Intrinsics for Math.min and max

[Martin Grajcar]

Answered inline.

On Tue, Apr 1, 2014 at 11:58 PM, Vitaly Davidovich <vitalyd at gmail.com>wrote:

> Apologies, meant to reply to the list.
>
> Sent from my phone
> On Apr 1, 2014 5:48 PM, "Vitaly Davidovich" <vitalyd at gmail.com> wrote:
>
>> I can't see the attachment (on my phone) but I'm guessing the jumps
>> generated by manual code are highly predicted? What if you try it with an
>> array of random values?
>>
>
The input array is random:

    @Setup public void setUp() {
        final Random random = new Random();
        for (int i=0; i<table.length; ++i) table[i] = random.nextInt();
    }

The whole benchmark is this loop:

    @GenerateMicroBenchmark public int intrinsic() {
        int result = Integer.MIN_VALUE;
        for (final int x : table) result = Math.max(result, x);
        return result;
    }

The values are random, but the branch gets more and more predictable as
result approaches the real maximum.

> I'm guessing the cmov based intrinsics only win on (a) cpus with poor
>> branch prediction, (b) unpredictable branches, or (c) code with lots of
>> branches clogging up branch history buffer.
>>
> Agreed, but my point was not to *force* using cmov for Math.max when the
compiler can do it anyway (though there cases when it doesn't although it
should like
http://stackoverflow.com/questions/19689214/strange-branching-performance).


> Also, is compiler generating larger code when using jumps? If so, icache
>> pressure could be an issue; I don't think a microbenchmark will capture
>> that though.
>>
> I'd guess the code size is about the same. Anyway, this microbenchmark is
really tiny.
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