/* * 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 NOT an atomic snapshot (concurrent * updates may occur while the sum is being calculated), and so cannot * be used alone for fine-grained synchronization control. * *

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. * *

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 { 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()); } }