Efficient Automated Code Partitioning for Microcontrollers with Switchable Memory Banks

Abstract

Switching active memory banks at runtime allows a processor with a narrow address bus to access memory that exceeds ranges normally addressable via the bus. Switching code memory banks is regaining interest in microcontrollers for the Internet of Things (IoT), which have to run continuously growing software, while at the same time consuming ultra-small amounts of energy. To make use of bank switching, such software must be partitioned among the available banks and augmented with bank-switching instructions. In contrast to the augmenting, which is done automatically by a compiler, today the partitioning is normally done manually by programmers. However, since IoT software is cross-compiled on much more powerful machines than its target microcontrollers, it becomes possible to partition it automatically during compilation. In this article, we thus study the problem of partitioning program code among banks such that the resulting runtime performance of the program is maximized. We prove that the problem is NP -hard and propose a heuristic algorithm with a low complexity, so it enables fast compilation and hence interactive software development. The algorithm decomposes the problem into three subproblems and introduces a heuristic for each of them: (1) which pieces of code to partition, (2) which of them to assign to permanently mapped banks, and (3) how to divide the remaining ones among switchable banks. We integrate the algorithm, together with earlier ones, in an open-source compiler and test the resulting solution on synthetic as well as actual commercial IoT software bases, thereby demonstrating its advantages and drawbacks. In particular, the results show that the performance of partitions produced by our algorithm comes close to that of partitions created manually by programmers with expert knowledge on the partitioned code.