Properly optimize Julia code

[JordiBolibar]

After some discussions in the Julia Discourse regarding Float64 vs Float32, some adjustments should be made to the code in order to avoid some performance pitfalls. Those are:

• Move all code back to Float64. Apparently, unless one is using GPUs, there's no benefit on that for CPUs.
• Use Int in exponents (e.g. in the flow law). See explanations in Discourse.
• Avoid memory allocation in util functions following example in iceflow_sandbox model.

[JordiBolibar]

Partially implemented in SIA!. There are still some operations remaining for which the pre-initialized size of the matrices needs to be adjusted. This is not urgent for the scientific applications, so to be updated later on.

This could be a good task for Lucille in her internship to optimize the SIA in a forward model.

[JordiBolibar]

More optimizations have been implemented. There are still quite a lot of memory allocations, though. Removing almost all of them would results in a relatively unreadable code, and it would imply passing even more initialized context matrices to SIA!().

To be discussed if it's worth it.

[JordiBolibar]

This still requires a bit more work. Once we have some time, we should perform a proper code optimization following this: https://viralinstruction.com/posts/optimise/.

Another really important optimization will come from making all parameters local, following #36