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 |
43 |
|
private static final long serialVersionUID = 7249069246863182397L; |
44 |
|
|
45 |
|
/* |
46 |
< |
* Overview: We maintain a table of Atomic long variables. The |
46 |
> |
* A StripedAdder maintains a table of Atomic long variables. The |
47 |
|
* table is indexed by per-thread hash codes that are initialized |
48 |
|
* to random values. |
49 |
|
* |
58 |
|
* and failures only become known via CAS failures, convergence |
59 |
|
* will be slow, and because threads are typically not bound to |
60 |
|
* CPUS forever, may not occur at all. However, despite these |
61 |
< |
* limitations, observed contention is typically very low in these |
61 |
> |
* limitations, observed contention is typically low in these |
62 |
|
* cases. |
63 |
|
* |
64 |
|
* Table entries are of class Adder; a form of AtomicLong padded |
67 |
|
* irregularly scattered in memory and thus don't interfere much |
68 |
|
* with each other. But Atomic objects residing in arrays will |
69 |
|
* tend to be placed adjacent to each other, and so will most |
70 |
< |
* often share cache lines without this precaution. Except for |
71 |
< |
* slot adders[0], Adders are constructed upon first use, which |
72 |
< |
* further improves per-thread locality and helps reduce (an |
73 |
< |
* already large) footprint. |
70 |
> |
* often share cache lines without this precaution. Adders are |
71 |
> |
* constructed upon first use, which further improves per-thread |
72 |
> |
* locality and helps reduce (an already large) footprint. |
73 |
|
* |
74 |
|
* A single spinlock is used for resizing the table as well as |
75 |
|
* populating slots with new Adders. Upon lock contention, threads |
76 |
< |
* try other slots rather than blocking. We guarantee that at |
77 |
< |
* least one slot (0) exists, so retries will eventually find a |
76 |
> |
* try other slots rather than blocking. After initialization, at |
77 |
> |
* least one slot exists, so retries will eventually find a |
78 |
|
* candidate Adder. During these retries, there is increased |
79 |
|
* contention and reduced locality, which is still better than |
80 |
|
* alternatives. |
86 |
|
static final int NCPU = Runtime.getRuntime().availableProcessors(); |
87 |
|
|
88 |
|
/** |
89 |
+ |
* The table size set upon first use when default-constructed |
90 |
+ |
*/ |
91 |
+ |
private static final int DEFAULT_ARRAY_SIZE = 8; |
92 |
+ |
|
93 |
+ |
/** |
94 |
|
* Padded version of AtomicLong |
95 |
|
*/ |
96 |
|
static final class Adder extends AtomicLong { |
100 |
|
|
101 |
|
/** |
102 |
|
* Holder for the thread-local hash code. The code starts off with |
103 |
< |
* a given random value, but may be set to a different |
104 |
< |
* pseudo-random value (using a cheaper but adequate xorshift |
101 |
< |
* generator) upon collisions. |
103 |
> |
* a given random value, but may be set to a different value upon |
104 |
> |
* collisions in retryAdd. |
105 |
|
*/ |
106 |
|
static final class HashCode { |
107 |
|
int code; |
127 |
|
static final ThreadHashCode threadHashCode = new ThreadHashCode(); |
128 |
|
|
129 |
|
/** |
130 |
< |
* Table of adders. Minimum size 2. Size grows to be at most NCPU. |
130 |
> |
* Table of adders. Size is power of two, grows to be at most NCPU. |
131 |
|
*/ |
132 |
|
private transient volatile Adder[] adders; |
133 |
|
|
134 |
|
/** |
135 |
|
* Serves as a lock when resizing and/or creating Adders. There |
136 |
< |
* is no need for a blocking lock: When busy, other threads try |
137 |
< |
* other slots. |
136 |
> |
* is no need for a blocking lock: Except during initialization |
137 |
> |
* races, when busy, other threads try other slots. |
138 |
|
*/ |
139 |
|
private final AtomicInteger mutex; |
140 |
|
|
141 |
|
/** |
139 |
– |
* Marsaglia XorShift random generator for rehashing on collisions |
140 |
– |
*/ |
141 |
– |
private static int xorShift(int r) { |
142 |
– |
r ^= r << 13; |
143 |
– |
r ^= r >>> 17; |
144 |
– |
return r ^ (r << 5); |
145 |
– |
} |
146 |
– |
|
147 |
– |
/** |
142 |
|
* Creates a new adder with zero sum. |
143 |
|
*/ |
144 |
|
public StripedAdder() { |
145 |
< |
this(2); |
145 |
> |
this.mutex = new AtomicInteger(); |
146 |
> |
// remaining initialization on first call to add. |
147 |
|
} |
148 |
|
|
149 |
|
/** |
154 |
|
* will concurrently update the sum. |
155 |
|
*/ |
156 |
|
public StripedAdder(int expectedContention) { |
157 |
< |
int cap = (expectedContention < NCPU) ? expectedContention : NCPU; |
158 |
< |
int size = 2; |
159 |
< |
while (size < cap) |
160 |
< |
size <<= 1; |
157 |
> |
int size; |
158 |
> |
if (expectedContention > 0) { |
159 |
> |
int cap = (expectedContention < NCPU) ? expectedContention : NCPU; |
160 |
> |
size = 1; |
161 |
> |
while (size < cap) |
162 |
> |
size <<= 1; |
163 |
> |
} |
164 |
> |
else |
165 |
> |
size = 0; |
166 |
|
Adder[] as = new Adder[size]; |
167 |
< |
as[0] = new Adder(0); // ensure at least one available adder |
167 |
> |
for (int i = 0; i < size; ++i) |
168 |
> |
as[i] = new Adder(0); |
169 |
|
this.adders = as; |
170 |
|
this.mutex = new AtomicInteger(); |
171 |
|
} |
176 |
|
* @param x the value to add |
177 |
|
*/ |
178 |
|
public void add(long x) { |
179 |
+ |
Adder[] as; Adder a; int n; long v; // locals to hold volatile reads |
180 |
|
HashCode hc = threadHashCode.get(); |
181 |
< |
for (int h = hc.code;;) { |
182 |
< |
Adder[] as = adders; |
183 |
< |
int n = as.length; |
184 |
< |
Adder a = as[h & (n - 1)]; |
185 |
< |
if (a != null) { |
186 |
< |
long v = a.get(); |
187 |
< |
if (a.compareAndSet(v, v + x)) |
188 |
< |
break; |
189 |
< |
if (n >= NCPU) { // Collision when table at max |
190 |
< |
h = hc.code = xorShift(h); // change code |
191 |
< |
continue; |
181 |
> |
if ((as = adders) == null || (n = as.length) < 1 || |
182 |
> |
(a = as[hc.code & (n - 1)]) == null || |
183 |
> |
!a.compareAndSet(v = a.get(), v + x)) |
184 |
> |
retryAdd(x, hc); |
185 |
> |
} |
186 |
> |
|
187 |
> |
/** |
188 |
> |
* Handle cases of add involving initialization, resizing, |
189 |
> |
* creating new Adders, and/or contention. |
190 |
> |
*/ |
191 |
> |
private void retryAdd(long x, HashCode hc) { |
192 |
> |
int h = hc.code; |
193 |
> |
final AtomicInteger mutex = this.mutex; |
194 |
> |
for (boolean retried = false; ; retried = true) { |
195 |
> |
Adder[] as; Adder a; long v; int n, k; // Locals for volatiles |
196 |
> |
if ((as = adders) == null || (n = as.length) < 1) { |
197 |
> |
if (mutex.get() == 0 && mutex.compareAndSet(0, 1)) { |
198 |
> |
try { |
199 |
> |
if (adders == null) // Default-initialize |
200 |
> |
adders = new Adder[DEFAULT_ARRAY_SIZE]; |
201 |
> |
} finally { |
202 |
> |
mutex.set(0); |
203 |
> |
} |
204 |
|
} |
205 |
+ |
else |
206 |
+ |
Thread.yield(); // initialization race |
207 |
|
} |
208 |
< |
final AtomicInteger mutex = this.mutex; |
209 |
< |
if (mutex.get() != 0) |
210 |
< |
h = xorShift(h); // Try elsewhere |
211 |
< |
else if (mutex.compareAndSet(0, 1)) { |
208 |
> |
else if ((a = as[k = h & (n - 1)]) != null && |
209 |
> |
retried && a.compareAndSet(v = a.get(), v + x)) |
210 |
> |
break; |
211 |
> |
else if ((a == null || n < NCPU) && |
212 |
> |
mutex.get() == 0 && mutex.compareAndSet(0, 1)) { |
213 |
|
boolean created = false; |
214 |
|
try { |
215 |
< |
Adder[] rs = adders; |
216 |
< |
if (a != null && rs == as) // Resize table |
217 |
< |
rs = adders = Arrays.copyOf(as, as.length << 1); |
218 |
< |
int j = h & (rs.length - 1); |
219 |
< |
if (rs[j] == null) { // Create adder |
220 |
< |
rs[j] = new Adder(x); |
221 |
< |
created = true; |
215 |
> |
if (adders == as) { |
216 |
> |
if (as[k] == null) { |
217 |
> |
as[k] = new Adder(x); |
218 |
> |
created = true; |
219 |
> |
} |
220 |
> |
else { // Expand table |
221 |
> |
Adder[] rs = new Adder[n << 1]; |
222 |
> |
for (int i = 0; i < n; ++i) |
223 |
> |
rs[i] = as[i]; |
224 |
> |
adders = rs; |
225 |
> |
} |
226 |
|
} |
227 |
|
} finally { |
228 |
|
mutex.set(0); |
229 |
|
} |
230 |
< |
if (created) { |
210 |
< |
hc.code = h; // Use this adder next time |
230 |
> |
if (created) |
231 |
|
break; |
232 |
< |
} |
232 |
> |
} |
233 |
> |
else { // Try elsewhere |
234 |
> |
h ^= h << 13; |
235 |
> |
h ^= h >>> 17; // Marsaglia XorShift |
236 |
> |
h ^= h << 5; |
237 |
|
} |
238 |
|
} |
239 |
+ |
hc.code = h; |
240 |
|
} |
241 |
|
|
242 |
|
/** |
247 |
|
* @return the estimated sum |
248 |
|
*/ |
249 |
|
public long sum() { |
250 |
< |
long sum = 0; |
250 |
> |
long sum = 0L; |
251 |
|
Adder[] as = adders; |
252 |
< |
int n = as.length; |
253 |
< |
for (int i = 0; i < n; ++i) { |
254 |
< |
Adder a = as[i]; |
255 |
< |
if (a != null) |
256 |
< |
sum += a.get(); |
252 |
> |
if (as != null) { |
253 |
> |
int n = as.length; |
254 |
> |
for (int i = 0; i < n; ++i) { |
255 |
> |
Adder a = as[i]; |
256 |
> |
if (a != null) |
257 |
> |
sum += a.get(); |
258 |
> |
} |
259 |
|
} |
260 |
|
return sum; |
261 |
|
} |
267 |
|
*/ |
268 |
|
public void reset() { |
269 |
|
Adder[] as = adders; |
270 |
< |
int n = as.length; |
271 |
< |
for (int i = 0; i < n; ++i) { |
272 |
< |
Adder a = as[i]; |
273 |
< |
if (a != null) |
274 |
< |
a.set(0L); |
270 |
> |
if (as != null) { |
271 |
> |
int n = as.length; |
272 |
> |
for (int i = 0; i < n; ++i) { |
273 |
> |
Adder a = as[i]; |
274 |
> |
if (a != null) |
275 |
> |
a.set(0L); |
276 |
> |
} |
277 |
|
} |
278 |
|
} |
279 |
|
|
297 |
|
* @return the estimated sum |
298 |
|
*/ |
299 |
|
public long sumAndReset() { |
300 |
< |
long sum = 0; |
300 |
> |
long sum = 0L; |
301 |
|
Adder[] as = adders; |
302 |
< |
int n = as.length; |
303 |
< |
for (int i = 0; i < n; ++i) { |
304 |
< |
Adder a = as[i]; |
305 |
< |
if (a != null) { |
306 |
< |
sum += a.get(); |
307 |
< |
a.set(0L); |
302 |
> |
if (as != null) { |
303 |
> |
int n = as.length; |
304 |
> |
for (int i = 0; i < n; ++i) { |
305 |
> |
Adder a = as[i]; |
306 |
> |
if (a != null) { |
307 |
> |
sum += a.get(); |
308 |
> |
a.set(0L); |
309 |
> |
} |
310 |
|
} |
311 |
|
} |
312 |
|
return sum; |
321 |
|
private void readObject(ObjectInputStream s) |
322 |
|
throws IOException, ClassNotFoundException { |
323 |
|
s.defaultReadObject(); |
293 |
– |
long c = s.readLong(); |
294 |
– |
Adder[] as = new Adder[2]; |
295 |
– |
as[0] = new Adder(c); |
296 |
– |
this.adders = as; |
324 |
|
mutex.set(0); |
325 |
+ |
add(s.readLong()); |
326 |
|
} |
327 |
|
|
328 |
|
} |
301 |
– |
|
302 |
– |
|