Schoeberl, M., Abbaspour, S., Akesson, B., Audsley, N., Capasso, R., Garside, J., Goossens, K., Goossens, S., Hansen, S., Heckmann, R., Hepp, S., Huber, B., Jordan, A., Kasapaki, E., Knoop, J., Li, Y., Prokesch, D., Puffitsch, W., Puschner, P., … Tocchi, A. (2015). T-CREST: Time-Predictable Multi-Core Architecture for Embedded Systems. Journal of Systems Architecture, 61(9), 449–471. https://doi.org/10.1016/j.sysarc.2015.04.002
E194-05 - Forschungsbereich Compilers and Languages E191-01 - Forschungsbereich Cyber-Physical Systems
Journal of Systems Architecture
Number of Pages:
Software; Hardware and Architecture; Real-time systems; Time-predictable computer architecture
Real-time systems need time-predictable platforms to allow static analysis of the worst-case execution time (WCET). Standard multi-core processors are optimized for the average case and are hardly analyzable. Within the T-CREST project we propose novel solutions for time-predictable multi-core architectures that are optimized for the WCET instead of the average-case execution time. The resulting time-predictable resources (processors, interconnect, memory arbiter, and memory controller) and tools (compiler, WCET analysis) are designed to ease WCET analysis and to optimize WCET performance. Compared to other processors the WCET performance is outstanding.
The T-CREST platform is evaluated with two industrial use cases. An application from the avionic domain demonstrates that tasks executing on different cores do not interfere with respect to their WCET. A signal processing application from the railway domain shows that the WCET can be reduced for computation-intensive tasks when distributing the tasks on several cores and using the network-on-chip for communication. With three cores the WCET is improved by a factor of 1.8 and with 15 cores by a factor of 5.7.
The T-CREST project is the result of a collaborative research and development project executed by eight partners from academia and industry. The European Commission funded T-CREST.
Computer Engineering and Software-Intensive Systems: 100%