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Titlebook: Euro-Par 2023: Parallel Processing Workshops; Euro-Par 2023 Intern Demetris Zeinalipour,Dora Blanco Heras,Pierangelo Conference proceeding

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GPPRMon: GPU Runtime Memory Performance and Power Monitoring Toolllection and offers useful visualization views to track power and performance optimizations. Our simulation-based framework dynamically collects microarchitectural metrics by monitoring individual instructions and reports achieved performance and power consumption information at runtime. Our visuali
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Towards Resource-Efficient DNN Deployment for Traffic Object Recognition: From Edge to Fogesource utilization, and viability of both edge-only and edge-fog based approaches. Moreover, the experimental results showcased the adaptability of the system to dynamic traffic scenarios, thus ensuring real-time recognition performance even in challenging environments.
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Malleable APGAS Programs and Their Support in Batch Job Schedulersr efficient malleability. In this paper, we propose an extension to an existing AMT system, namely ., that provides easy-to-use malleability. More specifically, programmers enable application malleability with only minimal code additions, thanks to the simple abstractions we provide. Runtime adjustm
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Making Uintah Performance Portable for Department of Energy Exascale Testbedsends. This paper also describes notable updates to Uintah’s support for Kokkos, which were required to make this extension possible. Results are shown for a challenging radiative heat transfer calculation, central to the University of Utah’s predictive boiler simulations. These results demonstrate s
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Online Job Failure Prediction in an HPC Systemation of these algorithms with Natural Language Processing (NLP) tools to represent jobs and (ii) the design of the approach to work in an online fashion in a real system. The study is based on a dataset extracted from a production machine hosted at the HPC centre CINECA in Italy. Experimental resul
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