This document introduces GPars, a Groovy/Java framework for expressing parallelism. It discusses how Moore's Law has led to ubiquitous parallelism due to more cores. GPars makes parallel programming easier by offering models like actors, dataflow, and CSP. It builds on Java concurrency utilities and works well for Groovy scripts and Java. GPars allows parallel collection operations to speed up tasks like calculating pi in parallel.

1. GPars
Parallelism the Right Way
Dr Russel Winder
It’z Interactive Ltd
russel@itzinteractive.com
russel@russel.org.uk
@russel_winder
Copyright © 2011 Russel Winder 1

2. Moore's Law
● More transistors.
● More cores.
● More parallelism.
● Ubiqitous parallelism.
Copyright © 2011 Russel Winder 2

3. Caveat
● Not all applications require parallelism.
● I/O bound best handled with single threaded event
loop.
Copyright © 2011 Russel Winder 3

4. Where Parallelism Is Needed
● Operating systems offer threads as access to the
cores.
● Languages offer threads as infrastructure.
Copyright © 2011 Russel Winder 4

5. Hummm...
● Shared memory multithreading is hard.
● Locks, semaphores, monitors, …
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6. Models of Management
● Actors
● Dataflow
● Communicating Sequential Processes (CSP)
● Data parallelism
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7. GPars
● A Groovy/Java implemented framework for easy
expression of parallelism.
● Offers:
– Actors
– Dataflow
– CSP
– Data parallelism
Copyright © 2011 Russel Winder 7

8. Builds on…
● GPars builds on java.util.concurrent and all the
JSR166 goodness.
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9. Usage
● GPars works supremely well in Groovy scripts that
manage Groovy and Java classes.
● GPars works very well as a Java API.
Copyright © 2011 Russel Winder 9

10. @Grab ( 'org.codehaus.gpars:gpars:1.0-SNAPSHOT' )
import groovyx.gpars.GParsPool
void execute ( final int numberOfTasks ) {
GParsPool.withPool {
final int n = 100000000i
final double delta = 1.0d / n
final startTimeNanos = System.nanoTime ( )
final int sliceSize = n / numberOfTasks
final items = [ ]
for ( int i in 0i ..< numberOfTasks ) { items << i }
final pi = 4.0d * delta * items.collectParallel { taskId ->
final int start = 1i + taskId * sliceSize
final int end = ( taskId + 1i ) * sliceSize
double sum = 0.0d ;
for ( int i in start .. end ) {
final double x = ( i - 0.5d ) * delta
sum += 1.0d / ( 1.0d + x * x )
}
sum
}.sumParallel ( )
final elapseTime = ( System.nanoTime ( ) - startTimeNanos ) / 1e9
println ( '==== Groovy GPars GParsPool pi = ' + pi )
println ( '==== Groovy GPars GParsPool iteration count = ' + n )
println ( '==== Groovy GPars GParsPool elapse = ' + elapseTime )
println ( '==== Groovy GPars GParsPool processor count = ' + Runtime.getRuntime ( ).availableProcessors ( ) )
println ( '==== Groovy GPars GParsPool task count = ' + numberOfTasks )
}
}
Copyright © 2011 Russel Winder 10

11. @Grab ( 'org.codehaus.gpars:gpars:1.0-SNAPSHOT' )
import groovyx.gpars.ParallelEnhancer
void execute ( final int numberOfTasks ) {
final int n = 100000000i
final double delta = 1.0d / n
final startTimeNanos = System.nanoTime ( )
final int sliceSize = n / numberOfTasks
final items = [ ]
for ( int i in 0i ..< numberOfTasks ) { items << i }
ParallelEnhancer.enhanceInstance ( items )
final pi = 4.0d * delta * items.collectParallel { taskId ->
final int start = 1i + taskId * sliceSize
final int end = ( taskId + 1i ) * sliceSize
double sum = 0.0d ;
for ( int i in start .. end ) {
final double x = ( i - 0.5d ) * delta
sum += 1.0d / ( 1.0d + x * x )
}
sum
}.sumParallel ( )
final elapseTime = ( System.nanoTime ( ) - startTimeNanos ) / 1e9
println ( '==== Groovy GPars ParallelEnhancer pi = ' + pi )
println ( '==== Groovy GPars ParallelEnhancer iteration count = ' + n )
println ( '==== Groovy GPars ParallelEnhancer elapse = ' + elapseTime )
println ( '==== Groovy GPars ParallelEnhancer processor count = ' + Runtime.getRuntime
( ).availableProcessors ( ) )
println ( '==== Groovy GPars ParallelEnhancer task count = ' + numberOfTasks )
}
Copyright © 2011 Russel Winder 11

12. GPars
Check it out, you know you
want to.
http://gpars.codehaus.org/
Copyright © 2011 Russel Winder 12

13. Mandatory Book Advert
Python for Rookies
Sarah Mount, James Shuttleworth and
Russel Winder
Thomson Learning Now called Cengage Learning.
Developing Java Software Third Edition
Russel Winder and Graham Roberts
Wiley
Buy these books!
Copyright © 2010 Russel Winder 13

14. GPars
Parallelism the Right Way
Dr Russel Winder
It’z Interactive Ltd
russel@itzinteractive.com
russel@russel.org.uk
@russel_winder
Copyright © 2011 Russel Winder 14