LabVIEW has another important advantage for making use of multicore CPUs: intuitive graphical representation of parallel code. While you can use traditional sequential languages to create parallel programs, keeping track of parallel operations can be an imposing challenge. Furthermore, because developers often work together to create large applications, decoding parallel code that you did not write can be even more difficult than decoding your own.
In contrast, the LabVIEW dataflow programming approach draws on one of the most basic forms of communication – the flowchart. For years, sequential programmers have been creating flowcharts to keep track of program elements and communicate with each other. Rather than translating flowcharts to sequential code and vice versa, you can implement ideas directly in graphical dataflow code. You also can quickly identify parallel code paths that can run on different processor cores.
LabVIEW graphical code intuitively represents the most common parallel programming patterns used in industry and academia. Some popular patterns include task parallelism, data parallelism, and pipelining.