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Architectural support for convolutional neural networks on modern CPUs., , , , и . PACT, стр. 16:1-16:13. ACM, (2018)AREP: Adaptive Resource Efficient Prefetching for Maximizing Multicore Performance., , , , и . PACT, стр. 367-378. IEEE Computer Society, (2015)Continuous shape shifting: Enabling loop co-optimization via near-free dynamic code rewriting., , , и . MICRO, стр. 23:1-23:12. IEEE Computer Society, (2016)SMiTe: Precise QoS Prediction on Real-System SMT Processors to Improve Utilization in Warehouse Scale Computers., , , и . MICRO, стр. 406-418. IEEE Computer Society, (2014)Adrenaline: Pinpointing and reining in tail queries with quick voltage boosting., , , , , , , и . HPCA, стр. 271-282. IEEE Computer Society, (2015)Input responsiveness: using canary inputs to dynamically steer approximation., , , , , и . PLDI, стр. 161-176. ACM, (2016)CrystalBall: Statically analyzing runtime behavior via deep sequence learning., , , , , и . MICRO, стр. 24:1-24:12. IEEE Computer Society, (2016)Proctor: Detecting and Investigating Interference in Shared Datacenters., , , , и . ISPASS, стр. 76-86. IEEE Computer Society, (2018)Outlier Detection for Improved Data Quality and Diversity in Dialog Systems., , , , , , , , и . NAACL-HLT (1), стр. 517-527. Association for Computational Linguistics, (2019)Octopus-Man: QoS-driven task management for heterogeneous multicores in warehouse-scale computers., , , , , , и . HPCA, стр. 246-258. IEEE Computer Society, (2015)