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NeurOPar, A Neural Network-Driven EDP Optimization Strategy for Parallel Workloads.

, , , , , and . SBAC-PAD, page 170-180. IEEE, (2023)

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On the influence of static power consumption in multicore embedded systems., , and . ISCAS, page 1374-1377. IEEE, (2015)The Impact of Turbo Frequency on the Energy, Performance, and Aging of Parallel Applications., , , , , , and . VLSI-SoC, page 149-154. IEEE, (2019)Decreasing the Learning Cost of Offline Parallel Application Optimization Strategies., , , , and . PDP, page 144-151. IEEE, (2020)Automatic Tuning TLP and DVFS for EDP with a Non-intrusive Genetic Algorithm Framework., , and . SBESC, page 146-153. IEEE, (2018)Exploiting Idle Hardware to Provide Low Overhead Fault Tolerance for VLIW Processors., , , , , and . JETC, 13 (2): 13:1-13:21 (2016)Aurora: seamless optimization of openMP applications.. Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, (2018)ndltd.org (oai:lume56.ufrgs.br:10183/179828).Analysing the Impact of MPI-2 Dynamic Process Creation to the Game of Life Problem., , and . WSCAD-SSC, page 133-140. IEEE Computer Society, (2012)Latency-Aware Cost-Efficient Provisioning of Composite Applications in Multi-Provider Clouds., , , , , , and . CLOSER, page 297-305. SCITEPRESS, (2023)Optimizing Parallel Applications via Dynamic Concurrency Throttling and Turbo Boosting., , , , , , , and . PDP, page 153-160. IEEE, (2021)LAANT: A library to automatically optimize EDP for OpenMP applications., , and . DATE, page 1229-1232. IEEE, (2017)