Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads

What is it about?

Applications running on this container with 100% working set fit into memory enjoy their performance. It suffers from transient performance degradations when its working set does not fit into the allocated memory on the container, even if host-level memory is available: the host machine has free memory and remote-memory is available: other nodes in the cluster have free memory. So, the objective of this research is to develop an unified memory orchestration framework for efficient management of both host and remote idle memory.

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Photo by imgix on Unsplash

Photo by imgix on Unsplash

Why is it important?

The paper makes three original contributions. First, we redesign the data flow in the critical path by introducing a host-coordinated memory pool that works as a local cache to reduce the latency in the critical path of the host and remote memory orchestration. Second, Valet utilizes unused local memory across containers by managing local memory via Valet host-coordinated memory pool, which allows containers to dynamically expand and shrink their memory allocations according to the workload demands. Third, Valet provides an efficient remote memory reclaiming technique on remote peers, based on two optimizations: (1) an activity-based victim selection scheme to allow the least-active-block of data to be selected for serving the eviction requests and (2) a migration protocol to move the least-active-block of data to less-memory- pressured remote node.