Quantization of the Jacobian matrix to speed up linear algebra operations

[pcarruscag]

Proposed Changes

Lossy compression of the Jacobian to make products and preconditioners faster.
Currently activated via a variant of LU-SGS preconditioner Q_LU_SGS, since it probably doesn't make sense to use this for ILU.
Only compatible with the primal compressible and incompressible solvers (disabled for adjoint mode). Other solvers fall back silently to regular LU-SGS.

For the CRM case I mentioned in the LDU PR, the 1.85s with normal LU-SGS become 1.66s in this branch (due to the change to clearing just the diagonal of the Jacobian instead of everything) and 1.36s with quantization.
So, a 50% speed-up between LDU, quantization, and other inefficiencies.

PR Checklist

• I am submitting my contribution to the develop branch.
• My contribution generates no new compiler warnings (try with --warnlevel=3 when using meson).
• My contribution is commented and consistent with SU2 style (https://su2code.github.io/docs_v7/Style-Guide/).
• I used the pre-commit hook to prevent dirty commits and used pre-commit run --all to format old commits.
• I have added a test case that demonstrates my contribution, if necessary.
• I have updated appropriate documentation (Tutorials, Docs Page, config_template.cpp), if necessary.