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Design of self-adaptable data parallel applications on multicore clusters automatically optimized for performance and energy through load distribution., и . Concurr. Comput. Pract. Exp., (2019)Parallel Data Partitioning Algorithms for Optimization of Data-Parallel Applications on Modern Extreme-Scale Multicore Platforms for Performance and Energy., и . IEEE Access, (2018)Improving the accuracy of energy predictive models for multicore CPUs by combining utilization and performance events model variables., , , и . J. Parallel Distributed Comput., (2021)SummaGen: Parallel Matrix-Matrix Multiplication Based on Non-rectangular Partitions for Heterogeneous HPC Platforms., , , и . IPDPS Workshops, стр. 57-68. IEEE, (2019)Scalable Dense Factorizations for Heterogeneous Computational Clusters., , и . ISPDC, стр. 49-56. IEEE Computer Society, (2008)Energy aware ultrascale systems., , , , , , , , , и 9 other автор(ы). Ultrascale Computing Systems, IET, (2019)Improving the Accuracy of Energy Predictive Models for Multicore CPUs Using Additivity of Performance Monitoring Counters., , , и . PaCT, том 11657 из Lecture Notes in Computer Science, стр. 51-66. Springer, (2019)A Hierarchical Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous Multi-Accelerator NUMA Nodes., , и . IEEE Access, (2020)Modern Multicore CPUs are not Energy Proportional: Opportunity for Bi-objective Optimization for Performance and Energy., , и . CoRR, (2019)A Novel Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms., , и . IEEE Trans. Parallel Distributed Syst., 29 (10): 2176-2190 (2018)