random = new Random()def randomDelay = { sleep random.nextInt(10) }def agent = new Agent<String>('')def threads = ('a'..'z').collect { letter -> Thread.start { randomDelay() agent.send{ updateValue it << letter } }}threads*.join()String result = agent.valprintln resultprintln result.size()
Software Transactional Memory…
GPars - 47
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@Grab('org.multiverse:multiverse-beta:0.7-RC-1')import org.multiverse.api.references.LongRefimport static groovyx.gpars.stm.GParsStm.atomicimport static org.multiverse.api.StmUtils.newLongRef
class Account { private final LongRef balance
Account(long initial) { balance = newLongRef(initial) }
void setBalance(long newBalance) { if (newBalance < 0) throw new RuntimeException("not enough money") balance.set newBalance }
long getBalance() { balance.get() }}// ...
…Software Transactional Memory
GPars - 48
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// ...def from = new Account(20)def to = new Account(20)def amount = 10
def watcher = Thread.start { 15.times { atomic { println "from: ${from.balance}, to: ${to.balance}" } sleep 100 }}sleep 150try { atomic { from.balance -= amount to.balance += amount sleep 500 } println 'transfer success'} catch(all) { println all.message}atomic { println "from: $from.balance, to: $to.balance" }
watcher.join()
Topics• Intro• Useful Groovy features for Concurrency• GParsCase Studies
Web TestingWord Split
• More Info• Bonus Material
GPars - 49
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GPars for testing
GPars - 50
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@Grab('net.sourceforge.htmlunit:htmlunit:2.6')import com.gargoylesoftware.htmlunit.WebClient@Grab('org.codehaus.gpars:gpars:0.10')import static groovyx.gpars.GParsPool.*
def testCases = [ ['Home', 'Bart', 'Content 1'], ['Work', 'Homer', 'Content 2'], ['Travel', 'Marge', 'Content 3'], ['Food', 'Lisa', 'Content 4']]
withPool(3) { testCases.eachParallel{ category, author, content -> postAndCheck category, author, content }}
private postAndCheck(category, author, content) { ...
Topics• Intro• Useful Groovy features for Concurrency• GParsCase Studies
Web TestingWord Split
• More Info• Bonus Material
GPars - 51
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Word Split with Fortress
GPars - 52
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Guy Steele’s StrangeLoop keynote (from slide 52 onwards for several slides):http://strangeloop2010.com/talk/presentation_file/14299/GuySteele-parallel.pdf
Word Split…
GPars - 53
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def swords = { s -> def result = [] def word = '' s.each{ ch -> if (ch == ' ') { if (word) result += word word = '' } else word += ch } if (word) result += word result}
assert swords("This is a sample") == ['This', 'is', 'a', 'sample']
assert swords("Here is a sesquipedalian string of words") == ['Here', 'is', 'a', 'sesquipedalian', 'string', 'of', 'words']
Word Split…
GPars - 54
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def swords = { s -> def result = [] def word = '' s.each{ ch -> if (ch == ' ') { if (word) result += word word = '' } else word += ch } if (word) result += word result}
Word Split…
GPars - 55
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def swords = { s -> def result = [] def word = '' s.each{ ch -> if (ch == ' ') { if (word) result += word word = '' } else word += ch } if (word) result += word result}
…Word Split…
GPars - 56
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…Word Split…
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Segment(left1, m1, right1) Segment(left2, m2, right2)
Segment(left1, m1 + [ ? ] + m2, right2)
…Word Split…
GPars - 58
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…Word Split…
GPars - 59
© ASERT 2006-
2013class Util { static maybeWord(s) { s ? [s] : [] } }import static Util.*
@Immutable class Chunk { String s public static final ZERO = new Chunk('') def plus(Chunk other) { new Chunk(s + other.s) } def plus(Segment other) { new Segment(s + other.l, other.m, other.r) } def flatten() { maybeWord(s) }}
@Immutable class Segment { String l; List m; String r public static final ZERO = new Segment('', [], '') def plus(Chunk other) { new Segment(l, m, r + other.s) } def plus(Segment other) { new Segment(l, m + maybeWord(r + other.l) + other.m, other.r) } def flatten() { maybeWord(l) + m + maybeWord(r) }}
…Word Split…
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def processChar(ch) { ch == ' ' ? new Segment('', [], '') : new Chunk(ch) }
def swords(s) { s.inject(Chunk.ZERO) { result, ch -> result + processChar(ch) } }
assert swords("Here is a sesquipedalian string of words").flatten() == ['Here', 'is', 'a', 'sesquipedalian', 'string', 'of', 'words']
…Word Split…
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…Word Split…
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…Word Split…
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© ASERT 2006-
2013THREADS = 4def pwords(s) { int n = (s.size() + THREADS - 1) / THREADS def map = new ConcurrentHashMap() (0..<THREADS).collect { i -> Thread.start { def (min, max) = [ [s.size(), i * n].min(), [s.size(), (i + 1) * n].min() ] map[i] = swords(s[min..<max]) } }*.join() (0..<THREADS).collect { i -> map[i] }.sum().flatten()}
…Word Split…
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© ASERT 2006-
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import static groovyx.gpars.GParsPool.withPool THRESHHOLD = 10 def partition(piece) { piece.size() <= THRESHHOLD ? piece : [piece[0..<THRESHHOLD]] + partition(piece.substring(THRESHHOLD))} def pwords = { input -> withPool(THREADS) { partition(input).parallel.map(swords).reduce{ a, b -> a + b }.flatten() }}
…Guy Steele example in Groovy…
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© ASERT 2006-
2013def words = { s -> int n = (s.size() + THREADS - 1) / THREADS def min = (0..<THREADS).collectEntries{ [it, [s.size(),it*n].min()] } def max = (0..<THREADS).collectEntries{ [it, [s.size(),(it+1)*n].min()] } def result = new DataFlows().with { task { a = swords(s[min[0]..<max[0]]) } task { b = swords(s[min[1]..<max[1]]) } task { c = swords(s[min[2]..<max[2]]) } task { d = swords(s[min[3]..<max[3]]) } task { sum1 = a + b } task { sum2 = c + d } task { sum = sum1 + sum2 } println 'Tasks ahoy!' sum } switch(result) { case Chunk: return maybeWord(result.s) case Segment: return result.with{ maybeWord(l) + m + maybeWord(r) } }}
DataFlow version: partially hard-coded to 4 partitions for easier reading
…Guy Steele example in Groovy…
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© ASERT 2006-
2013GRANULARITY_THRESHHOLD = 10THREADS = 4
println GParsPool.withPool(THREADS) { def result = runForkJoin(0, input.size(), input){ first, last, s -> def size = last - first if (size <= GRANULARITY_THRESHHOLD) { swords(s[first..<last]) } else { // divide and conquer def mid = first + ((last - first) >> 1) forkOffChild(first, mid, s) forkOffChild(mid, last, s) childrenResults.sum() } } switch(result) { case Chunk: return maybeWord(result.s) case Segment: return result.with{ maybeWord(l) + m + maybeWord(r) } }}
Fork/Join version
…Guy Steele example in Groovy
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© ASERT 2006-
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println GParsPool.withPool(THREADS) { def ans = input.collectParallel{ processChar(it) }.sum() switch(ans) { case Chunk: return maybeWord(ans.s) case Segment: return ans.with{ maybeWord(l) + m + maybeWord(r) } }}
Just leveraging the algorithm’s parallel nature
Topics• Intro• Useful Groovy features for Concurrency• Gpars• Case StudiesMore Info• Bonus Material
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More Information about Concurrency• Web sites
– http://gpars.codehaus.org/– http://g.oswego.edu/
Doug Lea's home page– http://gee.cs.oswego.edu/dl/concurrency-interest/– http://jcip.net/
Companion site for Java Concurrency in Practice– http://www.eecs.usma.edu/webs/people/okasaki/pubs.html#cup98
Purely Functional Data Structures– http://delicious.com/kragen/concurrency
Concurrency bookmark list– http://www.gotw.ca/publications/concurrency-ddj.htm
The Free Lunch is Over, Herb Sutter– http://manticore.cs.uchicago.edu/papers/damp07.pdf– http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10142
Concepts, Techniques, and Models of Computer Programming
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More Information about Groovy• Web sites
– http://groovy.codehaus.org– http://grails.codehaus.org– http://pleac.sourceforge.net/pleac_groovy (many examples)– http://www.asert.com.au/training/java/GV110.htm (workshop)
• Mailing list for users– [email protected]
• Information portals– http://www.aboutgroovy.org– http://www.groovyblogs.org
• Documentation (1000+ pages)– Getting Started Guide, User Guide, Developer Guide, Testing
Guide, Cookbook Examples, Advanced Usage Guide
• Books– Several to choose from ...
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More Information: Groovy in Action
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Contains a chapter on
GPars!
Bonus Material• Other concurrency options• Dining Philosopher Case Study
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Bonus Material• Other concurrency options
– Jetlang– JPPF– Multiverse– Gruple– Cascading– GridGain– ConTest
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Lightweight threads: Jetlang• Jetlang
– A high performance threading library– http://code.google.com/p/jetlang/
GPars - 74
import org.jetlang.fibers.ThreadFiberimport org.jetlang.channels.MemoryRequestChannelimport org.jetlang.channels.AsyncRequest
def req = new ThreadFiber() // or pooldef reply = new ThreadFiber()def channel = new MemoryRequestChannel()req.start()reply.start()
channel.subscribe(reply) { it.reply(it.request.sum()) }AsyncRequest.withOneReply(req, channel, [3, 4, 5]) { println it }
sleep 1000req.dispose()reply.dispose()
12
Other High-Level Libraries: JPPF– Open source Grid Computing platform– http://www.jppf.org/
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import org.jppf.client.*import java.util.concurrent.Callable
class Task implements Callable, Serializable { private static final long serialVersionUID = 1162L public Object call() { println 'Executing Groovy' "Hello JPPF from Groovy" }}def client = new JPPFClient()def job = new JPPFJob()def task = new Task()job.addTask taskdef results = client.submit(job)for (t in results) { if (t.exception) throw t.exception println "Result: " + t.result}
Other High-Level Libraries: Gruple...– http://code.google.com/p/gruple– Simple abstraction to coordinate and synchronize
threads with ease – based on Tuplespaces• Tuplespaces provide the illusion of a shared memory on top
of a message passing system, along with a small set of operations to greatly simplify parallel programming
– Example Tuple:[fname:"Vanessa", lname:"Williams", project:"Gruple"]
– Basic operations within a Tuplespace are:• put - insert a tuple into the space• get - read a tuple from the space (non-destructively)• take - take a tuple from the space (a destructive read)
– Further reading: Eric Freeman, Susanne Hupfer, and Ken Arnold. JavaSpaces Principles, Patterns, and Practice, Addison Wesley, 1999
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…Other High-Level Libraries: Gruple...
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import org.gruple.SpaceService
def defaultSpace = SpaceService.getSpace()defaultSpace << [fname:"Vanessa", lname:"Williams", project:"Gruple"]println defaultSpace.get(fname:"Vanessa", lname:"Williams", project:"Gruple")
[project:Gruple, lname:Williams, fname:Vanessa]
Other High-Level Libraries: ...Gruple...– Mandelbrot example (included in Gruple download)
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...Space space = SpaceService.getSpace("mandelbrot")
Map template = createTaskTemplate()Map task
String threadName = Thread.currentThread().namewhile(true) { ArrayList points task = space.take(template) println "Worker $threadName got task ${task['start']} for job ${task['jobId']}" points = calculateMandelbrot(task) Map result = createResult(task['jobId'], task['start'], points)
println "Worker $threadName writing result for task ${result['start']} for job ${result['jobId']}" space.put(result)}...
Other High-Level Libraries: ...Gruple
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Other High-Level Libraries: Cascading.groovy– API/DSL for executing tasks on a Hadoop cluster– http://www.cascading.org/
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def assembly = builder.assembly(name: "wordcount") { eachTuple(args: ["line"], results: ["word"]) { regexSplitGenerator(declared: ["word"], pattern: /[.,]*\s+/) } group(["word"]) everyGroup(args: ["word"], results: ["word", "count"]) { count() } group(["count"], reverse: true)}def map = builder.map() { source(name: "wordcount") { hfs(input) { text(["line"]) } } sink(name: "wordcount") { hfs(output) { text() } }}def flow = builder.flow(name: "wordcount", map: map, assembly: assembly)
Other High-Level Libraries: GridGain…– Simple & productive to use grid computing platform– http://www.gridgain.com/
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class GridHelloWorldGroovyTask extends GridTaskSplitAdapter<String, Integer> { Collection split(int gridSize, Object phrase) throws GridException { // ... } Object reduce(List results) throws GridException { // ... }} import static GridFactory.*
start()def grid = getGrid()def future = grid.execute(GridHelloWorldGroovyTask, "Hello World")def phraseLen = future.get()stop(true)
…Other High-Level Libraries: GridGain• http://gridgain.blogspot.com/2010/10/worlds-shortest-mapreduce-
app.html
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words = "Counting Letters In This Phrase".split(' ')map = new C1() { def apply(word) { word.size() } }reduce = sumIntReducer()println grid.forkjoin(SPREAD, yield(words, map), reduce)// => 27
grid.forkjoin(SPREAD,yield("Counting Letters In This Phrase".split(' '), new C1(){def apply(w){w.size()}}),sumReducer())
Testing multi-threaded applications: ConTest...• Advanced Testing for Multi-Threaded Applications
– Tool for testing, debugging, and coverage-measuring of concurrent programs (collects runtime statistics)
– Systematically and transparently (using a java agent) schedules the execution of program threads in ways likely to reveal race conditions, deadlocks, and other intermittent bugs (collectively called synchronization problems) with higher than normal frequency
– The ConTest run-time engine adds heuristically controlled conditional instructions (adjustable by a preferences file) that force thread switches, thus helping to reveal concurrent bugs. You can use existing tests and run ConTest multiple times – by default different heuristics used each time it is run
• http://www.alphaworks.ibm.com/tech/contest
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...Testing multi-threaded applications: ConTest
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NUM = 5count = 0def incThread = { n -> Thread.start{ sleep n*10 //synchronized(ParalInc) { count++ //}} }def threads = (1..NUM).collect(incThread)threads.each{ it.join() }assert count == NUM
targetClasses = ParalInctimeoutTampering = truenoiseFrequency = 500strength = 10000
Exception in thread "main" Assertion failed:
assert count == NUM | | | 4 | 5 false
> groovyc ParalInc.groovy> java -javaagent:../../Lib/ConTest.jar -cp %GROOVY_JAR%;. ParalInc
ParalInc.groovy
Bonus Material• Dining Philosopher’s Case Study
– GPars Actors– GPars CSP– Multiverse– Jetlang– Gruple
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Dining Philosophers…
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PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
…Dining Philosophers
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PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
PhilosopherThinking | Eating
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
ForkAvailable | InUse
Accepted | Rejected
Take | Release Take | Release
Dining Philosophers: Actors...
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© ASERT 2006-
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// adapted from GPars example, repo: http://git.codehaus.org/gitweb.cgi?p=gpars.git// file: src/test/groovy/groovyx/gpars/samples/actors/DemoDiningPhilosophers.groovy@Grab('org.codehaus.gpars:gpars:0.10')import groovyx.gpars.actor.*import groovy.beans.Bindable
def names = ['socrates', 'plato', 'aristotle', 'descartes', 'nietzsche']Actors.defaultActorPGroup.resize names.size()
class Philosopher extends AbstractPooledActor { private random = new Random() String name int timesEaten = 0 def forks @Bindable String status
void act() { assert 2 == forks.size() loop { think() forks*.send new Take() react {a -> react {b -> if ([a, b].any {Rejected.isCase it}) { [a, b].find {Accepted.isCase it}?.reply new Release() } else { eat() [a, b]*.reply new Release() } } } } }
…Dining Philosophers: Actors...
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© ASERT 2006-
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… void think() { setStatus('thinking') sleep random.nextInt(5000) setStatus('') }
void eat() { setStatus("eating ${++timesEaten}") sleep random.nextInt(3000) setStatus('') }
String toString() { switch (timesEaten) { case 0: return "$name has starved" case 1: return "$name has eaten once" default: return "$name has eaten $timesEaten times" } }}
final class Take {}final class Accepted {}final class Rejected {}final class Release {}
…Dining Philosophers: Actors...
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© ASERT 2006-
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…class Fork extends AbstractPooledActor { String name boolean available = true
void act() { loop { react {message -> switch (message) { case Take: if (available) { available = false reply new Accepted() } else reply new Rejected() break case Release: assert !available available = true break default: throw new IllegalStateException("Cannot process the message: $message") } } } }}
def forks = (1..names.size()).collect { new Fork(name: "Fork $it") }def philosophers = (1..names.size()).collect { new Philosopher(name: names[it - 1], forks: [forks[it - 1], forks[it % names.size()]])}
…Dining Philosophers: Actors
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© ASERT 2006-
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…import groovy.swing.*import java.awt.Fontimport static javax.swing.JFrame.*
def frame = new SwingBuilder().frame(title: 'Philosophers', defaultCloseOperation: EXIT_ON_CLOSE) { vbox { hbox { (0..<names.size()).each { i -> def widget = textField(id: names[i], text: names[i].center(14)) widget.font = new Font(widget.font.name, widget.font.style, 36) philosophers[i].propertyChange = { widget.text = philosophers[i].status.center(14) } } } }}
frame.pack()frame.visible = trueforks*.start()sleep 1000philosophers*.start()
sleep 10000
forks*.stop()forks*.join()philosophers*.stop()philosophers*.join()frame.dispose()philosophers.each { println it }
socrates has eaten 3 timesplato has eaten 3 timesaristotle has eaten 6 timesdescartes has eaten 2 timesnietzsche has eaten 5 times
Dining Philosophers: CSP...
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© ASERT 2006-
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// inspired by similar examples at the web sites below:// http://www.cs.kent.ac.uk/projects/ofa/jcsp/// http://www.soc.napier.ac.uk/~jmk/#_Toc271192596@Grab('org.codehaus.gpars:gpars:0.10')import org.jcsp.lang.*import groovyx.gpars.csp.PARimport groovyx.gpars.csp.ALTimport static java.lang.System.currentTimeMillis
def names = ['socrates', 'plato', 'aristotle', 'descartes', 'nietzsche']enum ForkAction { Take, Release, Stop }import static ForkAction.*
class Philosopher implements CSProcess { ChannelOutput leftFork, rightFork String name def forks = [] private random = new Random() private timesEaten = 0 private start = currentTimeMillis()
void run() { while (currentTimeMillis() - start < 10000) { think() eat() } [leftFork, rightFork].each { it.write(Stop) } println toString() } …
…Dining Philosophers: CSP...
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… void think() { println "$name is thinking" sleep random.nextInt(50) }
void eat() { [leftFork, rightFork].each { it.write(Take) } println "$name is EATING" timesEaten++ sleep random.nextInt(200) [leftFork, rightFork].each { it.write(Release) } }
String toString() { switch (timesEaten) { case 0: return "$name has starved" case 1: return "$name has eaten once" default: return "$name has eaten $timesEaten times" } }}
…Dining Philosophers: CSP...
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…class Fork implements CSProcess { ChannelInput left, right private active = [0, 1] as Set
void run() { def fromPhilosopher = [left, right] def forkAlt = new ALT(fromPhilosopher) while (active) { def i = forkAlt.select() read fromPhilosopher, i, Take read fromPhilosopher, i, Release } }
void read(phil, index, expected) { if (!active.contains(index)) return def m = phil[index].read() if (m == Stop) active -= index else assert m == expected }}…
…Dining Philosophers: CSP
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© ASERT 2006-
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…def lefts = Channel.createOne2One(names.size())def rights = Channel.createOne2One(names.size())
def philosophers = (0..<names.size()).collect { i -> return new Philosopher(leftFork: lefts[i].out(), rightFork: rights[i].out(), name: names[i])}
def forks = (0..<names.size()).collect { i -> return new Fork(left: lefts[i].in(), right: rights[(i + 1) % names.size()].in())}
def processList = philosophers + forks
new PAR(processList).run()
Why CSP?• Amenable to proof
and analysis
GPars - 96Picture source: http://wotug.org/parallel/theory/formal/csp/Deadlock/
Multiverse Philosophers…
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//@Grab('org.multiverse:multiverse-core:0.7-SNAPSHOT')//@Grab('org.multiverse:multiverse-alpha:0.7-SNAPSHOT')//@Grab('org.multiverse:multiverse-groovy:0.7-SNAPSHOT')//@GrabConfig(systemClassLoader=true, initContextClassLoader = true)// adapted multiverse Groovy example: http://git.codehaus.org/gitweb.cgi?p=multiverse.git// file: multiverse-groovy/src/test/groovy/org/multiverse/integration/org/multiverse/integration/examples/DiningPhilosphersTest.groovyimport org.multiverse.transactional.refs.BooleanRefimport org.multiverse.transactional.refs.IntRefimport static MultiverseGroovyLibrary.*
def food = new IntRef(5)def names = ['socrates', 'plato', 'aristotle', 'descartes', 'nietzsche']def forks = (1..5).collect { new Fork(id: it, free: new BooleanRef(true)) }def philosophers = (0..4).collect { new Philosopher(name: names[it], food: food, left: forks[(it + 1) % 5], right: forks[it])}def threads = philosophers.collect { new Thread(it) }threads*.start()threads*.join()philosophers.each { println it }
class Fork { int id BooleanRef free void take() { free.set(false) } void release() { free.set(true) }}
…Multiverse Philosophers
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class Philosopher implements Runnable { String name Fork left, right IntRef timesEaten = new IntRef() IntRef food
void eat() { atomic(trackreads: true, explicitRetryAllowed: true) { left.free.await(true) right.free.await(true) if (food.get() > 0) { left.take(); right.take() timesEaten.inc(); sleep 10; food.dec() } } }
void think() { atomic(trackreads: true, explicitRetryAllowed: true) { left.release(); right.release() } sleep 10 }
void run() { 10.times { eat(); think() } }
String toString() { switch (timesEaten) { case 0: return "$name has starved" case 1: return "$name has eaten once" default: return "$name has eaten $timesEaten times" } }}
Jetlang Philosophers…
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import org.jetlang.core.Callbackimport org.jetlang.fibers.ThreadFiberimport org.jetlang.channels.*
def names = ['socrates', 'plato', 'aristotle', 'descartes', 'nietzsche']
class Philosopher implements Callback { private random = new Random() String name int timesEaten = 0 String status def forks private channels = [new MemoryRequestChannel(), new MemoryRequestChannel()] private req = new ThreadFiber() private reply = new ThreadFiber() private responses = [] private gotFork = { it instanceof Accepted }
void start() { assert forks.size() == 2 req.start() reply.start() (0..1).each{ channels[it].subscribe(reply, forks[it]) } think() }
String toString() { switch (timesEaten) { case 0: return "$name has starved" case 1: return "$name has eaten once" default: return "$name has eaten $timesEaten times" } } …
…Jetlang Philosophers…
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… void think() { println(name + ' is thinking') sleep random.nextInt(3000) (0..1).each{ AsyncRequest.withOneReply(req, channels[it], new Take(it), this); } }
void eat() { timesEaten++ println toString() sleep random.nextInt(2000) }
void onMessage(Object message) { responses << message if (responses.size() == 2) { if (responses.every(gotFork)) { eat() } responses.findAll(gotFork).each { int index = it.index channels[index].publish(req, new Release(index), forks[index]) } responses = [] think() } }}
@Immutable class Take { int index }@Immutable class Accepted { int index }@Immutable class Rejected { int index }@Immutable class Release { int index }…
…Jetlang Philosophers
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…class Fork implements Callback { String name def holder = []
void onMessage(message) { def msg = message instanceof Request ? message.request : message def index = msg.index switch (msg) { case Take: if (!holder) { holder << index message.reply(new Accepted(index)) } else message.reply(new Rejected(index)) break case Release: assert holder == [index] holder = [] break default: throw new IllegalStateException("Cannot process the message: $message") } }}
def forks = (1..names.size()).collect { new Fork(name: "Fork $it") }def philosophers = (1..names.size()).collect { new Philosopher(name: names[it - 1], forks: [forks[it - 1], forks[it % names.size()]])}
philosophers*.start()sleep 10000philosophers.each { println it }
Gruple Philosophers…
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import org.gruple.SpaceServiceimport org.gruple.Space
class Philosopher { private random = new Random() String name Space space private timesEaten = 0 int id, num boolean done = false
void run() { while (true) { think() if (done) return space.take(fork: id) space.take(fork: (id + 1) % num) eat() space.put(fork: id) space.put(fork: (id + 1) % num) } }
void think() { println "$name is thinking" sleep random.nextInt(500) }
void eat() { println "$name is EATING" timesEaten++ sleep random.nextInt(1000) } …
…socrates is thinkingnietzsche is thinkingdescartes is EATINGaristotle is EATINGdescartes is thinkingplato is EATINGaristotle is thinkingsocrates is EATINGplato is thinkingnietzsche is EATINGsocrates is thinkingnietzsche is thinkingdescartes is EATINGdescartes is thinking
socrates has eaten 5 timesplato has eaten 4 timesaristotle has eaten 4 timesdescartes has eaten 4 timesnietzsche has eaten 5 times
…Gruple Philosophers
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… String toString() { switch (timesEaten) { case 0: return "$name has starved" case 1: return "$name has eaten once" default: return "$name has eaten $timesEaten times" } }}
def names = ['socrates', 'plato', 'aristotle', 'descartes', 'nietzsche']def diningSpace = SpaceService.getSpace('Dining')def philosophers = (0..<names.size()).collect{ new Philosopher(name: names[it], id: it, space: diningSpace, num: names.size())}(0..<names.size()).each{ diningSpace << [fork: it] }sleep 500def threads = (0..<names.size()).collect{ n -> Thread.start{ philosophers[n].run() } }sleep 10000philosophers*.done = truesleep 2000threads.join()println()philosophers.each{ println it }