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Red Oak Consulting · Smarter HPC Decisions Start with Great People - Red Oak ConsultingBuying High-Performance Computing (HPC) infrastructure is not like picking out a new laptop. It is a strategic decision, one that can shape...
️![RStudio screenshot showing OpenMP-enabled R code with parallel processing functions like openmp_enabled() and openmp_limits(). The editor displays a timesTwo() function using OpenMP pragmas for parallel execution. The right panel shows macrtools documentation for OpenMP installation functions, with the console confirming OpenMP detection and showing results from querying OpenMP functions.
Code:
#include <Rcpp.h>
#ifdef _OPENMP
#include <omp.h>
#endif
// [[Rcpp::export]]
Rcpp::IntegerVector openmp_limits() {
Rcpp::IntegerVector limit_data(3, NA_INTEGER);
#ifdef _OPENMP
limit_data[0] = omp_get_num_procs();
limit_data[1] = omp_get_max_threads();
limit_data[2] = omp_get_thread_limit();
#endif
return limit_data;
}
// [[Rcpp::export]]
bool openmp_enabled() {
bool enabled = false;
#ifdef _OPENMP
enabled = true;
#endif
return enabled;
}
// [[Rcpp::export]]
std::vector<double> timesTwo(std::vector<double> x) {
#pragma omp parallel for
for (size_t i = 0; i < x.size(); ++i) {
x[i] *= 2;
}
return x ;
}
/*** R
openmp_enabled()
openmp_limits()
timesTwo(42)
*/](https://files.mastodon.social/media_attachments/files/114/997/924/231/481/606/original/ac7cdd2de0def7b6.png)
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️: Title: HPC Engineer
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OpenMP support in:
