In JEP193, one of the specific goals of VarHandles
is to provide an alternative to of using FieldUpdaters
and AtomicIntegers
(and avoid some of the overhead associated with them).
AtomicIntegers
can be particularly wasteful in terms of memory since they're a separate object (they use around 36 bytes each, depending on a few factors such as wether compressed OOPs are enabled or not, etc.).
If you have many integers that may need to be updated atomically (in many small objects), there are essentially three options if you want to reduce the waste:
- Use an
AtomicFieldUpdater
- Use a
VarHandle
- Or re-arrange the code to use
AtomicIntegerArray
instead of fields in objects.
So I decided to test the alternatives and get an idea of the performance implications of each.
Using an atomic (volatile mode) increment of an integer field as a proxy, I'm getting the following results on a Mid 2014 MacBook Pro:
Benchmark Mode Cnt Score Error Units
VarHandleBenchmark.atomic thrpt 5 448041037.223 ± 36448840.301 ops/s
VarHandleBenchmark.atomicArray thrpt 5 453785339.203 ± 64528885.282 ops/s
VarHandleBenchmark.fieldUpdater thrpt 5 459802512.169 ± 52293792.737 ops/s
VarHandleBenchmark.varhandle thrpt 5 136482396.440 ± 9439041.030 ops/s
In this benchmark, the VarHandles
are roughly four times slower.
What I'm trying to understand is where the overhead comes from?
Is this due to the signature-polymorphic access methods? Am I making a mistake in the micro benchmark?
Benchmark details follow.
I ran the benchmark with the following JVM on a Mid 2014 MacBook Pro
> java -version
openjdk version "11.0.2" 2019-01-15
OpenJDK Runtime Environment AdoptOpenJDK (build 11.0.2+9)
OpenJDK 64-Bit Server VM AdoptOpenJDK (build 11.0.2+9, mixed mode)
Source code of the benchmark:
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.Scope;
import org.openjdk.jmh.annotations.State;
import org.openjdk.jmh.annotations.Threads;
import org.openjdk.jmh.annotations.Warmup;
import org.openjdk.jmh.infra.Blackhole;
import java.lang.invoke.MethodHandles;
import java.lang.invoke.VarHandle;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicIntegerArray;
import java.util.concurrent.atomic.AtomicIntegerFieldUpdater;
@State(Scope.Thread)
@Fork(value = 1, jvmArgs = {"-Xms256m", "-Xmx256m", "-XX:+UseG1GC"})
@Warmup(iterations = 3, time = 3)
@Measurement(iterations = 5, time = 5)
@Threads(4)
public class VarHandleBenchmark {
// array option
private final AtomicIntegerArray array = new AtomicIntegerArray(1);
// vanilla AtomicInteger
private final AtomicInteger counter = new AtomicInteger();
// count field and its VarHandle
private volatile int count;
private static final VarHandle COUNT;
// count2 field and its field updater
private volatile int count2;
private static final AtomicIntegerFieldUpdater<VarHandleBenchmark> COUNT2 ;
static {
try {
COUNT = MethodHandles.lookup()
.findVarHandle(VarHandleBenchmark.class, "count", Integer.TYPE);
COUNT2 = AtomicIntegerFieldUpdater.newUpdater(VarHandleBenchmark.class, "count2");
} catch (ReflectiveOperationException e) {
throw new AssertionError(e);
}
}
@Benchmark
public void atomic(Blackhole bh) {
bh.consume(counter.getAndAdd(1));
}
@Benchmark
public void atomicArray(Blackhole bh) {
bh.consume(array.getAndAdd(0, 1));
}
@Benchmark
public void varhandle(Blackhole bh) {
bh.consume(COUNT.getAndAdd(this, 1));
}
@Benchmark
public void fieldUpdater(Blackhole bh) {
bh.consume(COUNT2.getAndAdd(this, 1));
}
}
UPDATE: after applying apangin's solution, these are the results of the benchmark:
Benchmark Mode Cnt Score Error Units
VarHandleBenchmark.atomic thrpt 5 464045527.470 ± 42337922.645 ops/s
VarHandleBenchmark.atomicArray thrpt 5 465700610.882 ± 18116770.557 ops/s
VarHandleBenchmark.fieldUpdater thrpt 5 473968453.591 ± 49859839.498 ops/s
VarHandleBenchmark.varhandle thrpt 5 429737922.796 ± 41629104.677 ops/s
The difference disappears.