[R-SIG-Mac] Perplexed benchmark result from a new Macbook Pro Core i5

[Simon Urbanek]

On May 8, 2010, at 2:53 PM, Gardar Johannesson wrote:

> I was just replacing a Macbook Pro from 2008 (with a 2.2GHz Intel Core 2 Duo) with a new Macbook Pro (with a 2.4GHz Intel Core i5). To get a rough idea about the difference in R execution speed I ran a small test, with the output shown below. In short:
> 
> 1) The new Macbook Pro was ca 60% _slower_ at linear algebra (crossprod() and solve())
> 2) The new Macbook Pro was ca 17% faster on a long for-loop
> 3) Linking against Goto2 versus vecLib improved the linear algebra results slightly
> 
> Both test were done using the same 2.11.0 dmg image from CRAN. 
> 
> Any thoughts on this? 
> 

What OS X versions are on the respective machines? The vecLib performance varies greatly with their versions.


> Any ideas how I can improve the performance results? What about compiling from source?
> 

Note that you are essentially just comparing the BLAS libraries on each machine, R is practically not involved in this at all, so if you meant R in the "compiling from source" then the answer is likely no (R speed is what you see in the loops).


I don't have an i5 arounds, but comparing similar architectures (Penryn vs Nehalem) gives a slight edge to Nehalem (3.8s @ 2.8GHz vs 3.4s @ 2.66Ghz on solve(B)) but that is for a Xeon so the memory speed may be the edge (everything on OS X 10.6.3).

Cheers,
Simon


> 
> Thanks,
> Gardar Johannesson
> 
> 
> ###########################################
> ## Results from new macbook pro (Core i5 @ 2.4Ghz)
> 
>> set.seed(1)
>> A <- matrix(rnorm(2000*2000),2000,2000)
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  2.500   0.058   0.816 
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  2.502   0.050   0.814 
>> system.time(solve(B))
>   user  system elapsed 
>  7.208   0.265   2.740 
>> system.time(solve(B))
>   user  system elapsed 
>  7.121   0.264   2.666 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  2.964   0.602   3.528 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  3.040   0.732   3.732 
>> sessionInfo()
> R version 2.11.0 (2010-04-22) 
> i386-apple-darwin9.8.0 
> 
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
> 
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base     
> 
> loaded via a namespace (and not attached):
> [1] tools_2.11.0
>> 
> 
> ###################################################
> ## Results from old macbook pro (Core 2 Duo @ 2.2GHz)
> 
>> set.seed(1)
>> A <- matrix(rnorm(2000*2000),2000,2000)
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  1.429   0.073   0.800 
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  1.429   0.064   0.874 
>> system.time(solve(B))
>   user  system elapsed 
>  4.532   0.285   2.860 
>> system.time(solve(B))
>   user  system elapsed 
>  4.521   0.281   2.834 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  3.501   0.764   4.215 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  3.459   0.702   4.113 
>> sessionInfo()
> R version 2.11.0 (2010-04-22) 
> i386-apple-darwin9.8.0 
> 
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
> 
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base     
>> 
> 
> 
> ###################################################
> ## Results from new macbook pro (Core i5 @ 2.4Ghz)
> ## Linking against Goto2 BLAS (vs vecLib)
> 
>> set.seed(1)
>> A <- matrix(rnorm(2000*2000),2000,2000)
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  2.348   0.124   0.635 
>> system.time(B <- crossprod(A))
>   user  system elapsed 
>  2.342   0.110   0.622 
>> system.time(solve(B))
>   user  system elapsed 
>  6.634   0.327   2.158 
>> system.time(solve(B))
>   user  system elapsed 
>  6.697   0.348   2.034 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  2.577   0.548   2.885 
>> system.time({a <- rep(1.0,100); for(i in 1:1e6) a <- 1.0*a+0.0})
>   user  system elapsed 
>  2.411   0.478   2.859 
>> sessionInfo()
> R version 2.11.0 (2010-04-22) 
> i386-apple-darwin9.8.0 
> 
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
> 
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