[R] Performance difference between 32-bit build and 64-bit build on Solaris 8

[Prof Brian Ripley]

Your tests are of problems where you really should be using an optimized 
BLAS.  But because those pointers are twice the size, the L1 cache will 
hold half as many and so I am not surprised at a factor of three on a 
naive implementation.

For linear algebra on large matrices the key to good performance is to 
keep L1 cache misses to a minimum.  Using SunPerf and a 1000x1000 problem 
I got

32-bit
[1] 4.99 0.03 5.02 0.00 0.00
64-bit
[1] 5.25 0.03 5.29 0.00 0.00

and for your regression problem
32-bit
[1] 24.97  0.96 26.15  0.00  0.00
64-bit
[1] 26.25  1.06 27.52  0.00  0.00

So the moral appears to be to take the advice in the R-admin manual and 
tune your linear algebra system.


On Fri, 10 Jun 2005, Scott Gilpin wrote:

> Hi everyone -
>
> I'm seeing a 32-bit build perform significantly faster (up to 3x) than
> a 64 bit build on Solaris 8.  I'm running R version 2.1.0.  Here are
> some of my system details, and some resulting timings:
>
>> uname -a
> SunOS lonetree 5.8 Generic_117350-16 sun4u sparc SUNW,Sun-Fire-V440
>
> lonetree /home/sgilpin >gcc -v
> Reading specs from /usr/local/lib/gcc/sparc-sun-solaris2.8/3.4.2/specs
> Configured with: ../configure --with-as=/usr/ccs/bin/as
> --with-ld=/usr/ccs/bin/ld --disable-nls
> Thread model: posix
> gcc version 3.4.2
>
> I built the 32 bit version of R with no changes to config.site.  I
> built the 64 bit version with the following in config.site:
>
> CC="gcc -m64"
> FFLAGS="-m64 -g -02"
> LDFLAGS="-L/usr/local/lib/sparcv9 -L/usr/local/lib"
> CXXFLAGS="-m64 -g -02"
>
> neither build uses a BLAS.  Both builds are installed on the same
> machine, and the same disk.  The machine has virtually no load; R is
> one of the only processes running during these timings:
>
> First comparison:  solve on a large matrix
>
>> echo 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' |
> /disk/loneres01/R-2.1.0-32bit/bin/R -q --vanilla
>> set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))
> [1] 713.45   0.38 713.93   0.00   0.00
>>
>
>> echo 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' |
> /disk/loneres01/R-2.1.0-64bit/bin/R -q --vanilla
>> set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))
> [1] 2277.05    0.31 2278.38    0.00    0.00
>>
>
> Second comparison:  linear regression
>
> lonetree /home/sgilpin/R >echo 'set.seed(1);
> y<-matrix(rnorm(10000*500),500);
> x<-matrix(runif(500*100),500);
> system.time(fit<-lm(y~x))' | /disk/loneres01/R-2.1.0-32bit/bin/R -q --vanilla
>> set.seed(1);y<-matrix(rnorm(10000*500),500);x<-matrix(runif(500*100),500);system.time(fit<-lm(y~x))
> [1] 23.34  0.80 24.17  0.00  0.00
>>
>
> lonetree /home/sgilpin/R >echo 'set.seed(1);
> y<-matrix(rnorm(10000*500),500);
> x<-matrix(runif(500*100),500);
> system.time(fit<-lm(y~x))' | /disk/loneres01/R-2.1.0-64bit/bin/R -q --vanilla
>> set.seed(1);y<-matrix(rnorm(10000*500),500);x<-matrix(runif(500*100),500);system.time(fit<-lm(y~x))
> [1] 55.34  0.70 56.21  0.00  0.00
>>
>
> Final comparison:  stats-Ex.R (from R-devel)
> lonetree /home/sgilpin/R >time /disk/loneres01/R-2.1.0-32bit/bin/R -q
> --vanilla CMD BATCH stats-Ex.R
>
> real    1m4.042s
> user    0m47.400s
> sys     0m10.390s
> lonetree /home/sgilpin/R >time /disk/loneres01/R-2.1.0-64bit/bin/R -q
> --vanilla CMD BATCH stats-Ex.R
>
> real    1m20.017s
> user    1m3.590s
> sys     0m10.130s
>
> I've seen Prof. Ripley and others comment that a 64 bit build will be
> a little slower because the pointers are larger, and gc() will take
> longer, but these timings seem out of this range.
>
> Any thoughts?
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595