| 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 |
|
*/ |
| 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 that are initialized |
| 48 |
> |
* to random values. |
| 49 |
> |
* |
| 50 |
> |
* The table doubles in size upon contention (as indicated by |
| 51 |
> |
* failed CASes when performing add()), but is capped at the |
| 52 |
> |
* nearest power of two >= #CPUS. This reflects the idea that, |
| 53 |
> |
* when there are more threads than CPUs, then if each thread were |
| 54 |
> |
* bound to a CPU, there would exist a perfect hash function |
| 55 |
> |
* mapping threads to slots that eliminates collisions. When we |
| 56 |
> |
* reach capacity, we search for this mapping by randomly varying |
| 57 |
> |
* the hash codes of colliding threads. Because search is random, |
| 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 low in these |
| 62 |
> |
* cases. |
| 63 |
> |
* |
| 64 |
> |
* Table entries are of class Adder; a form of AtomicLong padded |
| 65 |
> |
* to reduce cache contention on most processors. Padding is |
| 66 |
> |
* overkill for most Atomics because they are most often |
| 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. 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 |
< |
* just try other slots rather than blocking. We guarantee that at |
| 76 |
> |
* try other slots rather than blocking. After initialization, at |
| 77 |
|
* least one slot exists, so retries will eventually find a |
| 78 |
< |
* candidate Adder. |
| 78 |
> |
* candidate Adder. During these retries, there is increased |
| 79 |
> |
* contention and reduced locality, which is still better than |
| 80 |
> |
* alternatives. |
| 81 |
|
*/ |
| 82 |
|
|
| 83 |
|
/** |
| 86 |
|
static final int NCPU = Runtime.getRuntime().availableProcessors(); |
| 87 |
|
|
| 88 |
|
/** |
| 89 |
< |
* Version of AtomicLong padded to avoid sharing cache |
| 90 |
< |
* lines on most processors |
| 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 { |
| 97 |
|
long p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, pa, pb, pc, pd; |
| 99 |
|
} |
| 100 |
|
|
| 101 |
|
/** |
| 102 |
< |
* Holder for the thread-local hash code. |
| 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 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. Initially of size 2; 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 |
|
/** |
| 142 |
< |
* Marsaglia XorShift for rehashing on collisions |
| 142 |
> |
* Creates a new adder with zero sum. |
| 143 |
|
*/ |
| 144 |
< |
private static int xorShift(int r) { |
| 145 |
< |
r ^= r << 13; |
| 146 |
< |
r ^= r >>> 17; |
| 113 |
< |
return r ^ (r << 5); |
| 144 |
> |
public StripedAdder() { |
| 145 |
> |
this.mutex = new AtomicInteger(); |
| 146 |
> |
// remaining initialization on first call to add. |
| 147 |
|
} |
| 148 |
|
|
| 149 |
|
/** |
| 150 |
< |
* Creates a new adder with initially zero sum. |
| 150 |
> |
* Creates a new adder with zero sum, and with stripes presized |
| 151 |
> |
* for the given expected contention level. |
| 152 |
> |
* |
| 153 |
> |
* @param expectedContention the expected number of threads that |
| 154 |
> |
* will concurrently update the sum. |
| 155 |
|
*/ |
| 156 |
< |
public StripedAdder() { |
| 157 |
< |
Adder[] as = new Adder[2]; |
| 158 |
< |
as[0] = new Adder(0); // ensure at least one available adder |
| 156 |
> |
public StripedAdder(int expectedContention) { |
| 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 |
> |
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) { |
| 164 |
< |
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(); |
| 247 |
– |
long c = s.readLong(); |
| 248 |
– |
Adder[] as = new Adder[2]; |
| 249 |
– |
as[0] = new Adder(c); |
| 250 |
– |
this.adders = as; |
| 324 |
|
mutex.set(0); |
| 325 |
+ |
add(s.readLong()); |
| 326 |
|
} |
| 327 |
|
|
| 328 |
|
} |
| 255 |
– |
|
| 256 |
– |
|
