The AXIOM software layers

AXIOM project aims at developing a heterogeneous computing board (SMP-FPGA).The Software Layers developed at the AXIOM project are explained.OmpSs provides an easy way to execute heterogeneous codes in multiple cores. People and objects will soon share the same digital network for information exchange in a world named as the age of the cyber-physical systems. The general expectation is that people and systems will interact in real-time. This poses pressure onto systems design to support increasing demands on computational power, while keeping a low power envelop. Additionally, modular scaling and easy programmability are also important to ensure these systems to become widespread. The whole set of expectations impose scientific and technological challenges that need to be properly addressed.The AXIOM project (Agile, eXtensible, fast I/O Module) will research new hardware/software architectures for cyber-physical systems to meet such expectations. The technical approach aims at solving fundamental problems to enable easy programmability of heterogeneous multi-core multi-board systems. AXIOM proposes the use of the task-based OmpSs programming model, leveraging low-level communication interfaces provided by the hardware. Modular scalability will be possible thanks to a fast interconnect embedded into each module. To this aim, an innovative ARM and FPGA-based board will be designed, with enhanced capabilities for interfacing with the physical world. Its effectiveness will be demonstrated with key scenarios such as Smart Video-Surveillance and Smart Living/Home (domotics).Peer ReviewedPostprint (author's final draft

Qduino: a cyber-physical programming platform for multicore Systems-on-Chip

Emerging multicore Systems-on-Chip are enabling new cyber-physical applications such as autonomous drones, driverless cars and smart manufacturing using web-connected 3D printers. Common to those applications is a communicating task pipeline, to acquire and process sensor data and produce outputs that control actuators. As a result, these applications usually have timing requirements for both individual tasks and task pipelines formed for sensor data processing and actuation. Current cyber-physical programming platforms, such as Arduino and embedded Linux with the POSIX interface do not allow application developers to specify those timing requirements. Moreover, none of them provide the programming interface to schedule tasks and map them to processor cores, while managing I/O in a predictable manner, on multicore hardware platforms. Hence, this thesis presents the Qduino programming platform. Qduino adopts the simplicity of the Arduino API, with additional support for real-time multithreaded sketches on multicore architectures. Qduino allows application developers to specify timing properties of individual tasks as well as task pipelines at the design stage. To this end, we propose a mathematical framework to derive each task’s budget and period from the specified end-to-end timing requirements. The second part of the thesis is motivated by the observation that at the center of these pipelines are tasks that typically require complex software support, such as sensor data fusion or image processing algorithms. These features are usually developed by many man-year engineering efforts and thus commonly seen on General-Purpose Operating Systems (GPOS). Therefore, in order to support modern, intelligent cyber-physical applications, we enhance the Qduino platform’s extensibility by taking advantage of the Quest-V virtualized partitioning kernel. The platform’s usability is demonstrated by building a novel web-connected 3D printer and a prototypical autonomous drone framework in Qduino

Concurrency Platforms for Real-Time and Cyber-Physical Systems

Parallel processing is an important way to satisfy the increasingly demanding computational needs of modern real-time and cyber-physical systems, but existing parallel computing technologies primarily emphasize high-throughput and average-case performance metrics, which are largely unsuitable for direct application to real-time, safety-critical contexts. This work contrasts two concurrency platforms designed to achieve predictable worst case parallel performance for soft real-time workloads with millisecond periods and higher. One of these is then the basis for the CyberMech platform, which enables parallel real-time computing for a novel yet representative application called Real-Time Hybrid Simulation (RTHS). RTHS combines demanding parallel real-time computation with real-time simulation and control in an earthquake engineering laboratory environment, and results concerning RTHS characterize a reasonably comprehensive survey of parallel real-time computing in the static context, where the size, shape, timing constraints, and computational requirements of workloads are fixed prior to system runtime. Collectively, these contributions constitute the first published implementations and evaluations of general-purpose concurrency platforms for real-time and cyber-physical systems, explore two fundamentally different design spaces for such systems, and successfully demonstrate the utility and tradeoffs of parallel computing for statically determined real-time and cyber-physical systems

Design and implementation of a container-based architecture for real-time control applications

The fourth industrial revolution and the advent of cyber-physical systems increase the flexibility and effectiveness in production, but they also change the role of software. Traditional monolithic systems need to split up in order to increase flexibility, maintainability and performance. There are existing approaches transforming traditional software towards a cloud-based infrastructure, but little work is done in applying this to real-time applications. This work proposes an architecture that uses containers to modularize real-time control applications, messaging for communication and a hardware abstraction layer to improve maintainability, reusability and flexibility. Using a prototypical implementation of the architecture, we validate the feasibility of this approach through a benchmark.Die vierte industrielle Revolution und die aufkommende Verbreitung von cyberphysikalischen Systemen (CPS) erhöht die Fliexibilität und Effektivität von Produktionsanlagen, ändert jedoch auch die Rolle der Software. Traditionelle monolitische Systeme müssen aufgesplittet werden, um die Flexibilität, Wartbarkeit und Performanz zu erhöhen. Es gibt bereits Ansätze, traditionelle Software in eine Cloud-basierte Infrastruktur zu transformieren, aber bisher gibt es wenige Arbeiten darüber, wie dies auf Echtzeitanwendungen übertragen werden kann. Diese Arbeit stellt eine Architektur vor, die Container verwendet, um Echtzeit-Steueranwendungen zu modularisieren, und außerdem Messaging zur Kommunikation und eine Hardware-Abstraktions-Schicht einsetzt, um Wartbarkeit, Wiederverwendbarkeit und Flexibilität verbessert. Mit einer prototypischen Implementierung der Architektur wird der Ansatz mit einem Benchmark evaluiert