Parallel processing can make better use of the system resources and thus increase efficiency. It is used to deal with data-intensive or computation-intensive analysis. This chapter explains how to perform parallel computing in esProc.
Parallel computing solves a computational problem by breaking it apart into discrete subtasks and distributing them among multiple servers on which they will be implemented concurrently. Each subtask returns its own computational result to the master task for summarization. Through the simultaneous use of multiple compute resources, parallel computing can effectively enhance the computational speed and the data processing ability.