Disaggregated memory for expansion and sharing in blade servers
Proceedings of the 36th annual international symposium on Computer architecture
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There is a constant battle to break-even between continuing improvements in DRAM capacities and the demands for even more memory by modern memory-intensive high-performance applications. Such applications do not take long to hit the physical memory limit and start paging to disk, which in turn considerably slows down their performance. We tackle this problem in the Adaptive Network Memory Engine (Anemone) project by pooling together the distributed memory resources of multiple machines across a gigabit network based cluster. Anemone is a distributed memory virtualization system that can dramatically improve application performance by paging over the gigabit network to the unused memory of remote clients. Anemone provides clients with completely transparent access to a potentially unlimited amount of collective memory pool. Earlier research efforts in this area advocate significant modifications to client systems, either in terms of a specific programming interface for applications, or in terms of extensive changes to the operating systems and device drivers. In contrast, Anemone requires no modifications to either the client system or the memory-intensive application.