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Energy Prediction of OpenMP Applications Using Random Forest Modeling Approach., , , , and . IPDPS Workshops, page 1251-1260. IEEE Computer Society, (2015)On the Quality of Implementation of the C++11 Thread Support Library., , and . PDP, page 94-98. IEEE Computer Society, (2015)Multi-Objective Auto-Tuning with Insieme: Optimization and Trade-Off Analysis for Time, Energy and Resource Usage., , and . Euro-Par, volume 8632 of Lecture Notes in Computer Science, page 87-98. Springer, (2014)Porting Real-World Applications to GPU Clusters: A Celerity and Cronos Case Study., , , , , , and . e-Science, page 90-98. IEEE, (2021)The AllScale API., , , and . eScience, page 488-497. IEEE, (2019)Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach., , , , , , , , , and 24 other author(s). CF, page 272-278. ACM, (2023)A Region-Aware Multi-Objective Auto-Tuner for Parallel Programs., , , and . ICPP Workshops, page 190-199. IEEE Computer Society, (2017)A multi-objective auto-tuning framework for parallel codes., , , , , , and . SC, page 10. IEEE/ACM, (2012)Performance Analysis and Benchmarking of the Intel SCC., , and . CLUSTER, page 139-149. IEEE Computer Society, (2011)Exploring the semantic gap in compiling embedded DSLs., , , , and . SAMOS, page 195-201. ACM, (2018)