The talk describes algorithm engineering (AE) as a methodology for algorithmic research where design, analysis, implementation and experimental evaluation of algorithms form a feedback cycle driving the development of efficient algorithm. Additional important components of the methodology include realistic models, algorithm libraries, and collections of realistic benchmark instances. We use one main example throughout this paper: sorting huge data sets using many multi-core processors and disks. The described system broke records for the GraySort and MinuteSort sorting benchmarks and helped with the record for the JouleSort benchmark.