CSALT: context switch aware large TLB

Computing in virtualized environments has become a common practice for many businesses. Typically, hosting companies aim for lower operational costs by targeting high utilization of host machines maintaining just enough machines to meet the demand. In this scenario, frequent virtual machine context switches are common, resulting in increased TLB miss rates (often, by over 5X when contexts are doubled) and subsequent expensive page walks. Since each TLB miss in a virtual environment initiates a 2D page walk, the data caches get filled with a large fraction of page table entries (often, in excess of 50%) thereby evicting potentially more useful data contents.

In this work, we propose CSALT - a Context-Switch Aware Large TLB, to address the problem of increased TLB miss rates and their adverse impact on data caches. First, we demonstrate that the CSALT architecture can effectively cope with the demands of increased context switches by its capacity to store a very large number of TLB entries. Next, we show that CSALT mitigates data cache contention caused by conflicts between data and translation entries by employing a novel TLB-Aware Cache Partitioning scheme. On 8-core systems that switch between two virtual machine contexts executing multi-threaded workloads, CSALT achieves an average performance improvement of 85% over a baseline with conventional L1-L2 TLBs and 25% over a baseline which has a large L3 TLB.