Distributed memory systems are becoming increasingly important since they provide a system-scale abstraction where physically separated memories can be addressed as a single logical one. This abstraction enables memory disaggregation, allowing systems as in-memory databases, caching services, and ephemeral storage to be naturally deployed at large scales. While this abstraction effectively increases the memory capacity of these systems, it faces additional overheads for remote memory accesses. To narrow the difference between local and remote accesses, low latency RDMA networks are a key element for efficient memory disaggregation. However, RDMA acceleration poses new obstacles to efficient memory management and particularly to memory compaction: network controllers and CPUs can concurrently access memory, potentially leading to inconsistencies if memory management operations are not synchronized. To ensure consistency, most distributed memory systems do not provide memory compaction and are exposed to memory fragmentation. We introduce CoRM, an RDMA-accelerated shared memory system that supports memory compaction and ensures strict consistency while providing one-sided RDMA accesses. We show that CoRM sustains high read throughput during normal operations, comparable to similar systems not providing memory compaction while experiencing minimal overheads during compaction. CoRM never disrupts RDMA connections and can reduce applications' active memory up to 6x by performing memory compaction.
@inproceedings{, author={Konstantin Taranov and Salvatore Di Girolamo and Torsten Hoefler}, title={{CoRM: Compactable Remote Memory over RDMA}}, year={2021}, month={Jun.}, booktitle={Proceedings of the 2021 ACM SIGMOD International Conference on Management of Data}, source={http://www.unixer.de/~htor/publications/}, }
