Why is "while (i++ < n) {}" significantly slower than "while (++i < n) {}"
Apparently on my Windows 8 laptop with HotSpot JDK 1.7.0_45 (with all compiler/VM options set to default), the below loop
final int n = Integer.MAX_VALUE;
int i = 0;
while (++i < n) {
}
is at least 2 orders of magnitude faster (~10 ms vs. ~5000 ms) than:
final int n = Integer.MAX_VALUE;
int i = 0;
while (i++ < n) {
}
I happened to notice this problem while writing a loop to evaluate another irrelevant performance issue. And the difference between ++i < n and i++ < n was huge enough to significantly influence the result.
If we look at the bytecode, the loop body of the faster version is:
iinc
iload
ldc
if_icmplt
And for the slower version:
iload
iinc
ldc
if_icmplt
So for ++i < n, it first increments local variable i by 1 and then push it onto the operand stack while i++ < n does those 2 steps in reverse order. But that doesn't seem to explain why the former is much faster. Is there any temp copy involved in the latter case? Or is it something beyond the bytecode (VM implementation, hardware, etc.) that should be responsible for the performance difference?
I've read some other discussion regarding ++i and i++ (not exhaustively though), but didn't find any answer that is Java-specific and directly related to the case where ++i or i++ is involved in a value comparison.
As others have pointed out, the test is flawed in many ways.
You did not tell us exactly how you did this test. However, I tried to implement a "naive" test (no offense) like this:
class PrePostIncrement
{
public static void main(String args[])
{
for (int j=0; j<3; j++)
{
for (int i=0; i<5; i++)
{
long before = System.nanoTime();
runPreIncrement();
long after = System.nanoTime();
System.out.println("pre : "+(after-before)/1e6);
}
for (int i=0; i<5; i++)
{
long before = System.nanoTime();
runPostIncrement();
long after = System.nanoTime();
System.out.println("post : "+(after-before)/1e6);
}
}
}
private static void runPreIncrement()
{
final int n = Integer.MAX_VALUE;
int i = 0;
while (++i < n) {}
}
private static void runPostIncrement()
{
final int n = Integer.MAX_VALUE;
int i = 0;
while (i++ < n) {}
}
}
When running this with default settings, there seems to be a small difference. But the real flaw of the benchmark becomes obvious when you run this with the -server flag. The results in my case then are along something like
...
pre : 6.96E-4
pre : 6.96E-4
pre : 0.001044
pre : 3.48E-4
pre : 3.48E-4
post : 1279.734543
post : 1295.989086
post : 1284.654267
post : 1282.349093
post : 1275.204583
Obviously, the pre-increment version has been completely optimized away. The reason is rather simple: The result is not used. It does not matter at all whether the loop is executed or not, so the JIT simply removes it.
This is confirmed by a look at the hotspot disassembly: The pre-increment version results in this code:
[Entry Point]
[Verified Entry Point]
[Constants]
# {method} {0x0000000055060500} 'runPreIncrement' '()V' in 'PrePostIncrement'
# [sp+0x20] (sp of caller)
0x000000000286fd80: sub $0x18,%rsp
0x000000000286fd87: mov %rbp,0x10(%rsp) ;*synchronization entry
; - PrePostIncrement::runPreIncrement@-1 (line 28)
0x000000000286fd8c: add $0x10,%rsp
0x000000000286fd90: pop %rbp
0x000000000286fd91: test %eax,-0x243fd97(%rip) # 0x0000000000430000
; {poll_return}
0x000000000286fd97: retq
0x000000000286fd98: hlt
0x000000000286fd99: hlt
0x000000000286fd9a: hlt
0x000000000286fd9b: hlt
0x000000000286fd9c: hlt
0x000000000286fd9d: hlt
0x000000000286fd9e: hlt
0x000000000286fd9f: hlt
The post-increment version results in this code:
[Entry Point]
[Verified Entry Point]
[Constants]
# {method} {0x00000000550605b8} 'runPostIncrement' '()V' in 'PrePostIncrement'
# [sp+0x20] (sp of caller)
0x000000000286d0c0: sub $0x18,%rsp
0x000000000286d0c7: mov %rbp,0x10(%rsp) ;*synchronization entry
; - PrePostIncrement::runPostIncrement@-1 (line 35)
0x000000000286d0cc: mov $0x1,%r11d
0x000000000286d0d2: jmp 0x000000000286d0e3
0x000000000286d0d4: nopl 0x0(%rax,%rax,1)
0x000000000286d0dc: data32 data32 xchg %ax,%ax
0x000000000286d0e0: inc %r11d ; OopMap{off=35}
;*goto
; - PrePostIncrement::runPostIncrement@11 (line 36)
0x000000000286d0e3: test %eax,-0x243d0e9(%rip) # 0x0000000000430000
;*goto
; - PrePostIncrement::runPostIncrement@11 (line 36)
; {poll}
0x000000000286d0e9: cmp $0x7fffffff,%r11d
0x000000000286d0f0: jl 0x000000000286d0e0 ;*if_icmpge
; - PrePostIncrement::runPostIncrement@8 (line 36)
0x000000000286d0f2: add $0x10,%rsp
0x000000000286d0f6: pop %rbp
0x000000000286d0f7: test %eax,-0x243d0fd(%rip) # 0x0000000000430000
; {poll_return}
0x000000000286d0fd: retq
0x000000000286d0fe: hlt
0x000000000286d0ff: hlt
It's not entirely clear for me why it seemingly does not remove the post-increment version. (In fact, I consider asking this as a separate question). But at least, this explains why you might see differences with an "order of magnitude"...
EDIT: Interestingly, when changing the upper limit of the loop from Integer.MAX_VALUE to Integer.MAX_VALUE-1, then both versions are optimized away and require "zero" time. Somehow this limit (which still appears as 0x7fffffff in the assembly) prevents the optimization. Presumably, this has something to do with the comparison being mapped to a (singed!) cmp instruction, but I can not give a profound reason beyond that. The JIT works in mysterious ways...
The difference between ++i and i++ is that ++i effectively increments the variable and 'returns' that new value. i++ on the other hand effectively creates a temp variable to hold the current value in i, then increments the variable 'returning' the temp variable's value. This is where the extra overhead is coming from.
// i++ evaluates to something like this
// Imagine though that somehow i was passed by reference
int temp = i;
i = i + 1;
return temp;
// ++i evaluates to
i = i + 1;
return i;
In your case it appears that the increment won't be optimized by the JVM because you are using the result in an expression. The JVM can on the other hand optimize a loop like this.
for( int i = 0; i < Integer.MAX_VALUE; i++ ) {}
This is because the result of i++ is never used. In a loop like this you should be able to use both ++i and i++ with the same performance as if you used ++i.
EDIT 2
You should really look here:
http://hg.openjdk.java.net/code-tools/jmh/file/f90aef7f1d2c/jmh-samples/src/main/java/org/openjdk/jmh/samples/JMHSample_11_Loops.java
EDIT The more I think about it, I realise that this test is somehow wrong, the loop will get seriously optimized by the JVM.
I think that you should just drop the @Param and let n=2.
This way you will test the performance of the while itself. The results I get in this case :
o.m.t.WhileTest.testFirst avgt 5 0.787 0.086 ns/op
o.m.t.WhileTest.testSecond avgt 5 0.782 0.087 ns/op
The is almost no difference
The very first question you should ask yourself is how you test and measure this. This is micro-benchmarking and in Java this is an art, and almost always a simple user (like me) will get the results wrong. You should rely on a benchmark test and very good tool for that. I used JMH to test this:
@Measurement(iterations=5, time=1, timeUnit=TimeUnit.MILLISECONDS)
@Fork(1)
@Warmup(iterations=5, time=1, timeUnit=TimeUnit.SECONDS)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
@BenchmarkMode(Mode.AverageTime)
@State(Scope.Benchmark)
public class WhileTest {
public static void main(String[] args) throws Exception {
Options opt = new OptionsBuilder()
.include(".*" + WhileTest.class.getSimpleName() + ".*")
.threads(1)
.build();
new Runner(opt).run();
}
@Param({"100", "10000", "100000", "1000000"})
private int n;
/*
@State(Scope.Benchmark)
public static class HOLDER_I {
int x;
}
*/
@Benchmark
public int testFirst(){
int i = 0;
while (++i < n) {
}
return i;
}
@Benchmark
public int testSecond(){
int i = 0;
while (i++ < n) {
}
return i;
}
}
Someone way more experienced in JMH might correct this results (I really hope so!, since I am not that versatile in JMH yet), but the results show that the difference is pretty darn small:
Benchmark (n) Mode Samples Score Score error Units
o.m.t.WhileTest.testFirst 100 avgt 5 1.271 0.096 ns/op
o.m.t.WhileTest.testFirst 10000 avgt 5 1.319 0.125 ns/op
o.m.t.WhileTest.testFirst 100000 avgt 5 1.327 0.241 ns/op
o.m.t.WhileTest.testFirst 1000000 avgt 5 1.311 0.136 ns/op
o.m.t.WhileTest.testSecond 100 avgt 5 1.450 0.525 ns/op
o.m.t.WhileTest.testSecond 10000 avgt 5 1.563 0.479 ns/op
o.m.t.WhileTest.testSecond 100000 avgt 5 1.418 0.428 ns/op
o.m.t.WhileTest.testSecond 1000000 avgt 5 1.344 0.120 ns/op
The Score field is the one you are interested in.