Parallel linear model

I have some additional questions: I want to add an extra matrix that I keep fixed, but I cannot get the parallel version working, any suggestions?

y<-rnorm(1000)
x<-matrix(rnorm(1000*10000),ncol=10000)
fix<-matrix(rnorm(1000*10),ncol=10)
#Non-parallel version works fine
pval<-apply(x,2, function(x)summary(lm(y~x+fix))$coeff[2,4])

library(parallel)
cores<-detectCores()
cl <- makeCluster(cores, methods=FALSE)
clusterExport(cl,"y","fix")
pvalstruct<-parApply(cl, x,2, function(x)summary(lm(y~x+fix))$coeff[2,4])

Patrik

"Patrik Waldmann" <patrik.waldmann at boku.ac.at> 23/08/2012 12:12 >>>

Here's a comparison on Windows based on 8 cores (excluding foreach):

y<-rnorm(1000)
x<-matrix(rnorm(1000*10000),ncol=10000)
dimx<-dim(x)
library(rbenchmark)
benchmark(pval<-apply(x,2, function(x)summary(lm(y~x))$coeff[2,4]), replications=1)

1 pval <- apply(x, 2, function(x) summary(lm(y ~ x))$coeff[2, 4])
test replications elapsed relative user.self sys.self user.child sys.child
1    1   25.16        1     20.46     2.17         NA        NA

library(parallel)
cores<-detectCores()
cl <- makeCluster(cores, methods=FALSE)
clusterExport(cl,"y")
benchmark(pval<-parApply(cl, x,2, function(x)summary(lm(y~x))$coeff[2,4]), replications=1)

1 pval <- parApply(cl, x, 2, function(x) summary(lm(y ~ x))$coeff[2, 4])
   test replications elapsed relative user.self sys.self user.child sys.child
1      1    5.52        1      0.74     0.28         NA        NA

stopCluster(cl)

# More fair

benchmark({cores<-detectCores()

+ cl <- makeCluster(cores, methods=FALSE)
+ clusterExport(cl,"y")
+ pval<-parApply(cl, x,2, function(x)summary(lm(y~x))$coeff[2,4])}, replications=1)
   test replications elapsed relative user.self sys.self user.child sys.child
1    {            1    7.11        1      0.65     0.37         NA        NA
Warning messages:
1: closing unused connection 10 (<-patwa-PC:10187)
2: closing unused connection 9 (<-patwa-PC:10187)
3: closing unused connection 8 (<-patwa-PC:10187)
4: closing unused connection 7 (<-patwa-PC:10187)
5: closing unused connection 6 (<-patwa-PC:10187)
6: closing unused connection 5 (<-patwa-PC:10187)
7: closing unused connection 4 (<-patwa-PC:10187)
8: closing unused connection 3 (<-patwa-PC:10187)

stopCluster(cl)

What does the warnings refer to?

Patrik

Dirk Eddelbuettel <edd at debian.org> 23/08/2012 02:53 >>>

The difference between user and elapsed is an old hat. Here is a great
example (and IIRC first shown here by Simon) with no compute time:

    R> system.time(mclapply(1:8, function(x) Sys.sleep(1)))   ## 2 cores by default
       user  system elapsed
      0.000   0.012   4.014
    R> system.time(mclapply(1:8, function(x) Sys.sleep(1), mc.cores=8))
       user  system elapsed
      0.012   0.020   1.039
    R>

so elapsed time is effectively the one second a Sys.sleep(1) takes, plus
overhead, if we allow for all eight (hyperthreaded) cores here.  By Brian
Ripley's choice a default of two is baked-in, so clueless users only get a
small gain.  "user time" is roughly the actual system load _summed over all
processes / threads_.

With that, could I ask any of the participants in the thread to re-try with a
proper benchmarking package such as rbenchmark or microbenchmark?  Either one
beats to the socks of system.time:

    R> library(rbenchmark)
    R> benchmark( mclapply(1:8, function(x) Sys.sleep(1)), mclapply(1:8, function(x) Sys.sleep(1), mc.cores=8), replications=1)
                                                       test replications elapsed relative user.self sys.self user.child sys.child
    1               mclapply(1:8, function(x) Sys.sleep(1))            1   4.013  3.89612     0.000    0.008      0.000     0.004
    2 mclapply(1:8, function(x) Sys.sleep(1), mc.cores = 8)            1   1.030  1.00000     0.004    0.008      0.004     0.000
    R>

and

    R> library(microbenchmark)
    R> microbenchmark( mclapply(1:8, function(x) Sys.sleep(1)), mclapply(1:8, function(x) Sys.sleep(1), mc.cores=8), times=1)
    Unit: seconds
                                                       expr     min      lq  median      uq     max
    1               mclapply(1:8, function(x) Sys.sleep(1)) 4.01377 4.01377 4.01377 4.01377 4.01377
    2 mclapply(1:8, function(x) Sys.sleep(1), mc.cores = 8) 1.03457 1.03457 1.03457 1.03457 1.03457
    R>

(and you normally want to run either with 10 or 100 or ... replications /
times).

Dirk