How do I write a correct micro-benchmark in Java?

How do you write (and run) a correct micro-benchmark in Java?

I'm looking for some code samples and comments illustrating various things to think about.

Example: Should the benchmark measure time/iteration or iterations/time, and why?

Related: Is stopwatch benchmarking acceptable?

Solution 1:

Tips about writing micro benchmarks from the creators of Java HotSpot:

Rule 0: Read a reputable paper on JVMs and micro-benchmarking. A good one is Brian Goetz, 2005. Do not expect too much from micro-benchmarks; they measure only a limited range of JVM performance characteristics.

Rule 1: Always include a warmup phase which runs your test kernel all the way through, enough to trigger all initializations and compilations before timing phase(s). (Fewer iterations is OK on the warmup phase. The rule of thumb is several tens of thousands of inner loop iterations.)

Rule 2: Always run with -XX:+PrintCompilation, -verbose:gc, etc., so you can verify that the compiler and other parts of the JVM are not doing unexpected work during your timing phase.

Rule 2.1: Print messages at the beginning and end of timing and warmup phases, so you can verify that there is no output from Rule 2 during the timing phase.

Rule 3: Be aware of the difference between -client and -server, and OSR and regular compilations. The -XX:+PrintCompilation flag reports OSR compilations with an at-sign to denote the non-initial entry point, for example: Trouble$1::run @ 2 (41 bytes). Prefer server to client, and regular to OSR, if you are after best performance.

Rule 4: Be aware of initialization effects. Do not print for the first time during your timing phase, since printing loads and initializes classes. Do not load new classes outside of the warmup phase (or final reporting phase), unless you are testing class loading specifically (and in that case load only the test classes). Rule 2 is your first line of defense against such effects.

Rule 5: Be aware of deoptimization and recompilation effects. Do not take any code path for the first time in the timing phase, because the compiler may junk and recompile the code, based on an earlier optimistic assumption that the path was not going to be used at all. Rule 2 is your first line of defense against such effects.

Rule 6: Use appropriate tools to read the compiler's mind, and expect to be surprised by the code it produces. Inspect the code yourself before forming theories about what makes something faster or slower.

Rule 7: Reduce noise in your measurements. Run your benchmark on a quiet machine, and run it several times, discarding outliers. Use -Xbatch to serialize the compiler with the application, and consider setting -XX:CICompilerCount=1 to prevent the compiler from running in parallel with itself. Try your best to reduce GC overhead, set Xmx(large enough) equals Xms and use UseEpsilonGC if it is available.

Rule 8: Use a library for your benchmark as it is probably more efficient and was already debugged for this sole purpose. Such as JMH, Caliper or Bill and Paul's Excellent UCSD Benchmarks for Java.

Solution 2:

I know this question has been marked as answered but I wanted to mention two libraries that help us to write micro benchmarks

Caliper from Google

Getting started tutorials

1. http://codingjunkie.net/micro-benchmarking-with-caliper/
2. http://vertexlabs.co.uk/blog/caliper

JMH from OpenJDK

Getting started tutorials

1. Avoiding Benchmarking Pitfalls on the JVM
2. Using JMH for Java Microbenchmarking
3. Introduction to JMH

Solution 3:

Important things for Java benchmarks are:

• Warm up the JIT first by running the code several times before timing it
• Make sure you run it for long enough to be able to measure the results in seconds or (better) tens of seconds
• While you can't call System.gc() between iterations, it's a good idea to run it between tests, so that each test will hopefully get a "clean" memory space to work with. (Yes, gc() is more of a hint than a guarantee, but it's very likely that it really will garbage collect in my experience.)
• I like to display iterations and time, and a score of time/iteration which can be scaled such that the "best" algorithm gets a score of 1.0 and others are scored in a relative fashion. This means you can run all algorithms for a longish time, varying both number of iterations and time, but still getting comparable results.

I'm just in the process of blogging about the design of a benchmarking framework in .NET. I've got a couple of earlier posts which may be able to give you some ideas - not everything will be appropriate, of course, but some of it may be.

Solution 4:

jmh is a recent addition to OpenJDK and has been written by some performance engineers from Oracle. Certainly worth a look.

The jmh is a Java harness for building, running, and analysing nano/micro/macro benchmarks written in Java and other languages targetting the JVM.

Very interesting pieces of information buried in the sample tests comments.

See also:

• Avoiding Benchmarking Pitfalls on the JVM
• Discussion on the main strengths of jmh.