Redundant dataflow applications on clustered manycore architectures

  • Increasing performance requirements in the embedded systems domain have encouraged a drift from singlecore to multicore processors. Cars are an example for complex embedded systems in which the use of multicores continues to grow. The requirements of software components running in modern cars are diverse. On the one hand there are safety-critical tasks like the airbag control, on the other hand tasks which do not have any safety-related requirements at all, for example those controlling the infotainment system. Trends like autonomous driving lead to tasks which are simultaneously safety-critical and computationally complex. To satisfy the requirements of modern embedded applications we developed a dataflow-based runtime environment (RTE) for clustered manycore architectures. The RTE is able to execute dataflow graphs in various redundancy configurations and with different schedulers. We implemented our RTE design on the Kalray Bostan Massively Parallel Processor Array and evaluated allIncreasing performance requirements in the embedded systems domain have encouraged a drift from singlecore to multicore processors. Cars are an example for complex embedded systems in which the use of multicores continues to grow. The requirements of software components running in modern cars are diverse. On the one hand there are safety-critical tasks like the airbag control, on the other hand tasks which do not have any safety-related requirements at all, for example those controlling the infotainment system. Trends like autonomous driving lead to tasks which are simultaneously safety-critical and computationally complex. To satisfy the requirements of modern embedded applications we developed a dataflow-based runtime environment (RTE) for clustered manycore architectures. The RTE is able to execute dataflow graphs in various redundancy configurations and with different schedulers. We implemented our RTE design on the Kalray Bostan Massively Parallel Processor Array and evaluated all possible configurations for three common computation tasks. To classify the performance of our RTE, we compared the non-redundant graph executions with OpenCL versions of the three applications. The results show that our RTE can come close or even surpass Kalray's OpenCL framework, although maximum performance was not the primary goal of our design.show moreshow less

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Metadaten
Author:Christoph KühbacherGND, Theo UngererORCiDGND, Sebastian AltmeyerGND
URN:urn:nbn:de:bvb:384-opus4-967262
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/96726
ISBN:978-1-4503-8713-2OPAC
Parent Title (English):SAC '22: proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, virtual event, April 25 - 29, 2022
Publisher:ACM
Place of publication:New York, NY
Editor:Jiman Hong, Miroslav Bures, Juw Won Park, Tomas Cerny
Type:Part of a Book
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2022/07/14
First Page:226
Last Page:235
DOI:https://doi.org/10.1145/3477314.3507272
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Systemnahe Informatik und Kommunikationssysteme
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Systems
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht