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Per-task Energy Accounting in Computing Systems., , , , , and . IEEE Comput. Archit. Lett., 13 (2): 85-88 (2014)DReAM: An Approach to Estimate per-Task DRAM Energy in Multicore Systems., , , , and . ACM Trans. Design Autom. Electr. Syst., 22 (1): 16:1-16:26 (2016)MEST: A Model-Driven Efficient Searching Approach for MapReduce Self-Tuning., , , , , and . IEEE Access, (2017)The Elasticity and Plasticity in Semi-Containerized Co-locating Cloud Workload: a View from Alibaba Trace., and . SoCC, page 347-360. ACM, (2018)An Experimental Comparison Between Genetic Algorithm and Particle Swarm Optimization in Spark Performance Tuning., , , and . ETCD@ASPLOS, page 1:1-1:6. ACM, (2017)Per-task energy metering and accounting in the multicore era.. Polytechnic University of Catalonia, Spain, (2016)Hardware support for accurate per-task energy metering in multicore systems., , , , , and . ACM Trans. Archit. Code Optim., 10 (4): 34:1-34:27 (2013)Sensible Energy Accounting with Abstract Metering for Multicore Systems., , , , , and . ACM Trans. Archit. Code Optim., 12 (4): 60:1-60:26 (2016)SEDEA: A Sensible Approach to Account DRAM Energy in Multicore Systems., , , , and . SBAC-PAD, page 73-80. IEEE Computer Society, (2017)DReAM: Per-Task DRAM Energy Metering in Multicore Systems., , , , and . Euro-Par, volume 8632 of Lecture Notes in Computer Science, page 111-123. Springer, (2014)