[Haskell-cafe] Why is Haskell so slow (comparing to Java/Scala)?

Joachim Durchholz jo at durchholz.org
Mon Oct 23 23:09:56 UTC 2017

Am 23.10.2017 um 23:49 schrieb Florian Weimer:
> It is possible that Hotspot optimizes away most of the code, perhaps
> even the entire array allocation.  Meaningful benchmarking is quite
> difficult due to such effects.
> Does the execution time even change if you increase the number of
> iterations (inner or outer)?

I tried that in Java, with this code:

     private static final int SIZE = 400_0000;

     private static final int ITERATIONS = 20;

     public static void main(String[] args) {
         for (int i = 1; i < ITERATIONS; i++) {
             long start = System.currentTimeMillis();
             Long [] a = new Long[SIZE];
             for (int j = 0; j < SIZE; j++) {
                 a[j] = 1L;
             long end = System.currentTimeMillis();
             System.out.println((end - start) + " ms");

Fiddling with SIZE and ITERATIONS led me to the following conclusions:

1) The first two iterations are warm-up, afterwards the times are pretty 
constant (about 7-8 ms for SIZE=100_000).
2) Cranking ITERATIONS up gave semi-regular slow iterations. I blame GC.
3) Per-loop run time seems to be roughly linear with array size, that's 
a strong indicator that the assignments are not optimized away. (In fact 
having a running time of 1-2 ms is a strong indicator that the software 
is in fact blowing some real CPU cycles.)

It is actually possible that the standard HotSpot JVM is faster than 
Haskell, for this type of task - i.e. just array manipulation with 
primitive values, and working set size small enough to make GC 
irrelevant. It's the kind of workload where HotSpot has all the 
information needed to fully optimize everything short of eliminating the 
loop altogether (which is usually not worth it for a mutable-language 
just-in-time compiler).
Make things a bit more complicated and real-world, and this advantage 
will shrink considerably:  Throw in a few classes, subclasses that 
override functions (Haskell equivalent would be unevaluated expressions 
in the list), iterate over a list instead of an array (which will 
actually make the Haskell program faster if the list spine can be 
optimized away), that kind of stuff.

That said, HotSpot is a pretty tough opponent to beat. It has 
person-decates if not person-centuries of optimization under its belt 
after all.
So does GHC, so maybe the comparison isn't so unfair after all, but 
saying "Haskell is slow" from a single microbenchmark simply does not 
hold any value.
Still, it is possible that the JVM is indeed faster for some kinds of 
workload. If that workload is actually relevant, it might be a valid 
optimization potential.

Just my 2 cents :-)


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