[concurrency-interest] Some interesting (confusing?) benchmark results

Kirk Pepperdine kirk at kodewerk.com
Tue Feb 12 04:50:10 EST 2013


Hi,
On 2013-02-11, at 9:52 PM, thurston at nomagicsoftware.com wrote:
Hi T,

Can you pub the raw data from your runs? Average tends to hide effects and it's difficult to say anything with only that measure.

Regards,
Kirk


> Hello,
> 
> I made some initial attempts at using ForkJoin framework for some rather obvious recursively parallel use-cases, namely summing the elements of an int[] and also sorting an int[] (randomly filled).
> 
> The problem-sizes I used ranged from 1M - 10M.
> 
> I really enjoy using the framework and find it relatively easy to reason about my programs (if not necessarily the internals of the framework).
> But I was disappointed with the results: in both cases they were slower than the corresponding Java serial implementation.
> 
> I completely understand the principle of YMMV, and I wasn't expecting 2x speedup, but especially in the case of the sort, but I was expecting that ForkJoin would do at least a little better than the single-threaded version.  I guess what I'm asking is: are these results surprising?  Does it mean I'm doing something wrong?
> 
> I'll give a brief description of my implementation:
> single-threaded:  Arrays.sort(int[])
> 
> ForkJoin: I'm using a merge-sort, with THRESHOLD = 250 (arrived at by trial-and-error)
> 
> int[] compute()
> {
> if int[].length < THRESHOLD
>    return insertionSort(int[])
> left = new MergeSort(int[] //split in half)
> right = new MergeSort(int[] //other half)
> return merge(right.compute(), left.join())
> }
> 
> The insertionSort() and merge() methods are just standard implementations; there is a bit of apples to oranges comparison since Arrays.sort() uses an optimized quicksort, but we're still talking O(nlog(n))
> 
> Just ran it on my laptop:
> Windows 7 64-bit
> 1.7.0_03; Java HotSpot(TM) 64-Bit Server VM 22.1-b02
> Core 2 Duo==> 2 cores 2GHz
> 
> 2M int[]:
> single-threaded: ~330ms
> ForkJoin (2 workers): ~390ms
> 
> Would appreciate any feedback and hopefully the #s are somewhat helpful (and please no scoffawing at my antiquated machine)
> 
> -T
> 
> 
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