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Comparing jsr166/src/jsr166e/StripedAdder.java (file contents):
Revision 1.2 by jsr166, Wed Jul 20 16:06:19 2011 UTC vs.
Revision 1.6 by dl, Tue Jul 26 17:16:36 2011 UTC

# Line 16 | Line 16 | 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, the set of
20 < * adders may grow to reduce contention. Method {@link #sum} returns
21 < * the current combined total across these adders. This value is
22 < * <em>NOT</em> an atomic snapshot (concurrent updates may occur while
23 < * the sum is being calculated), and so cannot be used alone for
24 < * fine-grained synchronization control.
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 < * significantly more space.  On the other hand, if it is known that
31 < * only one thread can ever update the sum, performance may be
32 < * significantly slower than just updating a local variable.
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   */
# Line 37 | Line 43 | public class StripedAdder implements Ser
43      private static final long serialVersionUID = 7249069246863182397L;
44  
45      /*
46 <     * Overview: We maintain a table of AtomicLongs (padded to reduce
47 <     * false sharing). The table is indexed by per-thread hash codes
48 <     * that are initialized as random values.  The table doubles in
49 <     * size upon contention (as indicated by failed CASes when
50 <     * performing add()), but is capped at the nearest power of two >=
51 <     * #cpus: At that point, contention should be infrequent if each
52 <     * thread has a unique index; so we instead adjust hash codes to
53 <     * new random values upon contention rather than expanding. A
54 <     * single spinlock is used for resizing the table as well as
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 <     * just try other slots rather than blocking. We guarantee that at
88 >     * try other slots rather than blocking. After initialization, at
89       * least one slot exists, so retries will eventually find a
90 <     * candidate Adder.
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 <     * Number of processors, to place a cap on table growth.
57 <     */
58 <    static final int NCPU = Runtime.getRuntime().availableProcessors();
59 <
60 <    /**
61 <     * Version of AtomicLong padded to avoid sharing cache
62 <     * lines on most processors
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;
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 <     * Holder for the thread-local hash code.
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(int h) { code = h; }
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 <        static final Random rng = new Random();
82 <        public HashCode initialValue() {
83 <            int h = rng.nextInt();
84 <            return new HashCode((h == 0) ? 1 : h); // ensure nonzero
85 <        }
131 >        public HashCode initialValue() { return new HashCode(); }
132      }
133  
134      /**
135       * Static per-thread hash codes. Shared across all StripedAdders
136 <     * because adjustments due to collisions in one table are likely
137 <     * to be appropriate for others.
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 <     * Table of adders. Initially of size 2; grows to be at most NCPU.
143 >     * Table of adders. Size is power of two, grows to be at most CAP.
144       */
145      private transient volatile Adder[] adders;
146  
147      /**
148       * Serves as a lock when resizing and/or creating Adders.  There
149 <     * is no need for a blocking lock: When busy, other threads try
150 <     * other slots.
149 >     * is no need for a blocking lock: Except during initialization
150 >     * races, when busy, other threads try other slots. However,
151 >     * during (double-checked) initializations, we use the
152 >     * "synchronized" lock on this object.
153       */
154      private final AtomicInteger mutex;
155  
156      /**
157 <     * Marsaglia XorShift for rehashing on collisions
157 >     * Creates a new adder with zero sum.
158       */
159 <    private static int xorShift(int r) {
160 <        r ^= r << 13;
161 <        r ^= r >>> 17;
113 <        return r ^ (r << 5);
159 >    public StripedAdder() {
160 >        this.mutex = new AtomicInteger();
161 >        // remaining initialization on first call to add.
162      }
163  
164      /**
165 <     * Creates a new adder with initially zero sum.
165 >     * Creates a new adder with zero sum, and with stripes presized
166 >     * for the given expected contention level.
167 >     *
168 >     * @param expectedContention the expected number of threads that
169 >     * will concurrently update the sum.
170       */
171 <    public StripedAdder() {
172 <        Adder[] as = new Adder[2];
173 <        as[0] = new Adder(0); // ensure at least one available adder
171 >    public StripedAdder(int expectedContention) {
172 >        int cap = (expectedContention < CAP) ? expectedContention : CAP;
173 >        int size = 1;
174 >        while (size < cap)
175 >            size <<= 1;
176 >        Adder[] as = new Adder[size];
177 >        for (int i = 0; i < size; ++i)
178 >            as[i] = new Adder(0);
179          this.adders = as;
180          this.mutex = new AtomicInteger();
181      }
# Line 129 | Line 186 | public class StripedAdder implements Ser
186       * @param x the value to add
187       */
188      public void add(long x) {
189 +        Adder[] as; Adder a; int n; long v; // locals to hold volatile reads
190          HashCode hc = threadHashCode.get();
191 <        for (int h = hc.code;;) {
192 <            Adder[] as = adders;
193 <            int n = as.length;
194 <            Adder a = as[h & (n - 1)];
195 <            if (a != null) {
196 <                long v = a.get();
197 <                if (a.compareAndSet(v, v + x))
198 <                    break;
199 <                if (n >= NCPU) {                 // Collision when table at max
200 <                    h = hc.code = xorShift(h);   // change code
201 <                    continue;
191 >        int h = hc.code;
192 >        if ((as = adders) == null || (n = as.length) < 1 ||
193 >            (a = as[(n - 1) & h]) == null ||
194 >            !a.compareAndSet(v = a.get(), v + x))
195 >            retryAdd(x, hc);
196 >    }
197 >
198 >    /**
199 >     * Handle cases of add involving initialization, resizing,
200 >     * creating new Adders, and/or contention. See above for
201 >     * explanation.
202 >     */
203 >    private void retryAdd(long x, HashCode hc) {
204 >        int h = hc.code;
205 >        final AtomicInteger mutex = this.mutex;
206 >        int collisions = 1 - mutex.get(); // first guess: collides if not locked
207 >        for (;;) {
208 >            Adder[] as; Adder a; long v; int k, n;
209 >            while ((as = adders) == null || (n = as.length) < 1) {
210 >                synchronized(mutex) {                // Try to initialize
211 >                    if (adders == null) {
212 >                        Adder[] rs = new Adder[DEFAULT_INITIAL_SIZE];
213 >                        rs[h & (DEFAULT_INITIAL_SIZE - 1)] = new Adder(0);
214 >                        adders = rs;
215 >                    }
216 >                }
217 >                collisions = 0;
218 >            }
219 >
220 >            if ((a = as[k = (n - 1) & h]) == null) { // Try to add slot
221 >                if (mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
222 >                    try {
223 >                        if (adders == as && as[k] == null)
224 >                            a = as[k] = new Adder(x);
225 >                    } finally {
226 >                        mutex.set(0);
227 >                    }
228 >                    if (a != null)
229 >                        break;
230                  }
231 +                collisions = 0;
232              }
233 <            final AtomicInteger mutex = this.mutex;
234 <            if (mutex.get() != 0)
148 <                h = xorShift(h);                 // Try elsewhere
149 <            else if (mutex.compareAndSet(0, 1)) {
150 <                boolean created = false;
233 >            else if (collisions != 0 && n < CAP &&   // Try to expand table
234 >                     mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
235                  try {
236 <                    Adder[] rs = adders;
237 <                    if (a != null && rs == as)   // Resize table
238 <                        rs = adders = Arrays.copyOf(as, as.length << 1);
239 <                    int j = h & (rs.length - 1);
240 <                    if (rs[j] == null) {         // Create adder
157 <                        rs[j] = new Adder(x);
158 <                        created = true;
236 >                    if (adders == as) {
237 >                        Adder[] rs = new Adder[n << 1];
238 >                        for (int i = 0; i < n; ++i)
239 >                            rs[i] = as[i];
240 >                        adders = rs;
241                      }
242                  } finally {
243                      mutex.set(0);
244                  }
245 <                if (created) {
164 <                    hc.code = h;                // Use this adder next time
165 <                    break;
166 <                }
245 >                collisions = 0;
246              }
247 +            else if (a.compareAndSet(v = a.get(), v + x))
248 +                break;
249 +            else
250 +                collisions = 1;
251 +            h ^= h << 13;                            // Rehash
252 +            h ^= h >>> 17;
253 +            h ^= h << 5;
254          }
255 +        hc.code = h;
256      }
257  
258      /**
# Line 176 | Line 263 | public class StripedAdder implements Ser
263       * @return the estimated sum
264       */
265      public long sum() {
266 <        long sum = 0;
266 >        long sum = 0L;
267          Adder[] as = adders;
268 <        int n = as.length;
269 <        for (int i = 0; i < n; ++i) {
270 <            Adder a = as[i];
271 <            if (a != null)
272 <                sum += a.get();
268 >        if (as != null) {
269 >            int n = as.length;
270 >            for (int i = 0; i < n; ++i) {
271 >                Adder a = as[i];
272 >                if (a != null)
273 >                    sum += a.get();
274 >            }
275          }
276          return sum;
277      }
# Line 194 | Line 283 | public class StripedAdder implements Ser
283       */
284      public void reset() {
285          Adder[] as = adders;
286 <        int n = as.length;
287 <        for (int i = 0; i < n; ++i) {
288 <            Adder a = as[i];
289 <            if (a != null)
290 <                a.set(0L);
286 >        if (as != null) {
287 >            int n = as.length;
288 >            for (int i = 0; i < n; ++i) {
289 >                Adder a = as[i];
290 >                if (a != null)
291 >                    a.set(0L);
292 >            }
293          }
294      }
295  
# Line 222 | Line 313 | public class StripedAdder implements Ser
313       * @return the estimated sum
314       */
315      public long sumAndReset() {
316 <        long sum = 0;
316 >        long sum = 0L;
317          Adder[] as = adders;
318 <        int n = as.length;
319 <        for (int i = 0; i < n; ++i) {
320 <            Adder a = as[i];
321 <            if (a != null) {
322 <                sum += a.get();
323 <                a.set(0L);
318 >        if (as != null) {
319 >            int n = as.length;
320 >            for (int i = 0; i < n; ++i) {
321 >                Adder a = as[i];
322 >                if (a != null) {
323 >                    sum += a.get();
324 >                    a.set(0L);
325 >                }
326              }
327          }
328          return sum;
# Line 244 | Line 337 | public class StripedAdder implements Ser
337      private void readObject(ObjectInputStream s)
338          throws IOException, ClassNotFoundException {
339          s.defaultReadObject();
247        long c = s.readLong();
248        Adder[] as = new Adder[2];
249        as[0] = new Adder(c);
250        this.adders = as;
340          mutex.set(0);
341 +        add(s.readLong());
342      }
343  
344   }
255
256

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