Ginkgo: Automated, Application-Driven Memory Overcommitment for Cloud Computing
Continuous advances in multicore and I/O technologies have caused memory to become a very valuable sharable resource that limits the number of Virtual Machines (VMs) that can be hosted in a single physical server.While today's hypervisors implement a wide range of mechanisms to overcommit memory, they lack memory allocation policies and frameworks capable of guaranteeing levels of quality of service to their applications. In this paper, the authors introduce Ginkgo, a memory overcommit framework that takes an application-aware approach to the problem. Ginkgo dynamically estimates VMmemory requirements for applications without user involvement or application changes. Ginkgo regularly monitors application progress and incoming load for each VM, using this data to predict application performance under different VM memory sizes.