Memory footprint reduction for embedded systems

Abstract

The memory footprint is considered an important constraint for embedded systems. This is especially important in the context of increasing sophistication of embedded software, and the increasing use of modern software engineering techniques like component-based design. Since reusability is the major motivation for using components, most components are not optimized for the (limited) functionality they have to realize in an embedded system. All this leads to an increasing amount of code and data that might not be needed for a given functionality. The memory footprint of an embedded system consists of 2 parts: the footprint of the application and the footprint of the operating system. In this keynote talk, I will focus on the memory footprint reduction of application as well as the Linux kernel. I will report memory footprint reductions that have been obtained by the Diablo binary rewriter, which has been used to substantially reduce the memory footprint of both applications and of the system software. For the applications, the optimizer is capable of reducing the code size of programs compiled with two proprietary ARM tool chains (ADS 1.1 and RVCT 2.1) with on average 16% for statically linked ARM programs, while making them 12.8% faster. Execution of the rewritten programs also consumes on average 10.7% less energy. For the system software, we specialize the kernel both for the system calls that are actually occurring in the application program, and for the boot parameters of the kernel. We also assume that the hardware is fixed so that part of the bootstrap process is completely deterministic and can be optimized based on actual trace information. Finally, we compress frozen code, and we swap cold code to flash memory. All combined, these compaction techniques on the kernel can reduce the kernel's RAM footprint with up to 48% for the Linux kernel. The slowdown was limited to 1--2%. This proves that binary rewriting can help in substantially reducing the memory footprint of both the application and the system software. The nice thing is that it can be done automatically, and that it also reduces the execution time and the power consumption.