Seismic inversion and imaging are adjoint-based optimization problems that
processes up to terabytes of data, regularly exceeding the memory capacity of
available computers. Data compression is an effective strategy to reduce this
memory requirement by a certain factor, particularly if some loss in accuracy
is acceptable. A popular alternative is checkpointing, where data is stored at
selected points in time, and values at other times are recomputed as needed
from the last stored state. This allows arbitrarily large adjoint computations
with limited memory, at the cost of additional recomputations. In this paper we
combine compression and checkpointing for the first time to compute a realistic
seismic inversion. The combination of checkpointing and compression allows
larger adjoint computations compared to using only compression, and reduces the
recomputation overhead significantly compared to using only checkpointing.