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The memory capacity of computers and edge devices continue to grow: the DRAM capacity for low end computers are at tens or hundreds of GBs and the modern high performance computing (HPC) platforms can support terabytes of RAM for Big data driven HPC and Machine Learning (ML) workloads. Although system virtualization improves resource consolidation, it does not tackle the increasing cost of address translation and the growing size of page tables OS kernel maintains. All virtual machines and processors use pages tables for address translation. On the other hand, Big data and latency-demanding applications are typically deployed in virtualized Clouds using the application deployment models, comprised of virtual machines (VMs), containers, and/or executors/JVMs. These applications enjoy high throughput and low latency if they are served entirely from memory. However, actual estimation and …