The paper deals with the efficient parallelization of
least-squares spectral element methods for incompressible flows.
The parallelization of this sort of problems requires two different
strategies. On the one hand, the spectral element discretization benefits
from an element-by-element parallelization strategy. On the other hand,
an efficient strategy to solve the large sparse global systems benefits
from a row-wise distribution of data. This requires two different
kinds of data distributions and the conversion between them
is rather complicated. In the present paper, the different
strategies together with its conversion are discussed. Moreover, some
results obtained on a distributed memory machine (Cray T3E) are presented
