For a typical calibration, the parameters class object is not huge (~20MB), but if one were doing large scale parallelization (or running on a machine with low memory), this could cause issues.
I think we can reduce the footprint of this object without loosing much. A couple of ideas:
- Use the more efficient data types (e.g.
retirement_age can be cast as an integer, more floating point values would be fine with 32 bit (or even 16 bit).
- Most parameters become constant long before the steady state: is there a way to reduce the size of arrays knowing that after some point in the
T dimension, things stop changing?
For a typical calibration, the parameters class object is not huge (~20MB), but if one were doing large scale parallelization (or running on a machine with low memory), this could cause issues.
I think we can reduce the footprint of this object without loosing much. A couple of ideas:
retirement_agecan be cast as an integer, more floating point values would be fine with 32 bit (or even 16 bit).Tdimension, things stop changing?