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HIGH PERFORMANCE COMPUTING


 Modena is to host a demonstration of heavy sensor infrastructure to collect real-time data g


Each project is being developed with industrial partners and help from city infrastructure. The capabilities of the Class framework will be demonstrated on a real smart-city use case in Modena, Italy, featuring a heavy sensor infrastructure to collect real-time data across a wide urban area, and three connected vehicles equipped with heterogeneous sensors/ actuators and V2X connectivity to enhance the driving experience. The Elastic software architecture, designed to satisfy the performance requirements of extreme-scale analytics through a novel elasticity concept that distributes workloads across the compute continuum, will be tested in a smart mobility use case deployed in the metropolitan area of Florence. Specifically, Elastic will provide


the required scalable computing infrastructure to the Florence tramway network, enhancing the tramway public transportation services, as well as its interaction with private vehicle transportation. This ability opens the door to the use of big data into critical real-time systems, providing additional data analytics


14 Scientific Computing World Winter 2021


“Two different software architectures, but they are connected because one addresses the edge device, the other communication between multiple edge devices and the cloud”


capabilities to implement more intelligent and autonomous control applications. ‘We want to allow the development of a


workflow in which then we can define all of the analytics that are needed for a given set of data sources. In the case of smart cities, let’s assume that you have 100 cameras distributed across the city. You want to get all of this information, apply a set of different analytic steps to generate unique information that the city can then use,’ said Quiñones. ‘We want to describe the whole workflow as a unique problem, so the programmer only focuses on the functional part. My workflow is composed of a set of


data analytics that is connected. It is the underlying platform, the underlying software architecture that deploys all these analytics on the right computing node.’ This kind of project provides many challenges. This includes processing data across the compute continuum (from edge to cloud), predicting real-time responses, and employing a programming model that can mix different application program interfaces (APIs) and models.


Predicting accidents ‘In the Class project, for example, we want to leverage the information that is collected from vehicles. This would then be combined with information from the city. We are augmenting the sensing capabilities of both the vehicles and the city. This allows the vehicle to see what is called ‘behind the corner’. Of course, the vehicle needs this


information in a very short period of time,’ said Quiñones. ‘If this information is available to the vehicle in milliseconds, then the vehicle can start to use this information. Moreover, if information can be guaranteed, that transmission will occur in a given timeframe of, for example,100


@scwmagazine | www.scientific-computing.com


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