demo/quantile.spmd.r

In pbdPROF: Programming with Big Data -- MPI Profiling Tools

### This file implements SPMD parallel framework.
### No distinguish for manster or worker, and everyone does the same jobs.

### Load library.
library(pbdMPI, quietly = TRUE)
init()

### Generate data.
comm.set.seed(1234)
n <- 1000                                       # each owns 1000 samples
for(i.rank in 0:(comm.size() - 1)){
  X <- runif(n)
  if(i.rank == comm.rank()){
    break
  }
}

### Define quantile function in SPMD.
quantile.spmd <- function(x.gbd, prob = 0.5){
  if(sum(prob < 0 | prob > 1) > 0){
    stop("prob should be in (0, 1)")
  }

  ### Get information from everyone to everyone.
  N <- allreduce(length(x.gbd), op = "sum")   # global size
  x.min <- allreduce(min(x.gbd), op = "min")  # global leftest
  x.max <- allreduce(max(x.gbd), op = "max")  # global rightest

  f.quantile <- function(x, prob = 0.5){      # bisection
    n <- allreduce(sum(x.gbd <= x), op = "sum")
    n / N - prob
  }
  uniroot(f.quantile, c(x.min, x.max), prob = prob[1])$root
} # End of quantile.spmd().

### Run.
log.time <- system.time({
  q50.X <- replicate(50, quantile.spmd(X))
})
comm.print(q50.X[1])
comm.print(log.time)

### Finish.
finalize()