Gaussian distribution in Java 8 with parallel Streams and LongAdder

LongAdderTest.java

import java.util.Random;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.LongAdder;
import java.util.stream.IntStream;

public class LongAdderTest {
    ConcurrentHashMap<Integer,LongAdder> frequencyMap = new ConcurrentHashMap<>() ;
    Random rnd = new Random() ;

    void run() {
        IntStream.range( 0, 10000 )
                 .parallel()
                 .forEach( ( n ) -> {
                     Integer key = Double.valueOf( rnd.nextGaussian() + 5 ).intValue() ;
                     frequencyMap.computeIfAbsent( key, ( k ) -> new LongAdder() ).increment() ;
                 } ) ;
        System.out.println( frequencyMap );
    }

    public static void main( String[] args ) {
        new LongAdderTest().run() ;
    }
}

LongGroovyAdder1.groovy

// Requires Java 8 and Groovy 2.3

import java.util.concurrent.ConcurrentHashMap
import java.util.concurrent.atomic.LongAdder
import static groovyx.gpars.GParsPool.withPool

new Random().with { rnd ->
    new ConcurrentHashMap<Integer,LongAdder>().with { frequencyMap ->
        withPool {    
            (0..10000).eachParallel { n ->
                Integer key = rnd.nextGaussian() + 5
                frequencyMap.computeIfAbsent( key, { k -> new LongAdder() } ).increment()
            }
        }
        println frequencyMap
    }
}

LongGroovyAdder2.groovy

// Requires Java 8 and Groovy 2.3

import java.util.concurrent.ConcurrentHashMap
import java.util.concurrent.atomic.LongAdder
import java.util.stream.IntStream;

new Random().with { rnd ->
    new ConcurrentHashMap<Integer,LongAdder>().with { frequencyMap ->
        IntStream.range( 0, 10000 )
                 .parallel()
                 .forEach { n ->
                     Integer key = rnd.nextGaussian() + 5
                     frequencyMap.computeIfAbsent( key, { k -> new LongAdder() } ).increment()
                 }
        println frequencyMap
    }
}