rpds VS Taskflow

Thanks for taking the time to provide a detailed response. Need to think on this. I had actually started a regular Clojure parser using LLVM as a hobby, but then my friend said it was better to implement this in a safe-memory and. save-concurrency language like Rust and leverage cranelift for code generation. So, now I am learning rust, lol. (Btw, Rust has a persistent data structures lib too: https://github.com/orium/rpds )

Take a look at https://github.com/orium/rpds or one of the many others.

Cool. Thanks! How does it compare to taskflow?

I've not seen yet, but it's been a bit since I looked last, any evidence of being able to build a computation graph and "save" it to re-run on new inputs. Something like https://github.com/taskflow/taskflow

- https://github.com/taskflow/taskflow (I recommend to learn it first since its API and documentation are excellent)

If you want some sort of "job" system, where you submit items to a some sort of queue to be processed in parallel, try searching for a thread pool - there isn't one in the standard library, but there's about a million implementations online. There are more complicated versions of that idea, that describe computation as a directed acyclic graph, such as taskflow.

The tooling decisions affect engine design though. For example if you want to have visual representation of job graph as it happened in specific frame of interest you need to pass the information around about job relationships and output it to a tool of choice. For example see https://github.com/taskflow/taskflow

I am aware of DAGs of task based threading library like Taskflow and HPX however the benefit they have is not obvious to me, as the following sequential section depends on the parallel part being completed fully. If you want to suggest elaboration on the benefits of this approach would be welcome.

Users should work with higher level primitives like tasks, parallel loops, asynchronous functions etc. Think TBB, Thrust, Taskflow, lparallel for CL, etc.

taskflow