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Re: st: Why is Mata much slower than MATLAB at matrix inversion?


From   Richard Herron <[email protected]>
To   [email protected]
Subject   Re: st: Why is Mata much slower than MATLAB at matrix inversion?
Date   Fri, 20 Jul 2012 16:26:59 -0400

Why is j pos def? j = mm' is symmetric with non-negative numbers. I
can think of a j = [0, 1; 1, 0] and k' = [1, -1] so that k'jk = -2 < 0
so that j isn't pos def. Am I missing something? (Although this isn't
an answer to the real question.)

Richard Herron


On Fri, Jul 20, 2012 at 4:11 PM, Patrick Roland
<[email protected]> wrote:
> j is necessarily positive definite. The speed difference seems to hold
> for matrices of all sizes. Would very much appreciate any insight
> here.
>
> On Fri, Jul 20, 2012 at 12:47 PM, Richard Herron
> <[email protected]> wrote:
>> Your matrix j isn't necessarily positive definite, although it is symmetric.
>>
>> Does this significant speed advantage stand for real use cases? I
>> don't know of a use case where you need to invert a 2000 x 2000
>> matrix.
>>
>> I think this is about all the the help that I can provide; I spend
>> most of my time outside of Mata. Hopefully one of the experts can shed
>> some light here.
>>
>> Richard Herron
>>
>>
>> On Fri, Jul 20, 2012 at 3:18 PM, Patrick Roland
>> <[email protected]> wrote:
>>> The matrix formation takes a negligible amount of time. luinv() seems
>>> to be (much) faster than cholinv() even for positive definite
>>> matrices. Here's the code I used to check:
>>>
>>> timer_clear()
>>> mata
>>> m = runiform(2000,2000)
>>> j = m*m'
>>> timer_on(1)
>>> h = cholinv(j)
>>> timer_off(1)
>>> timer_on(2)
>>> p = luinv(j)
>>> timer_off(2)
>>> timer()
>>>
>>>
>>> On Fri, Jul 20, 2012 at 11:57 AM, Richard Herron
>>> <[email protected]> wrote:
>>>> -cholinv()- would be faster if you met the symmetric, positive
>>>> definite requirement. I am also surprised that Mata isn't competitive
>>>> with Matlab on matrix inversion (I thought they all used the same
>>>> algorithms).
>>>>
>>>> Have you tried taking the matrix generation step out of the timing
>>>> block? Is there a chance that the matrix formation process if
>>>> different between the two (Sorry, I don't have Stata and Matlab
>>>> installs handy).
>>>>
>>>> Richard Herron
>>>>
>>>>
>>>> On Fri, Jul 20, 2012 at 2:50 PM, Patrick Roland
>>>> <[email protected]> wrote:
>>>>> luinv() takes about 15 times longer than MATLAB's inverse function.
>>>>> Maybe I'm being naive, but why wouldn't all serious matrix languages
>>>>> invert matrices at roughly the same speed? Don't they use the same
>>>>> linear algebra routines?
>>>>>
>>>>> Another curiosity is that the luinv() is more general and faster. Why
>>>>> would anyone want to use cholinv()?
>>>>>
>>>>> On Fri, Jul 20, 2012 at 9:17 AM, Richard Herron
>>>>> <[email protected]> wrote:
>>>>>> Patrick, -cholinv()- requires a symmetric positive definite matrix,
>>>>>> but I don't think you M matrix is PD. Try -luinv()-.
>>>>>>
>>>>>> Although for most use cases your matrix will be symmetric, right? Then
>>>>>> you should use -invsym()- or a solve function.
>>>>>>
>>>>>> Richard Herron
>>>>>>
>>>>>>
>>>>>> On Thu, Jul 19, 2012 at 9:22 PM, Patrick Roland
>>>>>> <[email protected]>
>>>>>> wrote:
>>>>>>>
>>>>>>> I'm comparing two code snippets. In Mata:
>>>>>>>
>>>>>>> mata
>>>>>>> timer_on(1)
>>>>>>> M = rnormal(2000,2000,0,1)
>>>>>>> J = cholinv(M)
>>>>>>> timer_off(1)
>>>>>>> timer()
>>>>>>> end
>>>>>>>
>>>>>>> In MATLAB:
>>>>>>>
>>>>>>> tic;
>>>>>>> M = normrnd(0,1,2000,2000);
>>>>>>> J = inv(M);
>>>>>>> toc;
>>>>>>>
>>>>>>> I find that MATLAB is about 20 times faster (1.5 seconds vs 30
>>>>>>> seconds). Is there something I'm missing here, or is MATLAB just much
>>>>>>> faster at matrix inversion? I'd much prefer to use Mata because of
>>>>>>> integration with Stata, but if the speed difference is going to be on
>>>>>>> this order then MATLAB is more attractive.
>>>>>>>
>>>>>>>
>>>>>>> Any input here is appreciated.
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