Paradigms for optimal sorting with multiple disks

The authors present several balancing paradigms pertinent to optimizing input/output performance with disk and processor parallelism. They use sorting as the canonical application to illustrate the paradigms. The use of parallel disks can help overcome the I/O bottleneck in sorting if the records in each read or write are evenly balanced among the disks. There are three known record-balancing paradigms that lead to optimal I/O algorithms: using randomness to assign blocks to disks, using the disks predominantly independently, and deterministically balancing the blocks by matching. The authors describe all of these techniques and compare their relative advantages. It is also shown that randomized and deterministic balancing can be extended to provide algorithms that are optimal both in terms of the number of I/Os and the internal processing time for parallel-processing machines with scalable I/O subsystems and parallel memory hierarchies.