I am having difficulty understanding how to use pmap in Julia. I am a
reasonably experienced matlab and c programmer. However, I am new to Julia
and to using parallel functions. I am running an experiment with nested for
loops, benchmarking different algorithms. In the inner loop, I am running
the algorithms across multiple trials. I would like to parallelize this
inner loop (as the outer iteration I can easily run as multiple jobs on a
cluster). The code looks like:
effNumCores = 3
procids = addprocs(effNumCores)
# This has to be added so that each run has access to these function definitions
@everywhere include("experimentUtils.jl")
# Initialize array of RMSE
fill!(runErrors, 0.0);
# Split up runs across number of cores
outerloop = floor(Int, numRuns / effNumCores)+1
r = 1
rend = effNumCores
for i = 1:outerloop
rend = min(r+effNumCores-1, numRuns)
# Empty RMSE passed, since it is create and returned in pmap_errors
Array{Float64}(0,0)
pmap_errors = pmap(r -> learningExperimentRun(mdp,hordeOfD, stepData,
alpha,lambda,beta, numAgents, numSteps, Array{Float64}(0,0), r), r:rend)
for j=1:(rend-r+1)
runErrors[:,:,MEAN_IND] += pmap_errors[j]
runErrors[:,:,VAR_IND] += pmap_errors[j].^2
end
r += effNumCores
end
rmprocs(procids)
The function called above is defined in separate file called
experimentUtils.jl, as
function learningExperimentRun(mdp::MDP, hordeOfD::horde, stepData::transData,
alpha::Float64,lambda::Float64, beta::Float64, numAgents::Int64,
numSteps::Int64, RMSE::Array{Float64, 2}, runNum::Int64)
# if runErrors is empty, then initialize; this is empty for parallel version
if (isempty(RMSE))
RMSE = zeros(Float64,numAgents, numSteps)
else
fill!(RMSE, 0.0)
end
srand(runNum)
agentInit(hordeOfD, mdp, alpha, beta,lambda,BETA_ETD)
getLearnerErrors(hordeOfD,mdp, RMSE,1)
mdpStart(mdp,stepData)
for i=2:numSteps
mdpStep(mdp,stepData)
updateLearners(stepData, mdp, hordeOfD)
getLearnerErrors(hordeOfD,mdp, RMSE,i)
end
return RMSE
end
When I try to run this, I get a large number of workers and get errors that
state that I have too many files open. I believe I must be doing something
seriously wrong. If anyone could help to parallelize this code in julia,
that would be fantastic. I am not tied to pmap, but after reading a bit, it
seemed to be the right function to use.
I should further add that I have an additional loop splitting runs over
cores, even though pmap could do that for me. I did this because pmap_errors
then becomes an array of numRuns (which could be 100s). By splitting it up
into loops, the returned pmap_errors has size that is at most the number of
cores. I am hoping that this memory then gets re-used when starting the
next loop over cores.
I tried at first avoiding this by using a distributed array for runErrors.
But, this was not clearly documented and so I abandoned that approach.
