On 5/1/08, Shige Song <[EMAIL PROTECTED]> wrote: > Will the use of jit improve performance of use contributed packages such as > lme4? Thanks.
A technology like a byte-compiler or a just-in-time compiler will change the performance of interpreted code. It will not change the performance of compiled code. My intent is that the compute-intensive parts of the functions in the lme4 package are performed in compiled code. You could profile the execution of a call to lmer that is taking a long time and see where the time is being spent. See ?Rprof for details. An even simpler measure is to add the optional argument verbose = TRUE in a call to lmer and watch the output of the iterations. Everything from the appearance of the first iteration output to the appearance of the last iteration output takes place in a single .Call to a C function mer_optimize. Performance during that period will depend on the C compiler used, the level of optimization used, the use of an accelerated BLAS (which sometimes can be counter-intuitive, we have seen situations where use of an accelerated BLAS slowed down the execution) and, of course, your hardware. Also, during that call the memory profile should stay essentially constant. There is some allocation and freeing of memory taking place during that call but only a few, relatively small, chunks are involved. I just realized that I am speaking about the behavior of the development version of the lme4 package, available on R-forge. The release version is similar but not quite as tightly coded. As indicated above, the first step in optimizing any code should always be to profile the execution of the code and R does provide tools for that. > > Shige > > > On Thu, May 1, 2008 at 7:31 AM, Nelson Castillo <[EMAIL PROTECTED]> wrote: > > > On Wed, Apr 30, 2008 at 6:27 PM, Gabor Grothendieck > > <[EMAIL PROTECTED]> wrote: > > > Aside from optiming your code by making use of R functions > > > that use C underneath as much as possible the big difference > > > between R and Matlab is Matlab's just-in-time compilation of > > > code. When that was introduced in Matlab huge speedups of > > > Matlab programs were noticeable. > > > > > > For R, there is a new package on CRAN, jit, that > > > aims to provide similar speedups. > > > > http://www.milbo.users.sonic.net/ra/index.html > > > > Great! I just found out about ra. In Python I love psyco and I guess I > > will test > > ra soon. > > > > Thanks, > > N.- > > > > -- > > http://arhuaco.org > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
