anchor.diff:  |Average 11+^.^|*4.5%*
   |===
   
  -With Parallel Garbage Collector, the results are less definite as with G1. There is an improvement for some data sets,
  +With the Parallel Garbage Collector, the results are less definite than G1. There is an improvement for some data sets,
   while others remain intact or show even a performance drop. However, on average, the Java 11 performs over 4% better.
   
   === Parallel GC vs. G1 GC on Java 11
  
positive.code:   OpenJDK Runtime Environment 18.9 (build 11.0.1+13)
    OpenJDK 64-Bit Server VM 18.9 (build 11.0.1+13, mixed mode)
  
  * The benchmark uses OptaPlanner version 7.14.0.Final.
  
  * 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.
  
negative.code: :awestruct-layout: blogPostBase
  :awestruct-tags: [production, benchmark]
  
  Java 11 was released some time ago, although the https://www.baeldung.com/java-in-2018[majority of developers stay on Java 8].
  Let's see which one of them is faster for https://www.optaplanner.org/[OptaPlanner]. The best way to find out is
  of course running OptaPlanner benchmarks.
  This article is a follow up on https://www.optaplanner.org/blog/2014/03/20/HowMuchFasterIsJava8.html[our similar article for Java 8].
  
  == Benchmark methodology
  
  To run the benchmark we used:
  
  * A stable machine without any other computational demanding processes running and with
  `2 x Intel® Xeon® CPU E5-2609 0 @ 2.4 GHz (8 cores total)` and `31.3 GiB` RAM memory, running RHEL 6.
  
  * Both G1 and Parallel GC for both Java versions to compare the impact of garbage collection.
  Java executed with the parameters `-Xmx1536M -server -XX:+UseG1GC` and `-Xmx1536M -server -XX:+UseParallelGC` respectively.
  
  * Both Oracle Java 8:
  
    java version "1.8.0_191"
    Java(TM) SE Runtime Environment (build 1.8.0_191-b12)
  