In this volume, designed for computational scientists and engineers
working on applications requiring the memories and processing rates of
large-scale parallelism, leading algorithmicists survey their own
field-defining contributions, together with enough historical and
bibliographical perspective to permit working one's way to the
frontiers.
This book is distinguished from earlier surveys in parallel numerical
algorithms by its extension of coverage beyond core linear algebraic
methods into tools more directly associated with partial differential
and integral equations - though still with an appealing generality - and
by its focus on practical medium-granularity parallelism, approachable
through traditional programming languages.
Several of the authors used their invitation to participate as a chance
to stand back and create a unified overview, which nonspecialists will
appreciate.