> Parallelism in C++ is most often used for scientific applications and other forms of mass number crunching.
There are two aspects. I agree to the aspect that today, C++ is used often for such tasks.
Now, what are the reasons why C++ is used dominantly in this domain? I think more or less the only reason is performance. The good performance is what makes the authors of such libraries put up with the disadvantages of C++.
However, I think it is also true that Rust allows for a more concise and safe formulation of the computation (also Scala, for example, which serves somewhat different purposes). For scientific applications, correctness matters, and knowing that the code which compiles does not has hidden memory errors and data races is extremely valuable, because it can save a ton of time.
Also, if there are still differences between Rust and C++ performance, they are minor. In many cases, Rust is faster.
Now, if authors of scientific computing libraries were to come to the conclusion that there exist an alternative which produces at least as fast code, provides better and safer support for parallelization, and is with some learning easier to work with, why should these library authors continue to use C++?
Of course, nobody is going to ditch a large C++ project like Eigen over night and rewrite it in Rust. There is too much inertia for that. Also, GCC support is still lacking. However, one can expect that the number of new projects which use Rust is going to increase and the project which are successful there will blaze a new trail. For something like Python extension modules, users of these libraries do not need to know anything about Rust.
Also, some nitpick. C++ is used in important scientific libraries. However, many essential libraries such as Numpy are written either completely in C, or use C interfaces, because C++ does not has a stable ABI and Python uses the C ABI. This would make a switch to Rust pretty easy. In fact, I think the impulses in this domain will come first from researchers and analysts which start to write small Rust extension for Python which use the C ABI and integrate with Numpy, for example.