Enhancing virtualized application performance through dynamic adaptive paging mode selection

Virtual address translation in a virtual machine monitor (VMM) for modern x86 processors can be implemented using a software approach known as shadow paging or a hardware approach known as nested paging. Most VMMs, including our Palacios VMM, support both. Using a range of benchmark measurements, we show that which approach is preferable for achieving high application performance under virtualization is workload dependent, and that the performance differences between the two approaches can be substantial. We have developed an algorithm, based on measuring the TLB miss rate and the VMM exit rate for paging-related exits, for measuring the performance of the current paging approach during normal execution and predicting when switching approaches is likely to be beneficial to the application. We combine this with new support in Palacios for switching paging approaches at any time to implement a dynamic adaptive paging approach called DAV2M for dynamically adaptive virtualized virtual memory. DAV2M attempts to deliver application performance that is the same or better than the best static approach for a given workload. Our evaluation shows that it does so, and, for a range of benchmarks, DAV2M delivers performance within 5--8% of native, reducing overheads by as much as a factor of four. Although both the shadow and nested paging approaches are evolving, the dynamic adaptive approach can combine their best qualities.