The example you cited appears to be generating random Householder vectors and multiplying them out using backwards accumulation.
Another simple thing to do would be to generate a random matrix $\mathbf A$, then compute its $\mathbf A=\mathbf Q \mathbf R$ decomposition and discard the $\mathbf R$ factor. The two LAPACK functions that you need are [geqrf] (to ...
I agree with Wolfgang's comment that the fundamentals are the same.
Nonetheless there are quite a few things that have changed since 2001 and it's a common refrain that C++ is growing very fast, with even some experts saying they can barely keep up.
There are two that I think are especially important:
Smart pointer types like unique pointers have made it ...
C++ is a general purpose programming language, and consequently the improvements that are made in successive standards are, by and large, not particularly geared towards scientific computing but to the general ease of programming complex software.
That said, there are a few features that I can see as quite useful in scientific software:
For a variety of ...
Feature test macros: HPC is generally stuck on old compilers or compilers with partially conformant implementations. This can help ease the pain of working on the custom architectures common in HPC. Example:
auto sl = std::source_location();
std::cerr << "Error at line ...