PageForge: A Near-Memory Content-Aware Page-Merging Architecture

摘要

To reduce the memory requirements of virtualized environments, modern hypervisors are equipped with the capability to search the memory address space and merge identical pages - a process called page deduplication. This process uses a combination of data hashing and exhaustive comparison of pages, which consumes processor cycles and pollutes caches. In this paper, we present a lightweight hardware mechanism that augments the memory controller and performs the page merging process with minimal hypervisor involvement. Our concept, called PageForge, is effective. It compares pages in the memory controller, and repurposes the Error Correction Codes (ECC) engine to generate accurate and inexpensive ECC-based hash keys. We evaluate PageForge with simulations of a 10-core processor with a virtual machine (VM) on each core, running a set of applications from the TailBench suite. When compared with RedHat's KSM, a state-ofthe-art software implementation of page merging, PageForge attains identical savings in memory footprint while substantially reducing the overhead. Compared to a system without same-page merging, PageForge reduces the memory footprint by an average of 48%, enabling the deployment of twice as many VMs for the same physical memory. Importantly, it keeps the average latency overhead to 10%, and the 95th percentile tail latency to 11%. In contrast, in KSM, these latency overheads are 68% and 136%, respectively.