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Workload-Aware DRAM Error Prediction using Machine Learning., , , , and . IISWC, page 106-118. IEEE, (2019)Measuring and Exploiting Guardbands of Server-Grade ARMv8 CPU Cores and DRAMs., , , , , , , , , and 2 other author(s). DSN Workshops, page 6-9. IEEE Computer Society, (2018)Characterization of HPC workloads on an ARMv8 based server under relaxed DRAM refresh and thermal stress., , , and . SAMOS, page 230-235. ACM, (2018)Access-aware DRAM failure-rate estimation under relaxed refresh operations., , and . SAMOS, page 292-299. IEEE, (2017)Concurrent GCs and Modern Java Workloads: A Cache Perspective., , , , and . ISMM, page 71-84. ACM, (2023)HaRMony: Heterogeneous-Reliability Memory and QoS-Aware Energy Management on Virtualized Servers., , , and . ASPLOS, page 575-590. ACM, (2020)ASPLOS 2020 was canceled because of COVID-19..DRAM Characterization under Relaxed Refresh Period Considering System Level Effects within a Commodity Server., , , and . IOLTS, page 236-239. IEEE, (2018)Relaxing DRAM refresh rate through access pattern scheduling: A case study on stencil-based algorithms., , and . IOLTS, page 45-50. IEEE, (2017)Workload-Aware DRAM Error Prediction using Machine Learning., , , , and . CoRR, (2020)An energy-efficient and error-resilient server ecosystem exceeding conservative scaling limits., , , , , , , , , and 16 other author(s). DATE, page 1099-1104. IEEE, (2018)