# A first example of using Boost

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Boost is, to quote the quote by Sutter and Alexandrescu which adornes the Boost website, *…one of the most highly regarded and expertly designed C++ library projects in the world*.

The impact of Boost on C++ cannot be overstated. Boost is, at its core, a collection of thoroughly designed and peer-reviewed libraries. Some of these have been included into the new C++11 standard (see our intro post on C++11) as for example lambda functions which we illustrated in another post on C++11.

Boost is mostly implemented using templates. That means headers files only, and compile-time – but not linking. Which is perfect for example posts like these.

Many, many Boost libraries are useful, and we could fill a series of posts. Here, as an introduction, we going to use two simple functions from the Boost.Math library to compute greatest common denominator and least common multiple.

I should note that I write this post on a machine with Boost headers in a standard system location. *So stuff just works.* If you have to install Boost from source, and into a non-standard location, you may need to add a `-I`

flag, not unlike how added the C++11 flag in this post .

#include#include // one file, automatically found here using namespace Rcpp; // [[Rcpp::export]] int computeGCD(int a, int b) { return boost::math::gcd(a, b); } // [[Rcpp::export]] int computeLCM(int a, int b) { return boost::math::lcm(a, b); }

We can test these:

a <- 6 b <- 15 cat( c(computeGCD(a,b), computeLCM(a,b)), "\n") 3 30 a <- 96 b <- 484 cat( c(computeGCD(a,b), computeLCM(a,b)), "\n") 4 11616

And as kindly suggested and submitted by Kohske Takahashi, we can also benchmark this against an R solution using the numbers package:

library(rbenchmark) library(numbers) a <- 962 b <- 4842 res <- benchmark(r1 = c(computeGCD(a,b), computeLCM(a,b)), r2 = c(GCD(a,b), LCM(a,b)), replications = 5000) print(res[,1:4]) test replications elapsed relative 1 r1 5000 0.054 1.000 2 r2 5000 0.421 7.796

This shows a nice performance gain.

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