I was benchmarking some code, and I could not get it to run as fast as with java.math.BigInteger , even when using the exact same algorithm. So I copied java.math.BigInteger source into my own package and tried this:

//import java.math.BigInteger; public class MultiplyTest { public static void main(String[] args) { Random r = new Random(1); long tm = 0, count = 0,result=0; for (int i = 0; i < 400000; i++) { int s1 = 400, s2 = 400; BigInteger a = new BigInteger(s1 * 8, r), b = new BigInteger(s2 * 8, r); long tm1 = System.nanoTime(); BigInteger c = a.multiply(b); if (i > 100000) { tm += System.nanoTime() - tm1; count++; } result+=c.bitLength(); } System.out.println((tm / count) + "nsec/mul"); System.out.println(result); } }

When I run this (jdk 1.8.0_144-b01 on MacOS) it outputs:

12089nsec/mul 2559044166

When I run it with the import line uncommented:

4098nsec/mul 2559044166

It's almost three times as fast when using the JDK version of BigInteger versus my version, even if it's using the exact same code.

I've examined the bytecode with javap, and compared compiler output when running with options:

-Xbatch -XX:-TieredCompilation -XX:+PrintCompilation -XX:+UnlockDiagnosticVMOptions -XX:+PrintInlining -XX:CICompilerCount=1

and both versions seem to generate the same code. So is hotspot using some precomputed optimisations that I can't use in my code? I always understood that they don't. What explains this difference?