PTEMagnet: Fine-Grained Physical Memory Reservation for Faster Page Walks in Public Clouds

The last few years have seen a rapid adoption of cloud computing for data-intensive tasks. In the cloud environment, it is common for applications to run under virtualization and to share a virtual machine with other applications (e.g., in a virtual private cloud setup). In this setting, our work identifies a new address translation bottleneck caused by memory fragmentation stemming from the interaction of virtualization, colocation, and the Linux memory allocator. The fragmentation results in the effective cache footprint of the host PT being larger than that of the guest PT. The bloated footprint of the host PT leads to frequent cache misses during nested page walks, increasing page walk latency.

In response to these observations, we propose PTEMagnet, a new software-only approach for reducing address translation latency in a public cloud. PTEMagnet prevents memory fragmentation through a fine-grained reservation-based allocator in the guest OS. Our evaluation shows that PTEMagnet is free of performance over-heads and can improve performance by up to 9% (4% on average). PTEMagnet is fully legacy-preserving, requiring no modifications to either user code or mechanisms for address translation and virtualization.