Feb. 4, 2021 BSC participates in the AI-SPRINTproject contributing its experience on the programming and parallelization of applications on distributed infrastructures. The work will be organized in two main contributions, the deployment ofCOMPSson the edge devices considered by the use cases and the implementation of the AI applications to be executed across distributed heterogeneous infrastructures (on premise, edge and public clouds). In particular,AI-SPRINTwill benefit from the recent developments on the adaptation ofCOMPSsfor Fog to Cloud platforms and will extend it to support the execution of serverless functions as a service.

On the other side,COMPSswill be adopted to develop AI and big data applications in support of the use cases also leveraging the recent enhancements to develop workflows that combine HPC compute engines with High Performance Data Analytics (HPDA) and machine learning methods. These ML implementations are available through thedislib librarythat is also part of theFujitsu-BSCcollaboration.

The technology developed within the project will be put to test by BSC on a personalized healthcare use case that will focus on privacy and security, much needed in healthcare scenarios since the information to be exchanged and processed involves medical data about patients.

More specifically, an automated system for personalized stroke risk assessment and prevention will be developed by using continuous, non-invasive monitoring of heart activity. The process will gather heart parameters collected from a wearable device, patients lifestyle information and biochemical blood indicators from a mobile application. All data will be anonymized, processed and used to train AI models cooperatively by local edge servers and cloud. At the same time, it will provide personalized notifications, alerts, and recommendations for stroke prevention.

AI-SPRINTdefines a novel framework for the design and operation of AI applications in computing continua leveraging theCOMPSsprogramming framework and supporting AI applications development by enabling the seamless design and partition of AI applications among the plethora of cloud-based solutions and AI-based sensor devices. Moreover it will generate impacts bringing together different European industrial end-users while and making available the software tools through a marketplace for AI start-ups, SMEs, system integrators, and European cloud providers statesDaniele Lezzi, Senior Researcher in theComputer Sciences department Workflows and Distributed Computingat BSC.

About COMPSs:

COMPSsis a task-based programming model known for notably improving the performance of large-scale applications by automatically parallelizing their execution. TheCOMPSsruntime has been recently extended within BSC projects:CLASSandELASTICto manage distribution, parallelism and heterogeneity in the edge resources transparently to the application programmer and to handle data regardless of persistency by supporting a single and unified data model.COMPSsis the base of the Design Tools of the project and it will support developers to easily compose AI/ML applications also leveraging the dislib library, helping end users to deal with big datasets on distributed resources and providing automatic parallelization of the code.

About Personalized Healthcare:

AI-SPRINTapplications will pave the way for an effective framework for personalized AI models preventing risks coupled with a lifestyle modificationmodification programmebenefiting people aged between 40 and 80, improving and extending human lives. The project addresses theUnited Nations strategic development goalsSDG3 (Good Health and Well Being) through the personalized healthcare pilot.

About AI-SPRINT

AI-SPRINTwill tackle the skill shortage and considerably reduce steep learning curves in the development of AI software on edge ecosystems through OSS (Operations Support System). The project addresses the followingUnited Nations strategic development goals(SDGs): SDG8 (Decent Work and Economic Growth) enabling novel AI applications running in computing continua, SDG9 (Industry, Innovation and Infrastructure) by fostering innovation in the maintenance and inspection use case and contributing OSS and SDG12 (Ensure sustainable consumption and production patterns) through farming 4.0 pilot.

For further information, visit AI-SPRINT website:https://www.ai-sprint-project.eu/

The AI-SPRINT project has received funding from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 101016577

Source: BSC

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BSC Working Towards Adoption of AI Applications to Capture Insights on Personalised Healthcare - HPCwire