System-Level Implications of Disaggregated Memory
Source: University of Michigan
Recent research on memory disaggregation introduces a new architectural building block - the memory blade - as a cost-effective approach for memory capacity expansion and sharing for an ensemble of blade servers. Memory blades augment blade servers' local memory capacity with a second-level (remote) memory that can be dynamically apportioned among blades in response to changing capacity demand, albeit at a higher access latency. In this paper, the authors build on the prior research to explore the software and systems implications of disaggregated memory. They develop a software-based prototype by extending the Xen hypervisor to emulate a disaggregated memory design wherein remote pages are swapped into local memory on-demand upon access.