Cross-Languages Visual Programming with Automated Multitasking Management

Abstract

In computer architecture, the Moore’s law says that the number of transistors inside a ship double every year duos increasing the performance of machines by having more computational power [Tar]. The theory was a valid path to follow since it’s first posited in 1965. However, by building smaller and smaller transistors, manufacturers are about to reach the transistors limit before some quantum phenomenon such as quantum tunneling which make them irrelevant [Pow], limiting the possibility of doubling the size of a chip and pushing the manufacturers to search for other designs and software solutions. An escape-route was to provide multiple cores inside a ship that enable multiple processes which in turn can run multiple threads. This approach can indeed offer more computational power but it can be difficult for software engineers to manage the resources shared between all of these units and threads. In this project we try to offer a solution to this problem by offering a cross-language visual programming tool in python that detect shared resources and reduce their complexity.