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Platforms that are based on heterogeneous architectures require an intelligent resource manager. An intelligent resource manager should be able to accurately predict the future workload of the system at hand and take it into consideration. In this paper, we show that there exist patterns in the interarrival times of resource requests, and that these patterns can be used for modeling and prediction...
Over the last 30 years, a number of secure processor architectures have been proposed to protect software integrity and confidentiality during its distribution and execution. In such architectures, encryption (together with integrity checking) is used extensively, on any data leaving a defined secure boundary.In this paper, we show how encryption can be achieved at the instruction level using a stream...
In this work, we present a modular software subsystem that exposes a set of APIs for supporting the automation of a set of design choices in the synthesis of a hardware accelerator by a proprietary FPGA toolchain. We model the subsystem around Vivado, Xilinx's proprietary FPGA toolchain, in order to provide a finer grained control on the toolchain's features with respect to the standard .tcl interface...
Matrix inversion for real-time applications can be a challenge for the designers since its computational complexity is typically cubic. Parallelism has been widely exploited to reduce such complexity, however most traditional methods do not scale well with the matrix size leading to communication bottlenecks. In this paper we exploit a decentralised parallel hardware architecture based on a strongly...
The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores different but interrelated mechanisms across the architecture...
Due to their flexibility and high performance, Coarse Grained Reconfigurable Array (CGRA) are a topic of increasing research interest. However, CGRAs also have the potential to achieve very high energy efficiency in comparison to other reconfigurable architectures when hardware optimizations are applied. Some of these optimizations are common for more traditional processors but can also lead to large...
The transition from conventional federated architectures to integrated architectures enables the integration of functionalities with different criticality with respect to safety, security and real-time on a single embedded computing platform. Mixed-criticality networks provide safe and predictable communication for functionalities with different criticality, offering benefits regarding spatial and...
The necessity to (re-)configure Internet of Things devices such as smart sensors during their entire lifecycle is becoming more important due to recent attacks targeting these devices. Allowing configuration parameters to be changed in any phase of a smart sensor's lifecycle allows security updates or new key material to be applied. Also, the functionality of a smart sensor can be altered by changing...
Power consumption and high compute density are the key factors to be considered when building a compute node for the upcoming Exascale revolution. Current architectural design and manufacturing technologies are not able to provide the requested level of density and power efficiency to realise an operational Exascale machine. A disruptive change in the hardware design and integration process is needed...
A major challenge for the European electronic industry is to enhance productivity while reducing costs and ensuring quality in development, integration and maintenance. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities but still need to scale to support real-world scenarios implied by the full deployment and use of complex electronic components and...
Geospatial data analytics is emerging as a promising technology in decision support systems in many application domains. This paper presents results from a study on the use of elastic cloud computing to provide geospatial data analytics in an efficient way. The analytics is applied to bulks of satellite data from multi-spectral optical sensors. The system design includes data integration, data caching,...
With its ability to detect, identify and, if applicable, recover from occurred faults, online-diagnosis can help achieving fault-tolerant systems. A sound decision on an occurred fault is the foundation for fault-specific recovery actions. For this, typically a large amount of data has to be analyzed and evaluated. A diagnostic process implemented on a distributed system needs to communicate all those...
Due to high accuracy, inherent redundancy, and embarrassingly parallel nature, the neural networks are fast becoming mainstream machine learning algorithms. However, these advantages come at the cost of high memory and processing requirements (that can be met by either GPUs, FPGAs or ASICs). For embedded systems, the requirements are particularly challenging because of stiff power and timing budgets...
Binary Edwards Curves (BEC) constitute an alternative to the standardized Weierstrass elliptic curve (EC) equations since the latter have intrinsic side channel attack vulnerabilities due to their lack of point operation uniformity. Thus, BECs have gained popularity over the past few years due to their uniformity, operation regularity, completeness and implementation attractiveness. However, BEC Scalar...
We present in this paper a security analysis of electronic devices which considers the lifecycle properties of embedded systems. We first define a generic model of electronic devices lifecycle showing the complex interactions between the numerous assets and the actors. The method is illustrated through a case study: a connected insulin pump. The lifecycle induced vulnerabilities are analyzed using...
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