From 022ca08a54354739616b8c8f5d4e7052fdf616fa Mon Sep 17 00:00:00 2001 From: Manon Simonot Date: Tue, 7 Jan 2025 16:32:04 +0100 Subject: [PATCH] Progress on double paralleism. --- R/point-estimation.R | 28 +++++++++---- R/sysdata.rda | Bin 269567 -> 269609 bytes data-raw/df_parallelization.rds | Bin 566 -> 603 bytes data-raw/parallelization-vignette.R | 26 ++++++++---- vignettes/parallelization.Rmd | 62 +++++++++++++++++++++------- 5 files changed, 86 insertions(+), 30 deletions(-) diff --git a/R/point-estimation.R b/R/point-estimation.R index cffdcab..30e753f 100644 --- a/R/point-estimation.R +++ b/R/point-estimation.R @@ -6,12 +6,25 @@ compute_point_estimate <- function(pf, nparams <- pf$nparams if (!is.null(guess)) { - # uses user default cluster - opt <- optimParallel::optimParallel( - par = guess, - fn = pf$get_value, - control = list(fnscale = -1) - ) + # if user did not set a default cluster we compute in sequential + if (is.null(parallel::getDefaultCluster())) { + cli::cli_alert_warning("Default cluster has not been set. You may consider setting one to run computation in parallel.") + opt <- stats::optim( + par = guess, + fn = pf$get_value, + method = "L-BFGS-B", + control = list(fnscale = -1) + ) + } + else { + # uses user default cluster to compute in parallel + opt <- optimParallel::optimParallel( + par = guess, + fn = pf$get_value, + control = list(fnscale = -1), + parallel = list(cl = NULL, forward = FALSE, loginfo = FALSE) + ) + } x0 <- opt$par fval <- opt$value } else { @@ -21,6 +34,7 @@ compute_point_estimate <- function(pf, if (length(upper_bound) != nparams) abort("The number of provided upper bounds does not match the number of parameters.") + # if user default cluser is not set, will run in sequential, else run in parallel opt <- rgenoud::genoud( fn = pf$get_value, nvars = nparams, @@ -31,7 +45,7 @@ compute_point_estimate <- function(pf, wait.generations = 2 * nparams + 1, BFGSburnin = 2 * nparams + 1, print.level = 0, - cluster = parallel::getDefaultCluster(), + cluster = if (!is.null(parallel::getDefaultCluster())) parallel::getDefaultCluster() else FALSE, balance = nparams > 2 ) opt <- compute_point_estimate( diff --git a/R/sysdata.rda b/R/sysdata.rda index 2270f2238f4ef220f6aa09e4216297bd3df3a516..ee327b452d5c549b7923bbdd85fe3add338e3b07 100644 GIT binary patch delta 77629 zcmV(%K;pmuxe%$k5P*aMv;sZw2u(O(HGmCKKa)Y&Abo0ed z-gVY_rn4%uyIY$(9JQBon!9$pw=Q<$w{GsX+iQ2b-uCBg_p`NG?Qdhb?_TP+bKcKh z?_8_Q_kWwGs@rJStvXqqFKTG=^49L>p4#naRMvW3?{?m0l=E`#_BVTnS?k^FX7_u$ zx_i`hd%gG9J>I_BtoF;^9dt)#mx~W)wZiW9)7@6;t<{@Pd%d2zZMy5ZxoGcunZ4NF zmbLD@Yu?>7cf51%-+QZNp7FW8H_g|3*S)%Q-+z4i_WRd+@2__^dwaOIJ38Ne?auqR zHQQI--SxiDyRGf-x6fVgw(INe<9BU)*6VxMy?luFXf@I4)o9j+fsyKi=o&t~_76ep zrR%t%<>=684?*Z@^cKp{+Xv3d8++c-^d66|p}nuRz3;dM1E2w*kn{=-9<&cy6#DzN zkAFkChpy}apgx%Z`!K5d-F?o3Lwe6oSvqUG55B}tua=vz^bflO&|hHs4ujiLUX9(y z)9-uUY2DpEp5xQ&-)8#(=pKX6P(F`edn(&cc2_%VdwqS>+@0OIS55ZWH({Xl<+cw) z0%B=|(?$VJfi$PEOqh%jf@H~n00000000#Tq!0;!045=( 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z%|T%1&%$LNEgb|dEw24(;^QF5?c3#D9_JwF{C(QoU4MlRf;9^lz5mrcTZ_v fu?Wf+02cGhGfOh^OH07w3=IDO7CD^fSpon6%>NTh diff --git a/data-raw/parallelization-vignette.R b/data-raw/parallelization-vignette.R index 79c04ce..79a741f 100644 --- a/data-raw/parallelization-vignette.R +++ b/data-raw/parallelization-vignette.R @@ -25,6 +25,10 @@ stat_assignments <- list(delta = 1) # Inference on the mean without parallelization -------------------------------- +plan(sequential) +setDefaultCluster(NULL) +progressr::handlers(global = FALSE) + pf <- PlausibilityFunction$new( null_spec = null_spec, stat_functions = stat_functions, @@ -32,7 +36,9 @@ pf <- PlausibilityFunction$new( x, y ) -pf$set_point_estimate(mean(y) - mean(x)) +tic() +pf$set_point_estimate() +time_without_parallel <- toc()$callback_msg pf$set_nperms(nperms) pf$set_parameter_bounds( @@ -47,11 +53,11 @@ pf$set_grid( tic() pf$evaluate_grid(grid = pf$grid) -time_without_parallelization <- toc()$callback_msg +time_without_future <- toc()$callback_msg # Inference on the mean with parallelization ----------------------------------- -ncores <- 4 +ncores <- 3 plan(multisession, workers = ncores) cl <- makeCluster(ncores) setDefaultCluster(cl) @@ -64,7 +70,9 @@ pf <- PlausibilityFunction$new( x, y ) -pf$set_point_estimate(mean(y) - mean(x)) +tic() +pf$set_point_estimate() +time_with_parallel <- toc()$callback_msg pf$set_nperms(nperms) pf$set_parameter_bounds( @@ -79,12 +87,16 @@ pf$set_grid( tic() pf$evaluate_grid(grid = pf$grid) -time_with_parallelization <- toc()$callback_msg +time_with_future <- toc()$callback_msg + +stopCluster(cl) df_parallelization <- list( delta = pf$grid$delta, - time_par = time_with_parallelization, - time_without_par = time_without_parallelization + time_without_parallel = time_without_parallel, + time_without_future = time_without_future, + time_with_parallel = time_with_parallel, + time_with_future = time_with_future ) saveRDS(df_parallelization, "data-raw/df_parallelization.rds") diff --git a/vignettes/parallelization.Rmd b/vignettes/parallelization.Rmd index fd34a3b..a2d157c 100644 --- a/vignettes/parallelization.Rmd +++ b/vignettes/parallelization.Rmd @@ -14,8 +14,10 @@ knitr::opts_chunk$set( ) library(flipr) load("../R/sysdata.rda") -time_without_parallelization <- df_parallelization$time_without_par -time_with_parallelization <- df_parallelization$time_par +time_without_parallel <- df_parallelization$time_without_parallel +time_without_future <- df_parallelization$time_without_future +time_with_parallel <- df_parallelization$time_with_parallel +time_with_future <- df_parallelization$time_with_future ``` The [**flipr**](https://permaverse.github.io/flipr/) package uses functions @@ -25,13 +27,21 @@ user side. We illustrate here how to achieve asynchronous evaluation. We use the [**future**](https://future.futureverse.org/index.html) package to set the plan, the **parallel** package to define a default cluster, and the [**progressr**](https://progressr.futureverse.org/index.html) package to report -progress updates. +progress updates. + +More precisely, setting a default cluster with **parallel** is useful to allow +parallel computation of the point estimate if an estimation is needed. On the +other side, setting the plan with +[**future**](https://future.futureverse.org/index.html) allows parallel +computation when evaluating the plausibility function. A comparison of +computation time with sequential and parallel computation for those two cases is +done in the following. ## Computation without parallel processing To show the benefit of parallel processing, we compare here the processing times -necessary to evaluate a grid with a plausibility function. First, here is the -computation without parallelization. +necessary to compute a point estimation and to evaluate the grid for a +plausibility function. First, here is the computation without parallelization. ```{r, eval=FALSE} set.seed(1234) @@ -51,7 +61,17 @@ pf <- PlausibilityFunction$new( x, y ) -pf$set_point_estimate(mean(y) - mean(x), overwrite = TRUE) +tic() +pf$set_point_estimate() +time_without_parallel <- toc()$callback_msg +``` + +```{r} +time_without_parallel +``` + +```{r, eval=FALSE} + pf$set_parameter_bounds( point_estimate = pf$point_estimate, conf_level = pf$max_conf_level @@ -63,11 +83,11 @@ pf$set_grid( tictoc::tic() pf$evaluate_grid(grid = pf$grid) -time_without_parallelization <- tictoc::toc() +time_without_future <- tictoc::toc()$callback_msg ``` ```{r} -time_without_parallelization +time_without_future ``` ## Computation with parallel processing @@ -83,8 +103,8 @@ following code with the `progressr::handlers()` function. After these settings, in this example. ```{r, eval=FALSE} -ncores <- 4 -future::plan(multisession, workers = ncores) +ncores <- 3 +future::plan(future::multisession, workers = ncores) cl <- parallel::makeCluster(ncores) parallel::setDefaultCluster(cl) progressr::handlers(global = TRUE) @@ -106,7 +126,16 @@ pf <- PlausibilityFunction$new( x, y ) -pf$set_point_estimate(mean(y) - mean(x), overwrite = TRUE) +tic() +pf$set_point_estimate() +time_with_parallel <- toc()$callback_msg +``` + +```{r} +time_with_parallel +``` + +```{r, eval=FALSE} pf$set_parameter_bounds( point_estimate = pf$point_estimate, conf_level = pf$max_conf_level @@ -118,7 +147,7 @@ pf$set_grid( tictoc::tic() pf$evaluate_grid(grid = pf$grid) -time_with_parallelization <- tictoc::toc() +time_with_future <- tictoc::toc()$callback_msg parallel::stopCluster(cl) ``` @@ -127,18 +156,19 @@ It is good practice to shut down the workers with the `parallel::stopCluster()` function at the end of the code. ```{r} -time_with_parallelization +time_with_future ``` This experiment proves that we can save a lot of computation time when using -parallel processing, as we gained approximately 33 seconds in this example to -evaluate the plausibility function. +parallel processing. Indeed, by setting 3 cores for each of the parallel +processing tools, we reduced approximately by 3 times the computation time for +both computing a point estimation and evaluating the plausibility function. Finally, to return to a sequential plan with no progress updates, the following code can be used. ```{r, eval=FALSE} -future::plan(sequential) +future::plan(future::sequential) parallel::setDefaultCluster(NULL) progressr::handlers(global = FALSE) ```