Treffer: Array Processing using Mathematics of Arrays for a Unified Approach to Embedded Processing with Application to The Internet of Things

In the development and deployment of embedded digital signal processing functionality within edge devices for the Internet of Things, the key requirements are effective and efficient implementation of the data processing, data storage, and data communications operations. This is becoming a major consideration for designers who are now, for example, routinely embedding Machine Learning and Deep Learning functionality within deployed embedded systems. In the design of such systems, there is a sequence of steps to undertake and realize a concept through to deployment, with an integrated approach to hardware and software design required to maximize the role that the hardware and software parts take to fulfill the overall required system functionality. How the data processing and memory organisation is achieved will depend on the data processing algorithms to employ. In this paper, the embedding of data processing for data within multi-dimensional arrays is considered, and the processing of dense and sparse arrays is developed with different approaches to efficiently store and process data. This paper will utilize the Mathematics of Arrays (MoA) approach for data processing on both dense and sparse arrays using Python and C coding that can be deployed in both software and, with extension, as a hardware solution. The approach illustrated here on basic examples constitutes both a new family of target hardware for MoA-based programming and, a new formalized and mechanisable technique for implementing a large family of computations.