Composable Virtual Memory for an Embedded SoC

Systems on a Chip concurrently execute multiple applications that may start and stop at run-time, creating many use-cases. Composability reduces the verifcation effort, by making the functional and temporal behaviours of an application independent of other applications. Existing approaches link applications to static address ranges that cannot be reused between applications that are not simultaneously active, wasting resources. In this paper we propose a composable virtual memory scheme that enables dynamic binding and relocation of applications. Our virtual memory is also predictable, for applications with real-time constraints. We integrated the virtual memory on, CompSOC, an existing composable SoC prototyped in FPGA. The implementation indicates that virtual memory is in general expensive, because it incurs a performance loss around 39% due to address translation latency. On top of this, composability adds to virtual memory an insigni cant extra performance penalty, below 1%

Run-time middleware to support real-time system scenarios

Abstract—Systems on Chip (SOC) are powerful multipro-cessor systems capable of running multiple independent applica-tions, often with both real-time and non-real-time requirements. Scenarios exist at two levels: first, combinations of independent applications, and second, different states of a single application. Scenarios are dynamic since applications can be started and stopped independently, and a single application’s behaviour can depend on its inputs, on different stages in processing, and so on. In this paper we describe how the CompSOC platform offers system integrators and application writers the capability to implement multiple scenarios. I

Integration and validation of embedded flight software on space-qualified multicore architectures

In the recent decades, the importance of software on space missions has notably increased, reflecting the need to integrate advanced on-board functionalities. With multicore processors being lately introduced to host critical high-performance applications, the complexity to validate software has significantly raised with respect to single core architectures. While there has been a big step forward in avionics after the publication of the CAST-32A paper, the ECSS-E-ST-40C software engineering standard used by the European Space Agency (ESA) is still not providing validation support for multicore processors. Hence, it is expected that standardising guidelines to develop software on such platforms will become a recurring topic in the industry to match the demands of future space exploration missions

A Survey of Timing Verification Techniques for Multi-Core Real-Time Systems

This survey provides an overview of the scientific literature on timing verification techniques for multi-core real-time systems. It reviews the key results in the field from its origins around 2006 to the latest research published up to the end of 2018. The survey highlights the key issues involved in providing guarantees of timing correctness for multi-core systems. A detailed review is provided covering four main categories: full integration, temporal isolation, integrating interference effects into schedulability analysis, and mapping and allocation. The survey concludes with a discussion of the advantages and disadvantages of these different approaches, identifying open issues, key challenges, and possible directions for future research

A Scenario-Aware Dataflow Programming Model

The FSM-SADF model of computation allows to find a tight bound on the throughput of firm real-time applications by capturing dynamic variations in scenarios. We explore an FSM-SADF programming model, and propose three different alternatives for scenario switching. The best candidate for our CompSOC platform was implemented, and experiments confirm that the tight throughput bound results in a reduced resource budget. This comes at the cost of a predictable overhead at run-time as well as increased communication and memory budgets. We show that design choices offer interesting trade-offs between run-time cost and resource budgets

Design and management of image processing pipelines within CPS : Acquired experience towards the end of the FitOptiVis ECSEL Project

Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.Peer reviewe

Predictable embedded multiprocessor architecture for streaming applications

The focus of this thesis is on embedded media systems that execute applications from the application domain car infotainment. These applications, which we refer to as jobs, typically fall in the class of streaming, i.e. they process on a stream of data. The jobs are executed on heterogeneous multiprocessor platforms, for performance and power efficiency reasons. Most of these jobs have firm real-time requirements, like throughput and end-to-end latency. Car-infotainment systems become increasingly more complex, due to an increase in the supported number of jobs and an increase of resource sharing. Therefore, it is hard to verify, for each job, that the realtime requirements are satisfied. To reduce the verification effort, we elaborate on an architecture for a predictable system from which we can verify, at design time, that the job’s throughput and end-to-end latency requirements are satisfied. This thesis introduces a network-based multiprocessor system that is predictable. This is achieved by starting with an architecture where processors have private local memories and execute tasks in a static order, so that the uncertainty in the temporal behaviour is minimised. As an interconnect, we use a network that supports guaranteed communication services so that it is guaranteed that data is delivered in time. The architecture is extended with shared local memories, run-time scheduling of tasks, and a memory hierarchy. Dataflow modelling and analysis techniques are used for verification, because they allow cyclic data dependencies that influence the job’s performance. Shown is how to construct a dataflow model from a job that is mapped onto our predictable multiprocessor platforms. This dataflow model takes into account: computation of tasks, communication between tasks, buffer capacities, and scheduling of shared resources. The job’s throughput and end-to-end latency bounds are derived from a self-timed execution of the dataflow graph, by making use of existing dataflow-analysis techniques. It is shown that the derived bounds are tight, e.g. for our channel equaliser job, the accuracy of the derived throughput bound is within 10.1%. Furthermore, it is shown that the dataflow modelling and analysis techniques can be used despite the use of shared memories, run-time scheduling of tasks, and caches