Self-Aware Adaptation in FPGA-based Systems

Sironi, Filippo; Triverio, Marco; Hoffmann, Henry; Maggio, Martina; Santambrogio, Marco D.

doi:10.1109/fpl.2010.43

Cited by 25 publications

(14 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, additional operating system support will be added to enable a self-optimizing [Sironi et al 2010] behavior of the minirobot. Based on the current environmental conditions and on the available hardware resources, BeBot should, for example, be able to select the most appropriate implementation for a specific task.…”

Section: Resultsmentioning

confidence: 99%

Applying dynamic reconfiguration in the mobile robotics domain

Nava

Sciuto

Santambrogio

et al. 2011

ACM Trans. Reconfigurable Technol. Syst.

View full text Add to dashboard Cite

Mobile robots are widely used in industrial environments and are expected to be widely available in human environments in the near future, for example, in the area of care and service robots. This article proposes an implementation for a highly customizable color recognition module based on Field Programmable Gate Array (FPGA) hardware to accomplish tasks like real-time frame processing for image streams. In comparison to a pure software solution on a CPU, an attached FPGA-based hardware accelerator enables real-time image processing and significantly reduces the required computing power of the CPU. Instead, the CPU can be used for tasks that cannot be efficiently implemented on FPGAs, for example, because of a large control overhead. We concentrate on a multirobot scenario where a group of robots follows a human team member by keeping a specific formation in order to support the human in exploration and object detection. Additionally, the robots provide a communication infrastructure to maintain a stable multihop communication network between the human and a base station recording all actions and evaluating the captured images and transmitted data. Depending on the current operating conditions, the robot system has to be able to execute a wide variety of different tasks. Since only a small number of tasks have to be executed concurrently, dynamic reconfiguration of the FPGA can be used to avoid the parallel implementation of all tasks on the FPGA. Within this context, this article discusses application fields where dynamic reconfiguration of FPGA-based coprocessors significantly reduces the CPU load and presents examples of how dynamic reconfiguration can be used in exploration.

show abstract

Section: Resultsmentioning

confidence: 99%

Applying dynamic reconfiguration in the mobile robotics domain

Nava

Sciuto

Santambrogio

et al. 2011

ACM Trans. Reconfigurable Technol. Syst.

View full text Add to dashboard Cite

show abstract

“…Closely related to our work, Sironi et al [2010] presented an FPGA-based self-aware adaptive computing system based on heterogeneous multicores. Their system supports performance monitoring through the Heartbeats framework, decision making and selfadaption.…”

Section: Self-aware Computing Nodesmentioning

confidence: 99%

“…Using a hot-swap mechanism that switches between a software and a hardware implementation, all performance goals were met. In contrast to Sironi et al [2010], we provide actual measurements of a system that dynamically adapts the number of used hardware cores in order to meet performance constraints. Unlike Sironi et al [2011], we target an embedded architecture where the entire system is implemented on a single chip and, in addition to respecting performance constraints, our system can also respect thermal constraints.…”

Section: Self-aware Computing Nodesmentioning

confidence: 99%

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

Agne

Happe

Lösch

et al. 2014

ACM Trans. Reconfigurable Technol. Syst.

View full text Add to dashboard Cite

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.

show abstract

“…Work on developing adaptive system for FPGA technologies was discussed in [8], where a HW/SW adaptive DES encryption was used to demonstrate how the Heartbeats API can be used to develop an FPGA-based Self-Aware Adaptive computing system. In this paper a system known as an Implementation Switch Service (ISS) is used to migrate a task from software to hardware when the processing rate drops below a certain level.…”

Section: Related Workmentioning

confidence: 99%

Heterogeneous Heartbeats: A framework for dynamic management of Autonomous SoCs

Fleming

Thomas

2014

2014 24th International Conference on Field Programmable Logic and Applications (FPL)

View full text Add to dashboard Cite

Modern computer systems are formed from many interacting systems and heterogeneous components, that face increasing constraints on performance, power consumption, and temperature. Such systems have complex run-time dynamics which cannot easily be predicted or modelled at design-time, creating a need for online dynamic systems management. The Heartbeats API is a popular open source project which provides a standardised way for applications to monitor and publish their progress in multi-core CPU systems, but it does not allow hardware components to be monitored or to observe the progress of other components of the system. This paper presents work which extends the capacities of the Heartbeats API across the whole system while maintaining backwards compatibility with the legacy software API. To demonstrate the framework's capabilities an Autonomous Underwater Vehicle (AUV) case study is explored, where a power-aware HW/SW image processing application is implemented on a reconfigurable SoC and an approximate energy saving of 30% is observed for an example input video. Current progress is also discussed on some applications which build upon the framework, including an CubeSat experiment for an Adaptive Heterogeneous FDIR system that will launch in 2016 by the European Space Agency.

show abstract

Self-Aware Adaptation in FPGA-based Systems

Cited by 25 publications

References 16 publications

Applying dynamic reconfiguration in the mobile robotics domain

Applying dynamic reconfiguration in the mobile robotics domain

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

Heterogeneous Heartbeats: A framework for dynamic management of Autonomous SoCs

Contact Info

Product

Resources

About