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- Reghenzani F., Massari G., Fornaciari W., “The Real Time Linux Kernel: A Survey on PREEMPT_RT”, ACM Computing Surveys (CSUR), Volume 52, Issue 1, Article 18, Feb 2019
- Martino R., Cilardo A., “A Flexible Framework for Exploring, Evaluating, and Comparing SHA 2 Designs”, IEEE Access, Volume 7, pp. 72443 72456, May 30, 2019
- Reghenzani F., Massari G., Santinelli L., Fornaciari W., “Statistical power estimation dataset for external validation GoF tests on EVT distribution”, Data in Brief, Volume 25, August 2019
- M. Fusi,F. Mazzocchetti, A. Farres, L. Kosmidis, R. Canal, F.J. Cazorla, J. Abella, “On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems”, Mathematics 2020, 8(3), 314.
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- G. Agosta, W. Fornaciari, D. Atienza, R. Canal, A. Cilardo, J. Flich Cardo, C. Hernandez Luz, M. Kulczewski, G. Massari, R. Tornero Gavilá, M. Zapater, “The RECIPE approach to challenges in deeply heterogeneous high performance systems”, Microprocessors and Microsystems, Volume 77, 2020.
- R. Canal, C. Hernandez, R. Tornero, A. Cilardo, G. Massari, F. Reghenzani, W. Fornaciari, M. Zapater, D. Atienza, A. Oleksiak, W. Piatek, and J. Abella, “Predictive Reliability and Fault Management in Exascale Systems: State of the Art and Perspectives”, ACM Computing Surveys volume 53 issue 5 article 95, September, 2020.
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- Qureshi Y., et al., “Gem5 X: A gem5 based System Level Simulation Framework to Optimize Many Core Platforms ”, High Performance Computing Symposium. Spring Simulation Conference (SpringSim), April 2019 Best Runner Up Paper Award.
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- Reghenzani F., et al., “Probabilistic WCET Reliability: On the experimental validation of EVT hypotheses”, Proceeding of the International Conference on Omni Layer Intelligent Systems, pp. 229 234, May 2019
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- Reghenzani F., et al., “A Probabilistic Approach To Energy Constrained Mixed Criticality Systems”, 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), July 2019
- Massari G., et al., “Predictive Resource Management for Next-Generation High-Performance Computing Heterogeneous Platforms
”, Proceedings of International Conference on Embedded Computer Systems, July 2019
- Agosta G., et al., “Challenges in Deeply Heterogeneous High Performance Systems”, Proceedings of Euromicro Conference on Digital System Design (DSD), August 2019
- Iranfar , A., et al., “A Machine Learning Based Framework for Throughput Estimation of Time Varying Applications in Multi Core Servers”, IEEE Int. Conf. on Very Large Scale Integration (VLSI SoC), Oct 2019
- Pupykina A. and Agosta G., “Prediction based Partitions Evaluation Algorithm for Resource Allocation”, Proceedings of the 2019 Parallel Computing Conference (ParCo), 2019
- G. Agosta et al., “Challenges in Deeply Heterogeneous High Performance Systems”, 22nd Euromicro Conference on Digital System Design (DSD), Kallithea, Greece, pp. 428-435, 2019.
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