test/extra166y/MapReduceDemo.java

/*
 * Written by Doug Lea with assistance from members of JCP JSR-166
 * Expert Group and released to the public domain, as explained at
 * http://creativecommons.org/publicdomain/zero/1.0/
 */

import jsr166y.*;
import extra166y.*;
import java.util.*;
import java.util.concurrent.*;

public class MapReduceDemo {
    static final int NCPU = Runtime.getRuntime().availableProcessors();
    static final Random rng = new Random();

    /**
     * Sequential version, for performance comparison
     */
    static <T,U> U seqMapReduce(T[] array,
                                Ops.Op<T,U> mapper,
                                Ops.Reducer<U> reducer,
                                U base) {
        int n = array.length;
        U x = base;
        for (int i = 0; i < n; ++i)
            x = reducer.op(x, mapper.op(array[i]));
        return x;
    }


    // sample functions
    static final class GetNext implements Ops.Op<Rand, Long> {
        public Long op(Rand x) {
            return x.next();
        }
    }

    static final class Accum implements Ops.Reducer<Long> {
        public Long op(Long a, Long b) {
            long x = a;
            long y = b;
            return x + y;
        }
    }

    /** for time conversion */
    static final long NPS = (1000L * 1000 * 1000);

    public static void main(String[] args) throws Exception {
        int n = 1 << 18;
        int reps = 1 << 8;
        Rand[] array = new Rand[n];
        for (int i = 0; i < n; ++i)
            array[i] = new Rand(i+1);
        ForkJoinPool fjp = new ForkJoinPool();
        ParallelArray<Rand> pa = ParallelArray.createUsingHandoff(array, fjp);
        final GetNext getNext = new GetNext();
        final Accum accum = new Accum();
        final Long zero = Long.valueOf(0);
        long last, now;
        double elapsed;
        for (int j = 0; j < 2; ++j) {
            long rseed = rng.nextLong();
            resetSeeds(array, rseed);
            long seqsum = 0;
            last = System.nanoTime();
            for (int k = 0; k < reps; ++k) {
                seqsum += seqMapReduce(array, getNext, accum, zero);
                Rand tmp = array[k];
                array[k] = array[n - k - 1];
                array[n - k - 1] = tmp;
            }
            now = System.nanoTime();
            elapsed = (double)(now - last) / NPS;
            last = now;
            System.out.printf("sequential:    %7.3f\n", elapsed);
            for (int i = 2; i <= NCPU; i <<= 1) {
                resetSeeds(array, rseed);
                long sum = 0;
                //                fjp.setParallelism(i);
                last = System.nanoTime();
                for (int k = 0; k < reps; ++k) {
                    sum += pa.withMapping(getNext).reduce(accum, zero);
                    Rand tmp = array[k];
                    array[k] = array[n - k - 1];
                    array[n - k - 1] = tmp;
                }
                now = System.nanoTime();
                elapsed = (double)(now - last) / NPS;
                last = now;
                System.out.printf("poolSize %3d:  %7.3f\n", fjp.getParallelism(), elapsed);
                if (sum != seqsum) throw new Error("checksum");
            }
            for (int i = NCPU; i >= 1; i >>>= 1) {
                resetSeeds(array, rseed);
                long sum = 0;
                //                fjp.setParallelism(i);
                last = System.nanoTime();
                for (int k = 0; k < reps; ++k) {
                    sum += pa.withMapping(getNext).reduce(accum, zero);
                    Rand tmp = array[k];
                    array[k] = array[n - k - 1];
                    array[n - k - 1] = tmp;
                }
                now = System.nanoTime();
                elapsed = (double)(now - last) / NPS;
                last = now;
                System.out.printf("poolSize %3d:  %7.3f\n", fjp.getParallelism(), elapsed);
                if (sum != seqsum) throw new Error("checksum");
            }
        }
        fjp.shutdownNow();
        fjp.awaitTermination(1, TimeUnit.SECONDS);
        Thread.sleep(100);
    }

    static void resetSeeds(Rand[] array, long s) {
        for (int i = 0; i < array.length; ++i)
            array[i].seed = s++;
    }

    /**
     * Xorshift Random algorithm.
     */
    public static final class Rand {
        private long seed;
        Rand(long s) {
            seed = s;
        }
        public long next() {
            long x = seed;
            x ^= x << 13;
            x ^= x >>> 7;
            x ^= (x << 17);
            seed = x;
            return x;
        }
    }

}
Revision:	1.6
Committed:	Fri Sep 27 17:07:44 2013 UTC (10 years, 6 months ago) by jsr166
Branch:	MAIN
CVS Tags:	HEAD
Changes since 1.5:	+4 -4 lines
Log Message:	No spaces separating one-character type parameters
#	Content
1	/*
2	* Written by Doug Lea with assistance from members of JCP JSR-166
3	* Expert Group and released to the public domain, as explained at
4	* http://creativecommons.org/publicdomain/zero/1.0/
5	*/
6
7	import jsr166y.*;
8	import extra166y.*;
9	import java.util.*;
10	import java.util.concurrent.*;
11
12	public class MapReduceDemo {
13	static final int NCPU = Runtime.getRuntime().availableProcessors();
14	static final Random rng = new Random();
15
16	/**
17	* Sequential version, for performance comparison
18	*/
19	static <T,U> U seqMapReduce(T[] array,
20	Ops.Op<T,U> mapper,
21	Ops.Reducer<U> reducer,
22	U base) {
23	int n = array.length;
24	U x = base;
25	for (int i = 0; i < n; ++i)
26	x = reducer.op(x, mapper.op(array[i]));
27	return x;
28	}
29
30
31
32	// sample functions
33	static final class GetNext implements Ops.Op<Rand, Long> {
34	public Long op(Rand x) {
35	return x.next();
36	}
37	}
38
39	static final class Accum implements Ops.Reducer<Long> {
40	public Long op(Long a, Long b) {
41	long x = a;
42	long y = b;
43	return x + y;
44	}
45	}
46
47	/** for time conversion */
48	static final long NPS = (1000L * 1000 * 1000);
49
50	public static void main(String[] args) throws Exception {
51	int n = 1 << 18;
52	int reps = 1 << 8;
53	Rand[] array = new Rand[n];
54	for (int i = 0; i < n; ++i)
55	array[i] = new Rand(i+1);
56	ForkJoinPool fjp = new ForkJoinPool();
57	ParallelArray<Rand> pa = ParallelArray.createUsingHandoff(array, fjp);
58	final GetNext getNext = new GetNext();
59	final Accum accum = new Accum();
60	final Long zero = Long.valueOf(0);
61	long last, now;
62	double elapsed;
63	for (int j = 0; j < 2; ++j) {
64	long rseed = rng.nextLong();
65	resetSeeds(array, rseed);
66	long seqsum = 0;
67	last = System.nanoTime();
68	for (int k = 0; k < reps; ++k) {
69	seqsum += seqMapReduce(array, getNext, accum, zero);
70	Rand tmp = array[k];
71	array[k] = array[n - k - 1];
72	array[n - k - 1] = tmp;
73	}
74	now = System.nanoTime();
75	elapsed = (double)(now - last) / NPS;
76	last = now;
77	System.out.printf("sequential: %7.3f\n", elapsed);
78	for (int i = 2; i <= NCPU; i <<= 1) {
79	resetSeeds(array, rseed);
80	long sum = 0;
81	// fjp.setParallelism(i);
82	last = System.nanoTime();
83	for (int k = 0; k < reps; ++k) {
84	sum += pa.withMapping(getNext).reduce(accum, zero);
85	Rand tmp = array[k];
86	array[k] = array[n - k - 1];
87	array[n - k - 1] = tmp;
88	}
89	now = System.nanoTime();
90	elapsed = (double)(now - last) / NPS;
91	last = now;
92	System.out.printf("poolSize %3d: %7.3f\n", fjp.getParallelism(), elapsed);
93	if (sum != seqsum) throw new Error("checksum");
94	}
95	for (int i = NCPU; i >= 1; i >>>= 1) {
96	resetSeeds(array, rseed);
97	long sum = 0;
98	// fjp.setParallelism(i);
99	last = System.nanoTime();
100	for (int k = 0; k < reps; ++k) {
101	sum += pa.withMapping(getNext).reduce(accum, zero);
102	Rand tmp = array[k];
103	array[k] = array[n - k - 1];
104	array[n - k - 1] = tmp;
105	}
106	now = System.nanoTime();
107	elapsed = (double)(now - last) / NPS;
108	last = now;
109	System.out.printf("poolSize %3d: %7.3f\n", fjp.getParallelism(), elapsed);
110	if (sum != seqsum) throw new Error("checksum");
111	}
112	}
113	fjp.shutdownNow();
114	fjp.awaitTermination(1, TimeUnit.SECONDS);
115	Thread.sleep(100);
116	}
117
118	static void resetSeeds(Rand[] array, long s) {
119	for (int i = 0; i < array.length; ++i)
120	array[i].seed = s++;
121	}
122
123	/**
124	* Xorshift Random algorithm.
125	*/
126	public static final class Rand {
127	private long seed;
128	Rand(long s) {
129	seed = s;
130	}
131	public long next() {
132	long x = seed;
133	x ^= x << 13;
134	x ^= x >>> 7;
135	x ^= (x << 17);
136	seed = x;
137	return x;
138	}
139	}
140
141	}