On the use of static branch prediction to reduce the worst-case execution time of real-time applications
| Autor: | Andreu Carminati, Renan Augusto Starke, Rômulo Silva de Oliveira |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
Control and Optimization Computer Networks and Communications Computer science ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology computer.software_genre Branch predictor 01 natural sciences Execution time 020202 computer hardware & architecture Computer Science Applications Reduction (complexity) Set (abstract data type) Low complexity Worst-case execution time Computer engineering Control and Systems Engineering Modeling and Simulation 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Compiler Electrical and Electronic Engineering Performance enhancement computer |
| Zdroj: | Real-Time Systems. 54:537-561 |
| ISSN: | 1573-1383 0922-6443 |
| DOI: | 10.1007/s11241-018-9306-y |
| Popis: | Nowadays, real-time applications need more and more hardware performance. This increasing performance demands the use of deterministic performance enhancement features such as static branch prediction. In this paper we propose a new technique which aims to use static branch prediction for worst-case execution time (WCET) reduction that can be applied on any processor that supports this type of prediction. The only requirement is the support of a WCET tool. This paper also describes how to estimate the maximum WCET reduction that can be obtained with static approaches. We show that our technique produces a slightly better result than a similar approach from the literature. We also compare WCET-centered techniques against standard compiler techniques not directly oriented to WCET reduction. We show that a very small or even no gain can be obtained with new techniques targeted to WCET reduction considering static branch prediction. That means the techniques considered in this paper are close to an optimal result. As a secondary contribution, we show that non WCET-aware techniques can also be used in real-time environments because they present good results and low complexity. We evaluate the prediction techniques using a set of examples from the Malardalen WCET benchmarks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink