Getting Started with npRmpi

This vignette is intentionally conservative. The goal is to provide a package-side overview of the modern npRmpi workflow without making routine vignette builds depend on live MPI startup.

The full install matrix, platform-specific notes, and longer mode comparisons belong on the gallery site rather than in a shipped package vignette:

The main practical point is simple: on platforms where spawning is supported, the recommended interactive route is now session mode (the spawn code path), where the estimator calls look like ordinary np code once MPI has been initialized with npRmpi.init(nslaves = ...).

Which mode should I use?

Use session / spawn for ordinary interactive work on platforms where spawning is supported.
Use attach when the MPI world is already launched with mpiexec and you still want npRmpi.init(mode = "attach") to manage the worker loop.
Use profile / manual-broadcast mode when startup and broadcast logic need to be explicit, especially on larger or heterogeneous clusters.

For teaching and troubleshooting, it is usually better to be explicit than to rely on mode = "auto".

Recommended starting point: session mode

library(npRmpi)

npRmpi.init(nslaves = 1)

set.seed(1)
x <- runif(200)
y <- sin(2 * pi * x) + rnorm(200, sd = 0.2)

bw <- npregbw(y ~ x, regtype = "ll", bwmethod = "cv.ls")
fit <- npreg(bws = bw)
summary(fit)

npRmpi.quit()

The same joint polynomial-order and bandwidth selection route is also available here for local-polynomial-capable methods via search.engine = "nomad+powell", but this package-side vignette stays operational rather than methodological.

If you want the recommended route without spelling out all of the LP tuning arguments, use nomad = TRUE. This is a documented convenience preset, not a generic optimizer alias: it fills only missing LP degree-search controls and leaves compatible explicit overrides in place. This route uses the optional NOMAD backend provided by the suggested package crs, so install crs first if you want to use nomad = TRUE or search.engine = "nomad"/"nomad+powell".

if (requireNamespace("crs", quietly = TRUE) &&
    utils::packageVersion("crs") >= package_version("0.15-41")) {
  npRmpi.init(nslaves = 1)

  set.seed(7)
  n <- 120
  x <- runif(n, -1, 1)
  y <- x + 0.4 * x^2 + rnorm(n, sd = 0.18)

  fit_nomad <- npreg(y ~ x, nomad = TRUE, degree.max = 1L, nmulti = 1L)
  fit_nomad$bws$nomad.shortcut

  bw_nomad_only <- npregbw(
    y ~ x,
    nomad = TRUE,
    search.engine = "nomad",
    degree.max = 1L,
    nmulti = 1L
  )
  bw_nomad_only$nomad.shortcut

  npRmpi.quit()
}

The same convenience entry point is available for the other LP-capable families: npcdens, npcdist, npplreg, npscoef, and npindex, together with their corresponding *bw constructors.

On current package sources, spawn is not the Windows entry path. There the practical starting point is attach mode under mpiexec.

Attach mode

Use attach mode when the MPI world is already launched via mpiexec and you want npRmpi.init(mode = "attach") to be the startup entry point.

library(npRmpi)
npRmpi.init(mode = "attach")

if (mpi.comm.rank(0L) == 0L) {
  set.seed(1)
  x <- runif(200)
  y <- sin(2 * pi * x) + rnorm(200, sd = 0.2)

  bw <- npregbw(y ~ x, regtype = "ll", bwmethod = "cv.ls")
  fit <- npreg(bws = bw)
  summary(fit)

  npRmpi.quit(mode = "attach")
}

For attach mode, keep R_PROFILE_USER and R_PROFILE cleared at launch time. Profile startup belongs to a different mode and should not be mixed into attach launches.

Profile / manual-broadcast mode

Use profile mode when explicit startup and broadcast control are needed, especially on larger or heterogeneous clusters. In this route, npRmpi.init() is not the startup entry point; instead, ranks are launched with inst/Rprofile (or R_PROFILE_USER) and then initialized explicitly inside the script.

mpi.bcast.cmd(np.mpi.initialize(), caller.execute = TRUE)

set.seed(1)
x <- runif(200)
y <- sin(2 * pi * x) + rnorm(200, sd = 0.2)
dat <- data.frame(y, x)

mpi.bcast.Robj2slave(dat)
mpi.bcast.cmd(
  bw <- npregbw(y ~ x, regtype = "ll", bwmethod = "cv.ls", data = dat),
  caller.execute = TRUE
)
mpi.bcast.cmd(
  fit <- npreg(bws = bw, data = dat),
  caller.execute = TRUE
)

summary(fit)
mpi.bcast.cmd(mpi.quit(), caller.execute = TRUE)

For profile mode, use exactly one startup profile source via R_PROFILE_USER or a local .Rprofile, clear R_PROFILE, and avoid --vanilla.

Practical guidance