  We revisit existing linear computation coding (LCC) algorithms, and introduce
a new framework that measures the computational cost of computing
multidimensional linear functions, not only in terms of the number of
additions, but also with respect to their suitability for parallel processing.
Utilizing directed acyclic graphs, which correspond to signal flow graphs in
hardware, we propose a novel LCC algorithm that controls the trade-off between
the total number of operations and their parallel executability. Numerical
evaluations show that the proposed algorithm, constrained to a fully parallel
structure, outperforms existing schemes.
