Predictable code and data paging for real time systems

There is a need for using virtual memory in real-time ap-plications: using virtual addressing provides isolation between concurrent processes; in addition, paging allows the execution of applications whose size is larger than main memory capac-ity, which is useful in embedded systems where main memory is expensive and thus scarce. However, virtual memory is gen-erally avoided when developing real-time and embedded appli-cations due to predictability issues. In this paper we propose a predictable paging system in which the page loading and page eviction points are selected at compile-time. The contents of main memory is selected using an Integer Linear Programming (ILP) formulation. Our approach is applied to code, static data and stack regions of individual tasks. We show that the time re-quired for selecting memory contents is reasonable for all ap-plications including the largest ones, demonstrating the scala-bility of our approach. Experimental results compare our ap-proach with a previous one, based on graph coloring. It shows that quality of page allocation is generally improved, with an average improvement of 30 % over the previous approach. An-other comparison with a state-of-the-art demand-paging sys-tem shows that predictability does not come at the price of per-formance loss. 1