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Boosting Design Space Explorations with Existing or Automatically Learned Knowledge.

, , , and . MMB/DFT, volume 7201 of Lecture Notes in Computer Science, page 221-235. Springer, (2012)

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Improving Computing Systems Automatic Multiobjective Optimization Through Meta-Optimization., , , and . IEEE Trans. on CAD of Integrated Circuits and Systems, 35 (7): 1125-1129 (2016)Studying SVM Method's Scalability Using Text Documents., , and . Scalable Computing: Practice and Experience, (2008)Multi-objective optimisations for a superscalar architecture with selective value prediction., , , and . IET Computers & Digital Techniques, 6 (4): 205-213 (2012)Boosting Design Space Explorations with Existing or Automatically Learned Knowledge., , , and . MMB/DFT, volume 7201 of Lecture Notes in Computer Science, page 221-235. Springer, (2012)Finding near-perfect parameters for hardware and code optimizations with automatic multi-objective design space explorations., , , and . Concurrency and Computation: Practice and Experience, 27 (9): 2196-2214 (2015)Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping., , and . Microprocessors and Microsystems - Embedded Hardware Design, 37 (1): 65-78 (2013)Optimal Partitioning of LLC in CAT-enabled CPUs to Prevent Side-Channel Attacks., , , , and . CSS, volume 11161 of Lecture Notes in Computer Science, page 115-123. Springer, (2018)Aspects Concerning SVM Method's Scalability., , and . IDC, volume 78 of Studies in Computational Intelligence, page 125-134. Springer, (2007)Automatic multi-objective optimization of parameters for hardware and code optimizations., , , and . HPCS, page 308-316. IEEE, (2011)Performance and energy optimisation in CPUs through fuzzy knowledge representation., , , , and . Inf. Sci., (2019)