checkpoint_schedules: schedules for incremental checkpointing of adjoint simulations

checkpoint_schedules provides schedules for step-based incremental checkpointing of the adjoints to computer models. The schedules contain instructions indicating the sequence of forward and adjoint steps to be executed, and the data storage and retrieval to be performed.
These instructions are independent of the model implementation, which enables the model authors to switch between checkpointing algorithms without recoding. Conversely, checkpointing_schedules provides developers of checkpointing algorithms a direct mechanism to convey their work to model authors. checkpointing_schedules has been integrated into tlm_adjoint (James R. Maddison et al., 2019), a Python library designed for the automated derivation
of higher-order tangent-linear and adjoint models and work is ongoing to integrate it with pyadjoint (Mitusch et al., 2019). This package can be incorporated into other gradient solvers based on adjoint methods, regardless of the specific approach taken to generate the adjoint model.