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From |
Patrick Roland <[email protected]> |

To |
[email protected] |

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

Date |
Sat, 21 Jul 2012 13:28:33 -0700 |

As a brief followup, and since StataCorp have responded, I tested matrix multiplication too. Stata 12.0 takes fully 100 times longer to multiply two 2000x2000 matrices than MATLAB R2011b. This code took ~21 seconds in Mata: mata j = rnormal(2000,2000,0,1) timer_on(1) g =j*j' timer_off(1) timer() end This code took ~0.21 seconds in MATLAB: j = randn(2000,2000); tic; g = j*j'; toc; Happy to stand corrected if I've made a mistake. On Fri, Jul 20, 2012 at 6:19 PM, Richard Herron <[email protected]> wrote: > Snap. Yes, your m from -runiform()- will certainly be invertible. > > Richard Herron > > > On Fri, Jul 20, 2012 at 7:14 PM, Patrick Roland > <[email protected]> wrote: >> To be clear, my point was that all Mata matrix inverse functions are >> slower than MATLAB. It does seem though that this is not true for >> small matrices (e.g. 100x100), but the difference is easily an order >> of magnitude when it comes to larger matrices (2000x2000). >> >> The fact that I compared cholinv() and a general inverse function >> should be to Mata's favor, since cholinv should presumably be faster >> if it exploits the special structure of the matrix. >> >> X'X is positive definite if X is invertible (as in my example), >> because a'X'Xa = (Xa)'(Xa) > 0. >> >> On Fri, Jul 20, 2012 at 2:48 PM, David M. Drukker <[email protected]> wrote: >>> Patrick Roland <[email protected]> posted that the Mata function >>> -cholinv()- is slower than a Matlab function for large matrices. >>> >>> Others have discussed some issues with Patrick's example. Despite these >>> issues, we took Patrick's post seriously, looked at the code, and found >>> something that could be sped up. >>> >>> We will release a faster version of -cholinv()- in an upcoming executable >>> update. >>> >>> Note that any speed difference related to -cholinv()- is only noticeable for >>> large matrices. For small matrices, such as variance-covariance matrices >>> for models with 100 or fewer parameters, the difference is much harder to >>> find. For example, the computation takes about .001 seconds on my machine. >>> >>> Best, >>> David >>> [email protected] >>> >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: Why is Mata much slower than MATLAB at matrix inversion?***From:*Pradipto Banerjee <[email protected]>

**References**:**st: Why is Mata much slower than MATLAB at matrix inversion?***From:*Patrick Roland <[email protected]>

**Re: st: Why is Mata much slower than MATLAB at matrix inversion?***From:*"David M. Drukker" <[email protected]>

**Re: st: Why is Mata much slower than MATLAB at matrix inversion?***From:*Patrick Roland <[email protected]>

**Re: st: Why is Mata much slower than MATLAB at matrix inversion?***From:*Richard Herron <[email protected]>

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