How much faster is Java 8?

Java SE 8 was released yesterday.
Traditionally, every new major JRE version comes with a free performance boost.
Do we get another free lunch? And how big is the gain this time?

Let’s benchmark it.

Benchmark methodology

  • Run the same code with 3 different JRE versions (SunJDK 1.6.0_26, OpenJDK 1.7.0_51 and OpenJDK 1.8.0).
    The code itself was written for Java 6 (both in syntax and JDK API’s usage) and compiled for Java 6 with OpenJDK 1.7.

  • Each run takes about 55 minutes.

  • VM arguments: -Xmx1536M -server
    Software: Linux 3.2.0-59-generic-pae
    Hardware: Intel® Xeon® CPU W3550 @ 3.07GHz

  • Each run solves 13 planning problems with OptaPlanner.
    Each planning problem runs for 5 minutes. It starts with a 30 second JVM warm up which is discarded.

  • Solving a planning problem involves no IO (except a few milliseconds during startup to load the input).
    A single CPU is completely saturated.
    It constantly creates many short lived objects, and the GC collects them afterwards.

  • The benchmarks measure the number of scores that can be calculated per millisecond. Higher is better.
    Calculating a score for a proposed planning solution is non-trivial:
    it involves many calculations, including checking for conflicts between every entity and every other entity.

  • To reproduce these benchmarks locally, build optaplanner from source
    and run the main class
    GeneralOptaPlannerBenchmarkApp.

Benchmark results

Executive summary

jdk6vs7vs8Summary

My observations:

  • On the biggest dataset (Machine Reassignment B10), which dwarfs any of the other datasets in size,
    Java 8 is 20% faster than Java 7, which was already 17% faster than Java 6.

  • In some cases, Java 8 is slower than Java 7.
    Specially for the course scheduling datasets, Java 8 is 6% slower than Java 7.
    Hopefully new releases of Java 8 will resolve this performance regression soon.

  • On average, Java 8 is only 1% faster than Java 7. This while Java 7 is already 16% faster than Java 6.

  • Despite that this is the first final release of OpenJDK 8, I did not find any regressions in Java 8.
    OptaPlanner’s examples are 100% reproducible, so as expected, the different JRE’s give the exact same results at every single iteration.

Raw benchmark numbers

Conclusion

On the big datasets, Java 8 is clearly faster. And this without changing a line of code.
On average, the result is less convincing (with the current release), but a free lunch is always welcome.

Update (18-JUN-2015): Java 8 build 0 versus build 45

I wrote this blog more than a year ago. Meanwhile both Java 8 and OptaPlanner have had a number of releases.
How much do the Java 8 updates affect performance?

To make a fair comparison, I ‘ve (re)ran the latest OptaPlanner code on both the original Java 8 release (build 0) and the latest release (build 45).
These are the results:

JDKCloud balancing 200cCloud balancing 800cMachine reassignment B1Machine reassignment B10Course scheduling c7Course scheduling c8Exam scheduling s2Exam scheduling s3Nurse rostering m1Nurse rostering mh1Sport scheduling nl14

SunJDK 1.6.0_26

46462

44963

94567

28655

5473

6989

6954

3785

3232

2948

1977

OpenJDK 1.7.0_51

53683

49798

116553

33733

6182

7848

8243

4606

3645

3377

2445

OpenJDK 1.8.0

54687

51625

135102

40529

5798

7357

8048

4441

3637

3324

2321

6 ⇒ 7

15.54%

10.75%

23.25%

17.72%

12.95%

12.29%

18.54%

21.69%

12.78%

14.55%

23.67%

7 ⇒ 8

1.87%

3.67%

15.91%

20.15%

-6.21%

-6.26%

-2.37%

-3.58%

-0.22%

-1.57%

-5.07%

Dataset scale

120k

1920k

500k

250000k

217k

145k

1705k

1613k

18k

12k

4k

On average, Java 8 build 45 is 2.07% faster than Java 8 build 0. That’s welcome!

JDKCloud balancing 200cCloud balancing 800cMachine reassignment B1Machine reassignment B10Course scheduling c7Course scheduling c8Exam scheduling s2Exam scheduling s3Nurse rostering m1Nurse rostering mh1Sport scheduling nl14

OpenJDK 1.8.0

63404

55295

126743

38260

6072

7825

10518

7176

3872

3558

1252

OpenJDK 1.8.0_45

64715

56472

131941

36175

6499

8084

10406

7217

3905

3595

1354

1.8.0 ⇒ 1.8.0_45

2.07%

2.13%

4.10%

-5.45%

7.03%

3.31%

-1.06%

0.57%

0.85%

1.04%

8.15%

Dataset scale

120k

1920k

500k

250000k

217k

145k

1705k

1613k

18k

12k

4k

This post was original published on here.