We consider the problem of distributed computation of a target function over a
two-user deterministic multiple-access channel. If the target and channel
functions are matched (i.e., compute the same function), significant
performance gains can be obtained by jointly designing the communication and
computation tasks. However, in most situations there is mismatch between these
two functions.  In this work, we analyze the impact of this mismatch on the
performance gains achievable with joint communication and computation designs
over separation-based designs. We show that for most pairs of target and
channel
functions there is no such gain, and separation of communication and
computation
is optimal.