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> whichmodel.sim <- make.simulation(reps = 8000, + design = equal.cover, + population.description = minkepop, + detectability = detect, + ds.analysis = strat.specific.or.not) > crash.test <- run.simulation(whichmodel.sim, run.parallel = TRUE) |++++++++++++++++++++++ | 43% ~01h 14m 48s Error: cannot allocate vector of size 1.1 Mb 11. unserialize(node$con) 10. recvData.SOCKnode(con) 9. recvData(con) 8. FUN(X[[i]], ...) 7. lapply(cl[1:jobs], recvResult) 6. staticClusterApply(cl, fun, length(x), argfun) 5. clusterApply(cl = cl, x = splitList(X, nchunks), fun = lapply, FUN = fun, ...) 4. do.call(c, clusterApply(cl = cl, x = splitList(X, nchunks), fun = lapply, FUN = fun, ...), quote = TRUE) 3. PAR_FUN(cl, X[Split[[i]]], FUN, ...) 2. pbapply::pblapply(X = as.list(1:simulation@reps), FUN = single.sim.loop, simulation = simulation, save.data = save.data, load.data = load.data, data.path = data.path, cl = myCluster, counter = FALSE) at run.simulation.R#96 1. run.simulation(whichmodel.sim, run.parallel = TRUE)
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Sounds like Cal may know some things that can help with this!
Sorry, something went wrong.
Feel free to contact him for comments - his work on parallel computing is on GPUs, but nonetheless he may have some useful insights.
Information on improving memory usage: http://adv-r.had.co.nz/memory.html#:~:text=Despite%20what%20you%20might%20have,memory%20to%20the%20operating%20system.
LHMarshall
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The text was updated successfully, but these errors were encountered: