Is dynamic compilation possible for embedded systems?

Abstract

JIT compilation and dynamic compilation are powerful techniques allowing to delay the final code generation to the runtime. There is many benefits: improved portability, virtual machine security, etc. Unforturnately the tools used for JIT compilation and dynamic compilation does not met the classical requirement for embedded platforms: memory size is huge and code generation has big overheads. In this paper we show how dynamic code specialization (JIT) can be used and be beneficial in terms of execution speed and energy consumption with memory footprint kept under control. We based our approaches on our tool deGoal and on LLVM, that we extended to be able to produce lightweight runtime specializers from annotated LLVM programs. Benchmarks are manipulated and transformed into templates and a specialization routine is build to instantiate the routines. Such approach allows to produce efficient specializations routines, with a minimal energy consumption and memory footprint compare to a generic JIT application. Through some benchmarks, we present its efficiency in terms of speed, energy and memory footprint. We show that over static compilation we can achieve a speed-up of 21 % in terms of execution speed but also a 10 % energy reduction with a moderate memory footprint.