Where does your variable `dims` come from? As pointed out above, global
variables can hurt type inference.
On Mar 13, 2016 8:29 AM, "Tim Loderhose" <[email protected]> wrote:

> I implemented the suggestions (see updated gist:
> https://gist.github.com/timlod/0f607e311d0464fd6c63).
> The allocation in the for loops disappeared and the time required halved
> to ~3s. The mmap access though still allocated a lot.
> And the vectorised access is still much faster and allocates less
> (although I want to get rid of the allocation altogether).
> Any other ideas?
>
> On Saturday, 12 March 2016 15:15:51 UTC+1, Dan wrote:
>>
>> Yep, `peCounters`, `paCounters` and `dims` are not type-stable. They are
>> one type by their default values and then assigned another. Perhaps rename
>> the default parameters, and copy them to `peCounters`, `paCounters` and
>> `dims` only if they are set to something other than `0`.
>>
>> Also, `mdhcounters` might not return a definite type (need to check that
>> function).
>> Fixing these should make the loop efficient.
>>
>> On Saturday, March 12, 2016 at 4:05:39 PM UTC+2, Tim Loderhose wrote:
>>>
>>> Here's the actual code:
>>> https://gist.github.com/timlod/0f607e311d0464fd6c63
>>> <https://www.google.com/url?q=https%3A%2F%2Fgist.github.com%2Ftimlod%2F0f607e311d0464fd6c63&sa=D&sntz=1&usg=AFQjCNHB4_Itk64Xevbo5RACmmrF0lsgBA>
>>>
>>> I am running the code from the REPL, may that be a problem? (As I read
>>> in the REPL everything is global). In the file nothing is global.
>>> Also, the counters are UInt16s, but that shouldnt matter I guess.
>>>
>>> Thanks for the help so far!
>>>
>>> On Saturday, 12 March 2016 14:22:38 UTC+1, Dan wrote:
>>>>
>>>> It's better to have code which actually runs in the post. In any case,
>>>> the allocations at the `for` lines is suspicious - the for should basically
>>>> only allocate a counter. Are there any global variables? Is `counter1` or
>>>> `counter2` or `dims` global? Globals are always a good source of confusion
>>>> to the type-inference engine.
>>>>
>>>> On Saturday, March 12, 2016 at 2:28:51 PM UTC+2, Tim Loderhose wrote:
>>>>>
>>>>> The code is in a function. I changed the names a bit to make it more
>>>>> understandable. The actual function is longer and has different variable
>>>>> names.
>>>>>
>>>>> On Saturday, 12 March 2016 13:01:28 UTC+1, tshort wrote:
>>>>>>
>>>>>> Is that code in a function? (It should be.) Also, one of your
>>>>>> variable names changed to `counter1s`. Suspect a type instability.
>>>>>> On Mar 12, 2016 4:12 AM, "Tim Loderhose" <[email protected]> wrote:
>>>>>>
>>>>>>> I tried around with that a bit, but then it gets much worse: From
>>>>>>> ~1s to ~6s, allocation as shown:
>>>>>>>
>>>>>>> 153710487     mat = Array{Complex64}(dims...)
>>>>>>>   4722450       file = Mmap.mmap(filename, Array{Complex64,2},
>>>>>>> (dims[2],length(counter1)))
>>>>>>>      9568          for i = 1:dims[2]
>>>>>>>      4000             for j = 1:length(counter1)
>>>>>>> 1690462534          mat[counter1s[j],i,counter2[j]] = file[i,j]
>>>>>>>         -                 end
>>>>>>>
>>>>>>> I swapped the for loops around here, but that didn't matter. I can
>>>>>>> gain a little bit by indexing i into the first dimension of mat, but it
>>>>>>> still lags far behind.
>>>>>>> Any other ideas?
>>>>>>>
>>>>>>> On Saturday, 12 March 2016 03:15:33 UTC+1, Greg Plowman wrote:
>>>>>>>>
>>>>>>>> I think array slices (on right hand side of assignment) create new
>>>>>>>> arrays, hence the allocation.
>>>>>>>> Try writing an explicit loop instead, something like:
>>>>>>>>
>>>>>>>> for j = 1:length(counter1)
>>>>>>>>    for i = 1:size(file,1)
>>>>>>>>        mat[counter1[j],i,counter2[j]] = file[i,j]
>>>>>>>>    end
>>>>>>>> end
>>>>>>>>
>>>>>>>>
>>>>>>>> On Saturday, March 12, 2016 at 12:25:00 PM UTC+11, Tim Loderhose
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Hi,
>>>>>>>>>
>>>>>>>>> I have a question regarding some allocation in my code I would
>>>>>>>>> like to get rid of.
>>>>>>>>> I am memory mapping a file (which could be very large) which is
>>>>>>>>> part of a complex 3D matrix, and then put its contents into the
>>>>>>>>> preallocated matrix along the second dimension. I need the counters 
>>>>>>>>> because
>>>>>>>>> the contents of file are only a subset of the full matrix.
>>>>>>>>>
>>>>>>>>> Here's a profiled snippet, where the file which is loaded has
>>>>>>>>> 120619520 bytes.
>>>>>>>>>
>>>>>>>>> 153705063     mat = Array{Complex64}(dims...)
>>>>>>>>>  4721282        file = Mmap.mmap(filename, Array{Complex64,2},
>>>>>>>>> (dims[2],length(counter1)))
>>>>>>>>> 16                   for i = 1:length(counter1)
>>>>>>>>> 148179531           mat[counter1[i],:,counter2[i]] = file[:,i]
>>>>>>>>>         -              end
>>>>>>>>>
>>>>>>>>> Why does the code allocate so much memory inside the for-loop
>>>>>>>>> (even more bytes than the contents of file)?
>>>>>>>>> It seems like this is a trivial matter, right now I just can't get
>>>>>>>>> my head around it, any help is appreciated :)
>>>>>>>>>
>>>>>>>>> Thanks,
>>>>>>>>> Tim
>>>>>>>>>
>>>>>>>>

Reply via email to