As an observation, performance optimized code is almost always effectively single-threaded these days, even when using all the cores on a CPU to very efficiently process workloads. Given this, it is not clear to me that Rust actually buys much when it comes to parallel programming for the purposes of performance. Is there another reason to focus on parallelism aside from performance?
This reminds me of when I use to write supercomputing codes. Lots of programming language nerds would wonder why we didn’t use functional models to simplify concurrency and parallelism. Our code was typically old school C++ (FORTRAN was already falling out of use). The truth was that 1) the software architecture was explicitly single-threaded — some of the first modern thread-per-core designs — to maximize performance, obviating any concerns about mutability and concurrency and 2) the primary performance bottlenecks tended to be memory bandwidth, of which functional programming paradigms tend to be relatively wasteful compared to something like C++. Consequently, C++ was actually simpler and higher performance for massively parallel computation, counterintuitively.
This reminds me of when I use to write supercomputing codes. Lots of programming language nerds would wonder why we didn’t use functional models to simplify concurrency and parallelism. Our code was typically old school C++ (FORTRAN was already falling out of use). The truth was that 1) the software architecture was explicitly single-threaded — some of the first modern thread-per-core designs — to maximize performance, obviating any concerns about mutability and concurrency and 2) the primary performance bottlenecks tended to be memory bandwidth, of which functional programming paradigms tend to be relatively wasteful compared to something like C++. Consequently, C++ was actually simpler and higher performance for massively parallel computation, counterintuitively.