src/jsr166e/StripedAdder.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/
 */

package jsr166e;
import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.io.IOException;
import java.io.Serializable;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;

/**
 * A set of variables that together maintain a sum.  When updates
 * (method {@link #add}) are contended across threads, this set of
 * adder variables may grow dynamically to reduce contention. Method
 * {@link #sum} returns the current combined total across these
 * adders. This value is <em>NOT</em> an atomic snapshot (concurrent
 * updates may occur while the sum is being calculated), and so cannot
 * be used alone for fine-grained synchronization control.
 *
 * <p> This class may be applicable when many threads frequently
 * update a common sum that is used for purposes such as collecting
 * statistics. In this case, performance may be significantly faster
 * than using a shared {@link AtomicLong}, at the expense of using
 * much more space.  On the other hand, if it is known that only one
 * thread can ever update the sum, performance may be significantly
 * slower than just updating a local variable.
 *
 * <p>A StripedAdder may optionally be constructed with a given
 * expected contention level; i.e., the number of threads that are
 * expected to concurrently update the sum. Supplying an accurate
 * value may improve performance by reducing the need for dynamic
 * adjustment.
 *
 * @author Doug Lea
 */
public class StripedAdder implements Serializable {
    private static final long serialVersionUID = 7249069246863182397L;

    /*
     * A StripedAdder maintains a table of Atomic long variables. The
     * table is indexed by per-thread hash codes.
     *
     * By default, the table is lazily initialized, to minimize
     * footprint until adders are used. On first use, the table is set
     * to size DEFAULT_INITIAL_SIZE (currently 8). Table size is
     * bounded by the number of CPUS (if larger than the default
     * size).
     *
     * Per-thread hash codes are initialized to random values.
     * Collisions are indicated by failed CASes when performing an add
     * operation (see method retryAdd). Upon a collision, if the table
     * size is less than the capacity, it is doubled in size unless
     * some other thread holds lock. If a hashed slot is empty, and
     * lock is available, a new Adder is created. Otherwise, if the
     * slot exists, a CAS is tried.  Retries proceed by "double
     * hashing", using a secondary hash (Marsaglia XorShift) to try to
     * find a free slot.
     *
     * The table size is capped because, when there are more threads
     * than CPUs, supposing that each thread were bound to a CPU,
     * there would exist a perfect hash function mapping threads to
     * slots that eliminates collisions. When we reach capacity, we
     * search for this mapping by randomly varying the hash codes of
     * colliding threads.  Because search is random, and failures only
     * become known via CAS failures, convergence will be slow, and
     * because threads are typically not bound to CPUS forever, may
     * not occur at all. However, despite these limitations, observed
     * contention is typically low in these cases.
     *
     * Table entries are of class Adder; a form of AtomicLong padded
     * to reduce cache contention on most processors. Padding is
     * overkill for most Atomics because they are usually irregularly
     * scattered in memory and thus don't interfere much with each
     * other. But Atomic objects residing in arrays will tend to be
     * placed adjacent to each other, and so will most often share
     * cache lines without this precaution.  Adders are by default
     * constructed upon first use, which further improves per-thread
     * locality and helps reduce footprint.
     *
     * A single spinlock is used for resizing the table as well as
     * populating slots with new Adders. Upon lock contention, threads
     * try other slots rather than blocking. After initialization, at
     * least one slot exists, so retries will eventually find a
     * candidate Adder.  During these retries, there is increased
     * contention and reduced locality, which is still better than
     * alternatives.
     */

    /**
     * Padded version of AtomicLong
     */
    static final class Adder extends AtomicLong {
        long p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, pa, pb, pc, pd, pe;
        Adder(long x) { super(x); }
    }

    private static final int NCPU = Runtime.getRuntime().availableProcessors();

    /**
     * Table bounds. DEFAULT_INITIAL_SIZE is the table size set upon
     * first use under default constructor, and must be a power of
     * two. There is not much point in making size a lot smaller than
     * that of Adders though.  CAP is the maximum allowed table size.
     */
    private static final int DEFAULT_INITIAL_SIZE = 8;
    private static final int CAP = Math.max(NCPU, DEFAULT_INITIAL_SIZE);

    /**
     * Holder for the thread-local hash code. The code is initially
     * random, but may be set to a different value upon collisions.
     */
    static final class HashCode {
        static final Random rng = new Random();
        int code;
        HashCode() {
            int h = rng.nextInt();
            code = (h == 0) ? 1 : h; // ensure nonzero
        }
    }

    /**
     * The corresponding ThreadLocal class
     */
    static final class ThreadHashCode extends ThreadLocal<HashCode> {
        public HashCode initialValue() { return new HashCode(); }
    }

    /**
     * Static per-thread hash codes. Shared across all StripedAdders
     * to reduce ThreadLocal pollution and because adjustments due to
     * collisions in one table are likely to be appropriate for
     * others.
     */
    static final ThreadHashCode threadHashCode = new ThreadHashCode();

    /**
     * Common placeholder for empty arrays.
     */
    static final Adder[] EMPTY_ARRAY = new Adder[0];

    /**
     * Table of adders. Size is either zero or a power of two, grows
     * to be at most CAP.
     */
    private transient volatile Adder[] adders;

    /**
     * Serves as a lock when resizing and/or creating Adders.  There
     * is no need for a blocking lock: Except during initialization
     * races, when busy, other threads try other slots. However,
     * during (double-checked) initializations, we use the
     * "synchronized" lock on this object.
     */
    private final AtomicInteger mutex;

    /**
     * Creates a new adder with zero sum.
     */
    public StripedAdder() {
        this.adders = EMPTY_ARRAY;
        this.mutex = new AtomicInteger();
        // remaining initialization on first call to add.
    }

    /**
     * Creates a new adder with zero sum, and with stripes presized
     * for the given expected contention level.
     *
     * @param expectedContention the expected number of threads that
     * will concurrently update the sum.
     */
    public StripedAdder(int expectedContention) {
        if (expectedContention > 0) {
            int cap = (expectedContention < CAP) ? expectedContention : CAP;
            int size = 1;
            while (size < cap)
                size <<= 1;
            Adder[] as = new Adder[size];
            for (int i = 0; i < size; ++i)
                as[i] = new Adder(0);
            this.adders = as;
        }
        else
            this.adders = EMPTY_ARRAY;
        this.mutex = new AtomicInteger();
    }

    /**
     * Adds the given value.
     *
     * @param x the value to add
     */
    public void add(long x) {
        Adder[] as; Adder a; int n; long v; // locals to hold volatile reads
        HashCode hc = threadHashCode.get();
        int h = hc.code;
        if ((as = adders) == null || (n = as.length) < 1 ||
            (a = as[(n - 1) & h]) == null ||
            !a.compareAndSet(v = a.get(), v + x))
            retryAdd(x, hc);
    }

    /**
     * Handle cases of add involving initialization, resizing,
     * creating new Adders, and/or contention. See above for
     * explanation.
     */
    private void retryAdd(long x, HashCode hc) {
        int h = hc.code;
        final AtomicInteger mutex = this.mutex;
        int collisions = 1 - mutex.get(); // first guess: collides if not locked
        for (;;) {
            Adder[] as; Adder a; long v; int k, n;
            while ((as = adders) == null || (n = as.length) < 1) {
                synchronized(mutex) {                // Try to initialize
                    if (adders == as) {
                        Adder[] rs = new Adder[DEFAULT_INITIAL_SIZE];
                        rs[h & (DEFAULT_INITIAL_SIZE - 1)] = new Adder(0);
                        adders = rs;
                    }
                }
                collisions = 0;
            }

            if ((a = as[k = (n - 1) & h]) == null) { // Try to add slot
                if (mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
                    try {
                        if (adders == as && as[k] == null)
                            a = as[k] = new Adder(x);
                    } finally {
                        mutex.set(0);
                    }
                    if (a != null)
                        break;
                }
                collisions = 0;
            }
            else if (collisions != 0 && n < CAP &&   // Try to expand table
                     mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
                try {
                    if (adders == as) {
                        Adder[] rs = new Adder[n << 1];
                        for (int i = 0; i < n; ++i)
                            rs[i] = as[i];
                        adders = rs;
                    }
                } finally {
                    mutex.set(0);
                }
                collisions = 0;
            }
            else if (a.compareAndSet(v = a.get(), v + x))
                break;
            else
                collisions = 1;
            h ^= h << 13;                            // Rehash
            h ^= h >>> 17;
            h ^= h << 5;
        }
        hc.code = h;
    }

    /**
     * Returns an estimate of the current sum.  The result is
     * calculated by summing multiple variables, so may not be
     * accurate if updates occur concurrently with this method.
     *
     * @return the estimated sum
     */
    public long sum() {
        long sum = 0L;
        Adder[] as = adders;
        if (as != null) {
            int n = as.length;
            for (int i = 0; i < n; ++i) {
                Adder a = as[i];
                if (a != null)
                    sum += a.get();
            }
        }
        return sum;
    }

    /**
     * Resets each of the variables to zero. This is effective in
     * fully resetting the sum only if there are no concurrent
     * updates.
     */
    public void reset() {
        Adder[] as = adders;
        if (as != null) {
            int n = as.length;
            for (int i = 0; i < n; ++i) {
                Adder a = as[i];
                if (a != null)
                    a.set(0L);
            }
        }
    }

    /**
     * Equivalent to {@code add(1)}.
     */
    public void increment() {
        add(1L);
    }

    /**
     * Equivalent to {@code add(-1)}.
     */
    public void decrement() {
        add(-1L);
    }

    /**
     * Equivalent to {@link #sum} followed by {@link #reset}.
     *
     * @return the estimated sum
     */
    public long sumAndReset() {
        long sum = 0L;
        Adder[] as = adders;
        if (as != null) {
            int n = as.length;
            for (int i = 0; i < n; ++i) {
                Adder a = as[i];
                if (a != null) {
                    sum += a.get();
                    a.set(0L);
                }
            }
        }
        return sum;
    }

    private void writeObject(java.io.ObjectOutputStream s)
        throws java.io.IOException {
        s.defaultWriteObject();
        s.writeLong(sum());
    }

    private void readObject(ObjectInputStream s)
        throws IOException, ClassNotFoundException {
        s.defaultReadObject();
        mutex.set(0);
        add(s.readLong());
    }

}
Revision:	1.7
Committed:	Tue Jul 26 18:30:35 2011 UTC (12 years, 10 months ago) by dl
Branch:	MAIN
Changes since 1.6:	+21 -10 lines
Log Message:	Use common empty placeholder
#	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	package jsr166e;
8	import java.util.Arrays;
9	import java.util.Random;
10	import java.util.concurrent.atomic.AtomicInteger;
11	import java.util.concurrent.atomic.AtomicLong;
12	import java.io.IOException;
13	import java.io.Serializable;
14	import java.io.ObjectInputStream;
15	import java.io.ObjectOutputStream;
16
17	/**
18	* A set of variables that together maintain a sum. When updates
19	* (method {@link #add}) are contended across threads, this set of
20	* adder variables may grow dynamically to reduce contention. Method
21	* {@link #sum} returns the current combined total across these
22	* adders. This value is <em>NOT</em> an atomic snapshot (concurrent
23	* updates may occur while the sum is being calculated), and so cannot
24	* be used alone for fine-grained synchronization control.
25	*
26	* <p> This class may be applicable when many threads frequently
27	* update a common sum that is used for purposes such as collecting
28	* statistics. In this case, performance may be significantly faster
29	* than using a shared {@link AtomicLong}, at the expense of using
30	* much more space. On the other hand, if it is known that only one
31	* thread can ever update the sum, performance may be significantly
32	* slower than just updating a local variable.
33	*
34	* <p>A StripedAdder may optionally be constructed with a given
35	* expected contention level; i.e., the number of threads that are
36	* expected to concurrently update the sum. Supplying an accurate
37	* value may improve performance by reducing the need for dynamic
38	* adjustment.
39	*
40	* @author Doug Lea
41	*/
42	public class StripedAdder implements Serializable {
43	private static final long serialVersionUID = 7249069246863182397L;
44
45	/*
46	* A StripedAdder maintains a table of Atomic long variables. The
47	* table is indexed by per-thread hash codes.
48	*
49	* By default, the table is lazily initialized, to minimize
50	* footprint until adders are used. On first use, the table is set
51	* to size DEFAULT_INITIAL_SIZE (currently 8). Table size is
52	* bounded by the number of CPUS (if larger than the default
53	* size).
54	*
55	* Per-thread hash codes are initialized to random values.
56	* Collisions are indicated by failed CASes when performing an add
57	* operation (see method retryAdd). Upon a collision, if the table
58	* size is less than the capacity, it is doubled in size unless
59	* some other thread holds lock. If a hashed slot is empty, and
60	* lock is available, a new Adder is created. Otherwise, if the
61	* slot exists, a CAS is tried. Retries proceed by "double
62	* hashing", using a secondary hash (Marsaglia XorShift) to try to
63	* find a free slot.
64	*
65	* The table size is capped because, when there are more threads
66	* than CPUs, supposing that each thread were bound to a CPU,
67	* there would exist a perfect hash function mapping threads to
68	* slots that eliminates collisions. When we reach capacity, we
69	* search for this mapping by randomly varying the hash codes of
70	* colliding threads. Because search is random, and failures only
71	* become known via CAS failures, convergence will be slow, and
72	* because threads are typically not bound to CPUS forever, may
73	* not occur at all. However, despite these limitations, observed
74	* contention is typically low in these cases.
75	*
76	* Table entries are of class Adder; a form of AtomicLong padded
77	* to reduce cache contention on most processors. Padding is
78	* overkill for most Atomics because they are usually irregularly
79	* scattered in memory and thus don't interfere much with each
80	* other. But Atomic objects residing in arrays will tend to be
81	* placed adjacent to each other, and so will most often share
82	* cache lines without this precaution. Adders are by default
83	* constructed upon first use, which further improves per-thread
84	* locality and helps reduce footprint.
85	*
86	* A single spinlock is used for resizing the table as well as
87	* populating slots with new Adders. Upon lock contention, threads
88	* try other slots rather than blocking. After initialization, at
89	* least one slot exists, so retries will eventually find a
90	* candidate Adder. During these retries, there is increased
91	* contention and reduced locality, which is still better than
92	* alternatives.
93	*/
94
95	/**
96	* Padded version of AtomicLong
97	*/
98	static final class Adder extends AtomicLong {
99	long p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, pa, pb, pc, pd, pe;
100	Adder(long x) { super(x); }
101	}
102
103	private static final int NCPU = Runtime.getRuntime().availableProcessors();
104
105	/**
106	* Table bounds. DEFAULT_INITIAL_SIZE is the table size set upon
107	* first use under default constructor, and must be a power of
108	* two. There is not much point in making size a lot smaller than
109	* that of Adders though. CAP is the maximum allowed table size.
110	*/
111	private static final int DEFAULT_INITIAL_SIZE = 8;
112	private static final int CAP = Math.max(NCPU, DEFAULT_INITIAL_SIZE);
113
114	/**
115	* Holder for the thread-local hash code. The code is initially
116	* random, but may be set to a different value upon collisions.
117	*/
118	static final class HashCode {
119	static final Random rng = new Random();
120	int code;
121	HashCode() {
122	int h = rng.nextInt();
123	code = (h == 0) ? 1 : h; // ensure nonzero
124	}
125	}
126
127	/**
128	* The corresponding ThreadLocal class
129	*/
130	static final class ThreadHashCode extends ThreadLocal<HashCode> {
131	public HashCode initialValue() { return new HashCode(); }
132	}
133
134	/**
135	* Static per-thread hash codes. Shared across all StripedAdders
136	* to reduce ThreadLocal pollution and because adjustments due to
137	* collisions in one table are likely to be appropriate for
138	* others.
139	*/
140	static final ThreadHashCode threadHashCode = new ThreadHashCode();
141
142	/**
143	* Common placeholder for empty arrays.
144	*/
145	static final Adder[] EMPTY_ARRAY = new Adder[0];
146
147	/**
148	* Table of adders. Size is either zero or a power of two, grows
149	* to be at most CAP.
150	*/
151	private transient volatile Adder[] adders;
152
153	/**
154	* Serves as a lock when resizing and/or creating Adders. There
155	* is no need for a blocking lock: Except during initialization
156	* races, when busy, other threads try other slots. However,
157	* during (double-checked) initializations, we use the
158	* "synchronized" lock on this object.
159	*/
160	private final AtomicInteger mutex;
161
162	/**
163	* Creates a new adder with zero sum.
164	*/
165	public StripedAdder() {
166	this.adders = EMPTY_ARRAY;
167	this.mutex = new AtomicInteger();
168	// remaining initialization on first call to add.
169	}
170
171	/**
172	* Creates a new adder with zero sum, and with stripes presized
173	* for the given expected contention level.
174	*
175	* @param expectedContention the expected number of threads that
176	* will concurrently update the sum.
177	*/
178	public StripedAdder(int expectedContention) {
179	if (expectedContention > 0) {
180	int cap = (expectedContention < CAP) ? expectedContention : CAP;
181	int size = 1;
182	while (size < cap)
183	size <<= 1;
184	Adder[] as = new Adder[size];
185	for (int i = 0; i < size; ++i)
186	as[i] = new Adder(0);
187	this.adders = as;
188	}
189	else
190	this.adders = EMPTY_ARRAY;
191	this.mutex = new AtomicInteger();
192	}
193
194	/**
195	* Adds the given value.
196	*
197	* @param x the value to add
198	*/
199	public void add(long x) {
200	Adder[] as; Adder a; int n; long v; // locals to hold volatile reads
201	HashCode hc = threadHashCode.get();
202	int h = hc.code;
203	if ((as = adders) == null \|\| (n = as.length) < 1 \|\|
204	(a = as[(n - 1) & h]) == null \|\|
205	!a.compareAndSet(v = a.get(), v + x))
206	retryAdd(x, hc);
207	}
208
209	/**
210	* Handle cases of add involving initialization, resizing,
211	* creating new Adders, and/or contention. See above for
212	* explanation.
213	*/
214	private void retryAdd(long x, HashCode hc) {
215	int h = hc.code;
216	final AtomicInteger mutex = this.mutex;
217	int collisions = 1 - mutex.get(); // first guess: collides if not locked
218	for (;;) {
219	Adder[] as; Adder a; long v; int k, n;
220	while ((as = adders) == null \|\| (n = as.length) < 1) {
221	synchronized(mutex) { // Try to initialize
222	if (adders == as) {
223	Adder[] rs = new Adder[DEFAULT_INITIAL_SIZE];
224	rs[h & (DEFAULT_INITIAL_SIZE - 1)] = new Adder(0);
225	adders = rs;
226	}
227	}
228	collisions = 0;
229	}
230
231	if ((a = as[k = (n - 1) & h]) == null) { // Try to add slot
232	if (mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
233	try {
234	if (adders == as && as[k] == null)
235	a = as[k] = new Adder(x);
236	} finally {
237	mutex.set(0);
238	}
239	if (a != null)
240	break;
241	}
242	collisions = 0;
243	}
244	else if (collisions != 0 && n < CAP && // Try to expand table
245	mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
246	try {
247	if (adders == as) {
248	Adder[] rs = new Adder[n << 1];
249	for (int i = 0; i < n; ++i)
250	rs[i] = as[i];
251	adders = rs;
252	}
253	} finally {
254	mutex.set(0);
255	}
256	collisions = 0;
257	}
258	else if (a.compareAndSet(v = a.get(), v + x))
259	break;
260	else
261	collisions = 1;
262	h ^= h << 13; // Rehash
263	h ^= h >>> 17;
264	h ^= h << 5;
265	}
266	hc.code = h;
267	}
268
269	/**
270	* Returns an estimate of the current sum. The result is
271	* calculated by summing multiple variables, so may not be
272	* accurate if updates occur concurrently with this method.
273	*
274	* @return the estimated sum
275	*/
276	public long sum() {
277	long sum = 0L;
278	Adder[] as = adders;
279	if (as != null) {
280	int n = as.length;
281	for (int i = 0; i < n; ++i) {
282	Adder a = as[i];
283	if (a != null)
284	sum += a.get();
285	}
286	}
287	return sum;
288	}
289
290	/**
291	* Resets each of the variables to zero. This is effective in
292	* fully resetting the sum only if there are no concurrent
293	* updates.
294	*/
295	public void reset() {
296	Adder[] as = adders;
297	if (as != null) {
298	int n = as.length;
299	for (int i = 0; i < n; ++i) {
300	Adder a = as[i];
301	if (a != null)
302	a.set(0L);
303	}
304	}
305	}
306
307	/**
308	* Equivalent to {@code add(1)}.
309	*/
310	public void increment() {
311	add(1L);
312	}
313
314	/**
315	* Equivalent to {@code add(-1)}.
316	*/
317	public void decrement() {
318	add(-1L);
319	}
320
321	/**
322	* Equivalent to {@link #sum} followed by {@link #reset}.
323	*
324	* @return the estimated sum
325	*/
326	public long sumAndReset() {
327	long sum = 0L;
328	Adder[] as = adders;
329	if (as != null) {
330	int n = as.length;
331	for (int i = 0; i < n; ++i) {
332	Adder a = as[i];
333	if (a != null) {
334	sum += a.get();
335	a.set(0L);
336	}
337	}
338	}
339	return sum;
340	}
341
342	private void writeObject(java.io.ObjectOutputStream s)
343	throws java.io.IOException {
344	s.defaultWriteObject();
345	s.writeLong(sum());
346	}
347
348	private void readObject(ObjectInputStream s)
349	throws IOException, ClassNotFoundException {
350	s.defaultReadObject();
351	mutex.set(0);
352	add(s.readLong());
353	}
354
355	}