Add support for async T_exp! and T_lim!

[charleskawczynski]

We can compute T_exp! and T_lim! asynchronously to improve performance. #229 does this using @async, but Simon mentioned that this is perhaps not the best option and there is a warning about @async in the Julia docs:

  │ Warning
  │
  │  It is strongly encouraged to favor Threads.@spawn over @async always even when no parallelism is required especially in publicly distributed
  │  libraries. This is because a use of @async disables the migration of the parent task across worker threads in the current implementation of Julia.
  │  Thus, seemingly innocent use of @async in a library function can have a large impact on the performance of very different parts of user applications.

Tim Besard discusses this in https://www.youtube.com/watch?v=fw0R5G8pB0U. I'm going to have a second look at this to see what's the right way to leverage parallelism/concurrency, since we'll probably want similar or the same solution in #233.

[charleskawczynski]

We're going to fuse these function instead, so that we can reduce the number of DSS calls.