Multi-Criterial Code Optimization for Embedded Hard Real-Time Systems (Multi-Opt)
|Name||Multi-Criterial Code Optimization for Embedded Hard Real-Time Systems|
(in German: Multikriterielle Code-Optimierung für Eingebettete Harte Echtzeitsysteme)
|Role of TUHH||Applicant|
|Funds Donor||Deutsche Forschungsgemeinschaft (DFG)|
Embedded hard real-time systems often have to meet additional design constraints beyond their worst-case timing constraints. Systems operated on battery power have a limited amount energy available and should thus be as energy-efficient as possible. In addition, instruction, data and main memories of typical embedded processor architectures are also frequently severely limited due to technical limitations or given financial budgets. While designing embedded systems, these additional criteria also have to be considered, besides the system's real-time constraints.
In order to achieve a correctly designed system, it has to meet all of the imposed resource constraints. If a system violates one or several design constraints, either the hardware platform must be modified or the resource demand of the software must be lowered. Modifying the hardware usually comes with an increase in costs and hardly predictable side effects. For example, exchanging the system's micro-controller in order to reduce power consumption will lead to changes in temporal behavior. Reducing the resource demand of the software by simply removing parts of the code is also not easily possible without compromising the correct functional behavior of the system.
As a result, this project aims at optimizing embedded software systems at the compiler level with respect to multiple different design requirements. While translating source code to executable code, the compiler will aim to generate optimized code that finally fulfills all constraints with respect to multiple design criteria. However, current compilers are not able to achieve this, because multi-criterial system design is a highly volatile process. The optimization goals interfere with or may even directly contradict each other. Therefore, as part of this proposal, new optimization methods will be researched, implemented end evaluated for existing embedded hardware architectures. We focus on three of the most important criteria that embedded system designers are facing: Worst-Case Execution Time (WCET), code size and energy consumption.
|Title: Multi-Criteria Function Inlining for Hard Real-Time Systems. <em>In Proceedings of the 28th International Conference on Real-Time Networks and Systems (RTNS)</em>|
|Written by: Kateryna Muts and Heiko Falk|
|in: June (2020).|
|on pages: 56-66|
|Address: Paris / France|
|how published: 20-90 MF20 RTNS|
Note: kmuts, hfalk, multiopt, ESD, WCC
Abstract: Modern hard real-time systems shall satisfy some special requirements. Besides timing constraints, the additional design criteria such as code size and energy consumption are also not negligible. To optimize a system towards the mentioned specifications simultaneously is impossible, since the improvement in one of them may lead to the degradation of others. Many compiler-based optimizations techniques have been proposed to optimize an embedded application taking into account only one requirement. Nevertheless, some heuristics consider other requirements as constraints, but not many works have tried to solve a multi-objective problem in this context. We aim to extend a well-known compiler-based optimization, function inlining, to a multi-objective problem. We show that in case of such setup, the considered optimization leads to a set of trade-offs between timing constraints, code size, and energy consumption. Depending on the requirements, a system designer can utilize the output set to make a final decision about the system configuration without building an expensive hardware.