  Pipelined Krylov subspace methods avoid communication latency by reducing the
number of global synchronization bottlenecks and by hiding global communication
behind useful computational work. In exact arithmetic pipelined Krylov subspace
algorithms are equivalent to classic Krylov subspace methods and generate
identical series of iterates. However, as a consequence of the reformulation of
the algorithm to improve parallelism, pipelined methods may suffer from
severely reduced attainable accuracy in a practical finite precision setting.
This work presents a numerical stability analysis that describes and quantifies
the impact of local rounding error propagation on the maximal attainable
accuracy of the multi-term recurrences in the preconditioned pipelined BiCGStab
method. Theoretical expressions for the gaps between the true and computed
residual as well as other auxiliary variables used in the algorithm are
derived, and the elementary dependencies between the gaps on the various
recursively computed vector variables are analyzed. The norms of the
corresponding propagation matrices and vectors provide insights in the possible
amplification of local rounding errors throughout the algorithm. Stability of
the pipelined BiCGStab method is compared numerically to that of pipelined CG
on a symmetric benchmark problem. Furthermore, numerical evidence supporting
the effectiveness of employing a residual replacement type strategy to improve
the maximal attainable accuracy for the pipelined BiCGStab method is provided.
