> On 29 Sep 2016, at 10:05, Gerriet M. Denkmann <g...@mdenkmann.de> wrote:
>
>
>> On 29 Sep 2016, at 14:38, Quincey Morris
>> <quinceymor...@rivergatesoftware.com> wrote:
>>
>> On Sep 29, 2016, at 00:15 , Gerriet M. Denkmann <g...@mdenkmann.de> wrote:
>>>
>>> dispatch_apply( nbrOfThreads, queue, ^void(size_t idx)
>>>
>>> As my computer has just 8 CPUs, I thought that using nbrOfThreads > 8 would
>>> be silly: adding overhead without gaining anything.
>>>
>>> Turns out this is quite wrong. One function (called threadHappyFunction)
>>> works more than 10 times faster using nbrOfThreads = a few ten-thousand (as
>>> compared to nbrOfThreads = 8).
>>>
>>> This is nice, but I would like to know why can this happen.
>>
>> What makes you think “nbrOfThreads” represents a number of threads?
>
> Well, nothing. Just let’s call it nbrOfBlocksToBeUsedByDispatchApply, or
> whatever. But ultimately any of these things has to run on a CPU, of which
> there are no more than 8.
There are mored shared resources than just execution units in your system (e.g.
memory bandwidth, or for non-linear accesses latency). Maybe one of your blocks
is bandwidth bound, while the other is compute bound? Your second function
might be memory bound (with lots of read-modify-write traffic). There are many
other factors (and the dispatch_apply man-page tells you that number of
invocations is very dependant on your block), such as caches or
hyper-threading. The performance counters in Instruments may be able to guide
you.
Daniel.
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