Self-Awareness as a Model for Designing and Operating Heterogeneous Multicores

Abstract

Self-aware computing is a paradigm for structuring and simplifying the design and operation of computing systems that face unprecedented levels of system dynamics and thus require novel forms of adaptivity. The generality of the paradigm makes it applicable to many types of computing systems and, previously, researchers started to introduce concepts of self-awareness to multicore architectures. In our work we build on a recent reference architectural framework as a model for self-aware computing and instantiate it for an FPGA-based heterogeneous multicore running the ReconOS reconfigurable architecture and operating system. After presenting the model for self-aware computing and ReconOS, we demonstrate with a case study how a multicore application built on the principle of self-awareness, autonomously adapts to changes in the workload and system state. Our work shows that the reference architectural framework as a model for self-aware computing can be practically applied and allows us to structure and simplify the design process, which is essential for designing complex future computing systems. ACM Reference Format:Andreas Agne, Markus Happe, Achim Lösch, Christian Plessl, and Marco Platzner. 2014. Self-awareness as a model for designing and operating heterogeneous multicores.

Self-aware computing systems: From psychology to engineering

“…The aim of this project was to take inspiration from self-awareness theories in psychology, to develop new methodologies for the engineering of complex computing systems. A range of different case studies were used in developing the framework and reference architecture, case studies which are concerned with both the platform level (e.g., [47]) and the application level (e.g., [48]). How these relate to the EPiCS vision was laid out in a summary paper [49], and the culmination of the project's results are documented in a 2015 book [50].…”

An Architecture for Self -Aware IOT Applications

“…In recent years, self-aware computing has received a lot of attention in embedded and multi-core systems [4,5,6,7] but also other application areas such as surveillance and security [8,9,10,11], IoT [12], cloud and data centres [13,14,15], automotive systems [16], as well as robotic and space applications [17,18] have been investigated. In the vast majority, SA has mainly focussed on individual nodes and their local objectives rather than the collaborating collective and their common, network-wide goals.…”