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Cyber-Physical Systems (CPS) attempt to meet real-time and safety requirements through the use of hypervisors that provide isolation via virtualization and RTOS that manage the concurrency of various system tasks. These tasks encompass a wide spectrum of activities, including AI flows and resource-intensive computations. However, their efficiency is hindered by decisions made at the OS level, which often lacks awareness of their specific intricacies.
One of the key limitations to efficiently develop CPSs is the absence of parallel programming models tailored to harness the parallel capabilities of the most advanced processors. Conventional models like OpenMP and CUDA are not equipped to accommodate the non-functional properties that are integral to CPSs, such as real-time behavior and safety requirements. Consequently, there exists a significant gap in the availability of integrated computing frameworks capable of providing the mechanisms required for developing, deploying, and executing complex CPSs on parallel and heterogeneous platforms. These frameworks must be holistically designed, considering primary requirements in CPS like efficiency, interoperability, reliability and sustainability.
HiPART aims to develop a comprehensive framework that addresses the issues at hand, allowing complex CPS to operate efficiently on cutting-edge parallel and heterogeneous processor architectures. Through tailored support for real-time behavior, safety requirements, and the efficient exploitation of advanced parallel and heterogeneous processor architectures, we expect to bridge the existing gap and facilitate the efficient development, deployment, and execution of complex CPSs. This, in turn, will contribute to the realization of more capable and reliable autonomous systems across various domains, from autonomous mobility to space exploration.
This page is part of the project PID2023-148117NA-I00 finance MICIU/AEI /10.13039/501100011033 y por FEDER, UE.
Company Details
- Founded
- -
- Address
- Barcelona, Catalonia, Es
- Industry
- Technology, Information And Internet
- Keywords
- Barcelona.
- HQ
- Barcelona, Catalonia
Hipart Questions
HiPART's LinkedIn profile is https://es.linkedin.com/company/hipart
HiPART's industry is
Technology, Information and Internet
HiPART's top competitors are
Geotopsa, Sl,
Nimbleai.eu,
Inlab Fib,
Openmp Architecture Review Board,
Geokinesia,
Sparsity Technologies,
Lioness-Esa,
Barcelona Supercomputing Center,
Teledetect,
Hipeac.
HiPART's categories are Technology, Information and Internet
HiPART's founding year is 2024
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