Is it possible that any one of capitals,{marketHistory for i in 1
:trials},depths,ALRs,{vec(variances) for i in 1:trials},{weights[:,i] for i
in 1:trials},sigComponents is of length 1?Testing with "-p 3" and a busywait function: @everywhere function bw(s...) t1 = time() while (time() - t1) < s[1] end end pmap(bw, [10,20,30], [4,5,6]) results in 3 workers first taking up 100% of 3 cores, then 2 and finally 1 for the final 10 seconds. pmap(bw, [10,20,30], [4]) will result in just one worker taking up one core for 10 seconds. On Sun, Feb 23, 2014 at 3:25 PM, Micah McClimans <[email protected]>wrote: > Sure. > > Invoked with julia -p 8 > > fid=open("/home/main/data/juliafiles/Julia/machinefile.txt") > > rc=readlines(fid) > > m={match(r"(\r|\n)",rcd) for rcd in rc} > > machines={rc[ma][1:(m[ma].offset-1)] for ma in 1:length(m)} > ... > addprocs(machines;dir="/home/main/data/programfiles/julia/usr/bin") > ... > @everywhere progfile="/home/main/data/juliafiles/Julia/WLPPInt.jl"@everywhere > marketHistoryFile="/home/main/data/juliafiles/Julia/daily.mat" > @everywhere using MAT > @everywhere include(progfile) > @everywhere Daily= matread(marketHistoryFile)@everywhere marketHistory= > NYSE["NYSE_Smoothed_Closes"] > ... > results=pmap(runWLPPIntTest,capitals,{marketHistory for i in > 1:trials},depths,ALRs,{vec(variances) for i in 1:trials},{weights[:,i] for i > in 1:trials},sigComponents) > > I'm not really sure if this is enough to be useful though, or what really > would be able to be useful. > > > > On Sunday, February 23, 2014 3:58:04 AM UTC-5, Amit Murthy wrote: > >> Is it possible to share the relevant portions of the call here? >> >> >> On Sun, Feb 23, 2014 at 11:44 AM, Micah McClimans <[email protected]>wrote: >> >>> Thank you, it turns out my problem was coming from an @everywhere macro, >>> not from pmap. >>> >>> However, and I hope it is not bad practice continuing in this same >>> thread, but now I'm seeing that pmap is not utilizing all of the workers >>> available for the process, in fact it is using only one, despite having 8 >>> local and 8 remote workers available. What sort of problems could be >>> causing this behavior? >>> >>> >>> On Saturday, February 22, 2014 6:32:18 PM UTC-5, Stefan Karpinski wrote: >>> >>>> If there are other processors, pmap doesn't use the head node by >>>> default: >>>> >>>> julia> addprocs(2) >>>> 2-element Array{Any,1}: >>>> 2 >>>> 3 >>>> >>>> julia> pmap(x->myid(), 1:10) >>>> 10-element Array{Any,1}: >>>> 2 >>>> 3 >>>> 3 >>>> 2 >>>> 2 >>>> 3 >>>> 2 >>>> 3 >>>> 2 >>>> 3 >>>> >>>> >>>> On Sat, Feb 22, 2014 at 5:50 PM, Micah McClimans >>>> <[email protected]>wrote: >>>> >>>>> I am working on distributing a compute intensive task over a cluster >>>>> in Julia, using the pmap function. However, for several reasons I would >>>>> like to avoid having the master node used in the computation- is there a >>>>> way to accomplish this using the built in keyword, or will I need to >>>>> rewrite pmap? >>>>> >>>> >>>> >>
