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root/jsr166/jsr166/src/jsr166e/StripedAdder.java
Revision: 1.6
Committed: Tue Jul 26 17:16:36 2011 UTC (12 years, 10 months ago) by dl
Branch: MAIN
Changes since 1.5: +102 -86 lines
Log Message:
Performance improvements

File Contents

# 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 * 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: 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 * Creates a new adder with zero sum.
158 */
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 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(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 }
182
183 /**
184 * Adds the given value.
185 *
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 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 else if (collisions != 0 && n < CAP && // Try to expand table
234 mutex.get() == 0 && mutex.compareAndSet(0, 1)) {
235 try {
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 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 /**
259 * Returns an estimate of the current sum. The result is
260 * calculated by summing multiple variables, so may not be
261 * accurate if updates occur concurrently with this method.
262 *
263 * @return the estimated sum
264 */
265 public long sum() {
266 long sum = 0L;
267 Adder[] as = adders;
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 }
278
279 /**
280 * Resets each of the variables to zero. This is effective in
281 * fully resetting the sum only if there are no concurrent
282 * updates.
283 */
284 public void reset() {
285 Adder[] as = adders;
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
296 /**
297 * Equivalent to {@code add(1)}.
298 */
299 public void increment() {
300 add(1L);
301 }
302
303 /**
304 * Equivalent to {@code add(-1)}.
305 */
306 public void decrement() {
307 add(-1L);
308 }
309
310 /**
311 * Equivalent to {@link #sum} followed by {@link #reset}.
312 *
313 * @return the estimated sum
314 */
315 public long sumAndReset() {
316 long sum = 0L;
317 Adder[] as = adders;
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;
329 }
330
331 private void writeObject(java.io.ObjectOutputStream s)
332 throws java.io.IOException {
333 s.defaultWriteObject();
334 s.writeLong(sum());
335 }
336
337 private void readObject(ObjectInputStream s)
338 throws IOException, ClassNotFoundException {
339 s.defaultReadObject();
340 mutex.set(0);
341 add(s.readLong());
342 }
343
344 }