3. Program Order: Execution Order (maybe):
int w = 10; int x = 20;
int x = 20; int y = 30;
int y = 30; int b = x * y;
int z = 40;
int w = 10;
int a = w + z; int z = 40;
int b = x * y; int a = w + z;
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5. Why Should We Care About the
Details
?
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6. static long foo = 0;
private static void increment() {
for (long l = 0; l < 500000000L; l++) {
foo++;
}
}
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7. public static long foo = 0;
public static Lock lock = new Lock();
private static void increment() {
for (long l = 0; l < 500000000L; l++){
lock.lock();
try {
foo++;
} finally {
lock.unlock();
}
}
}
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8. static AtomicLong foo = new AtomicLong(0);
private static void increment() {
for (long l = 0; l < 500000000L; l++) {
foo.getAndIncrement();
}
}
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9. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
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10. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
• One Thread (volatile): 4 700 ms (15x)
Sunday, 13 November 11
11. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
• One Thread (volatile): 4 700 ms (15x)
• One Thread (Atomic) : 5 700 ms (19x)
Sunday, 13 November 11
12. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
• One Thread (volatile): 4 700 ms (15x)
• One Thread (Atomic) : 5 700 ms (19x)
• One Thread (Lock) : 10 000 ms (33x)
Sunday, 13 November 11
13. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
• One Thread (volatile): 4 700 ms (15x)
• One Thread (Atomic) : 5 700 ms (19x)
• One Thread (Lock) : 10 000 ms (33x)
• Two Threads (Atomic) : 30 000 ms (100x)
Sunday, 13 November 11
14. Cost of Contention
Increment a counter 500 000 000 times.
• One Thread : 300 ms
• One Thread (volatile): 4 700 ms (15x)
• One Thread (Atomic) : 5 700 ms (19x)
• One Thread (Lock) : 10 000 ms (33x)
• Two Threads (Atomic) : 30 000 ms (100x)
• Two Threads (Lock) : 224 000 ms (746x)
^^^^^^^^
~4 minutes!!!
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15. Parallel v. Serial - String Split
Guy Steele @ Strangle Loop:
http://www.infoq.com/presentations/Thinking-Parallel-
Programming
Scala Implementation and Brute Force version in Java:
https://github.com/mikeb01/folklore/
15
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16. Parallel (Scala) Serial (Java)
2000.0
1500.0
1000.0
500.0
0
String Split (ops/sec) higher is better
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27. How Fast Is It - Throughput
ABQ Disruptor
30000000.0
22500000.0
15000000.0
7500000.0
0
Unicast Diamond
27
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28. How Fast Is It - Latency
ABQ Disruptor
Min 145 29
Mean 32,757 52
99 Percentile 2,097,152 128
99.99 Percentile 4,194,304 8,192
Max 5,069,086 175,567
28
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30. Ordering and Visibility
private static final int SIZE = 32;
private final Object[] data = new Object[SIZE];
private volatile long sequence = -1;
private long nextValue = -1;
public void publish(Object value) {
long index = ++nextValue;
data[(int)(index % SIZE)] = value;
sequence = index;
}
public Object get(long index) {
if (index <= sequence) {
return data[(int)(index % SIZE)];
}
return null;
}
30
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31. Ordering and Visibility - Store
mov $0x1,%ecx
add 0x18(%rsi),%rcx ;*ladd
;...
lea (%r12,%r8,8),%r11 ;*getfield data
;...
mov %r12b,(%r11,%r10,1)
mov %rcx,0x10(%rsi)
lock addl $0x0,(%rsp) ;*ladd
31
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33. Look Ma’ No Memory Barrier
AtomicLong sequence = new AtomicLong(-1);
public void publish(Object value) {
long index = ++nextValue;
data[(int)(index % SIZE)] = value;
sequence.lazySet(index);
}
33
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35. Cache Line Padding
public class PaddedAtomicLong extends AtomicLong {
public volatile long p1, p2, p3, p4, p5, p6 = 7L;
//... lines omitted
public long sumPaddingToPreventOptimisation() {
return p1 + p2 + p3 + p4 + p5 + p6;
}
}
35
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36. Summary
• Concurrency is a tool
• Ordering and visibility are the key challenges
• For performance the details matter
• Don't believe everything you read
o Come up with your own theories and test them!
36
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37. Q&A
recruitment@lmax.com
Sunday, 13 November 11
