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. The text contains extended coverage beyond core linear algebraic methods into tools more directly associated with partial differential and integral equations. There is a focus on practical medium-granularity parallelism, approachable through traditional programming languages.