| 1. |
- Behnam, Moris, et al.
(författare)
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An overrun method to support composition of semi-independent real-time components
- 2008
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Ingår i: Proceedings - International Computer Software and Applications Conference. - 9780769532622 ; , s. 1347-1352
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Konferensbidrag (refereegranskat)abstract
- Engineers of embedded software systems rely on efficient design techniques and tools along with efficient run-time support. In the design of complex embedded real-time systems, the Hierarchical Scheduling Framework (HSF) has been introduced as a design-time framework enabling compositional schedulability analysis of embedded software systems with real-time properties. Moreover, the HSF provides a run-time framework guaranteeing that these non-functional requirements are met. In this paper a system consists of a number of semi-independent components called subsystems, and these subsystems are allowed to share logical resources. The HSF makes sure that the individual subsystems respect their allocated CPU budgets. However, as semi-independent sub-systems share logical resources, extra complexity is introduced. Specifically, the contribution of this paper is a novel method to allow for budget overruns; a common scenario when a subsystem utilizes shared logical resources. This proposed method is not only more resource efficient than existing methods, but it is also more appropriate for supporting composability of independently developed real-time subsystems.
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| 2. |
- Behnam, Moris, et al.
(författare)
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Scheduling of Semi-Independent Real-Time Components: Overrun Methods and Resource Holding Times
- 2008
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Ingår i: Proceedings of the 13th IEEE International Conference on Emerging echnologies and Factory Automation (ETFA’08). - 9781424415052 ; , s. 575-582
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Konferensbidrag (refereegranskat)abstract
- The Hierarchical Scheduling Framework (HSF) has been introduced as a design-time framework enabling compositional schedulability analysis of embedded software systems with real-time properties. In this paper a system consists of a number of semi-independent components called subsystems. Subsystems are developed independently and later integrated to form a system. To support this design process, our proposed methods allow nonintrusive configuration and tuning of subsystem timing behaviour via subsystem interfaces for selecting scheduling parameters. This paper considers two methods to handle overruns due to resource sharing between subsystems in the HSF. We present the scheduling algorithms for overruns and their associated schedulability analysis, together with analysis that shows under what circumstances one or the other overrun method is preferred. Furthermore, we show how to calculate resource-holding times within our framework.
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| 3. |
- Behnam, Moris, et al.
(författare)
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SIRAP : A Synchronization Protocol for Hierarchical Resource Sharing in Real-Time Open Systems
- 2007
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Ingår i: EMSOFT'07: Proceedings of the Seventh ACM and IEEE International Conference on Embedded Software. - New York, New York, USA : ACM Press. - 9781595938251 ; , s. 279-288
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Konferensbidrag (refereegranskat)abstract
- This paper presents a protocol for resource sharing in a hierarchical real-time scheduling framework. Targeting real-time open systems, the protocol and the scheduling framework significantly reduce the efforts and errors associated with integrating multiple semi-independent subsystems on a single processor. Thus, our proposed techniques facilitate modern software development processes, where subsystems are developed by independent teams (or subcontractors) and at a later stage integrated into a single product. Using our solution, a subsystem need not know, and is not dependent on, the timing behaviour of other subsystems; even though they share mutually exclusive resources. In this paper we also prove the correctness of our approach and evaluate its efficiency.
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| 4. |
- Danielsson, Jakob, et al.
(författare)
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Resource Depedency Analysis in Multi-Core Systems
- 2020
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Ingår i: Proceedings - 2020 IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728173030 ; , s. 87-94
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Konferensbidrag (refereegranskat)abstract
- In this paper, we evaluate different methods for statistical determination of application resource dependency in multi-core systems. We measure the performance counters of an application during run-time and create a system resource usage profile. We then use the resource profile to evaluate the application dependency on the specific resource. We discuss and evaluate two methods to process the data, including moving average filter and partitioning the data into smaller segments in order to interpret data for correlation calculations. Our aim with this study is to evaluate and create a generalizeable methods for automatic determination of resource dependencies. The final outcome of the methods used in this study is the answer to the question: 'To what resources is this application dependent on?'. The recommendation of this tool will be used in conjunction with our last-level cache partitioning controller (LLC-PC), to make decision if an application should receive last-level cache partition slices.
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| 5. |
- Tsog, Nandinbaatar
(författare)
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Improving On-Board Data Processing using CPU-GPU Heterogeneous Architectures for Real-Time Systems
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis investigates the efficacy of heterogeneous computing architectures in real-time systems.The goals of the thesis are twofold. First, to investigate various characteristics of the Heterogeneous System Architectures (HSA) compliant reference platforms focusing on computing performance and power consumption. The investigation is focused on the new technologies that could boost on-board data processing systems in satellites and spacecraft. Second, to enhance the usage of the heterogeneous processing units by introducing a technique for static allocation of parallel segments of tasks.The investigation and experimental evaluation show that our method of GPU allocation for the parallel segments of tasks is more energy efficient compared to any other studied allocation. The investigation is conducted under different types of environments, such as process-level isolated environment, different software stacks, including kernels, and various task set scenarios. The evaluation results indicate that a balanced use of heterogeneous processing units (CPU and GPU) could improve schedulability of task sets up to 90% with the proposed allocation technique.
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| 6. |
- Tsog, Nandinbaatar, et al.
(författare)
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Intelligent Data Processing using In-Orbit Advanced Algorithms on Heterogeneous System Architecture
- 2018
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Ingår i: IEEE Aerospace Conference 2018 IEEEAC2018. ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- In recent years, commercial exploitation of small satellites and CubeSats has rapidly increased. Time to market of processed customer data products is becoming an important differentiator between solution providers and satellite constellation operators. Timely and accurate data dissemination is the key to success in the commercial usage of small satellite constellations which is ultimately dependent on a high degree of autonomous fleet management and automated decision support. The traditional way for disseminating data is limited by on the communication capability of the satellite and the ground terminal availability. Even though cloud computing solutions on the ground offer high analytical performance, getting the data from the space infrastructure to the ground servers poses a bottleneck of data analysis and distribution. On the other hand, adopting advanced and intelligent algorithms onboard offers the ability of autonomy, tasking of operations, and fast customer generation of low latency conclusions, or even real-time communication with assets on the ground or other sensors in a multi-sensor configuration. In this paper, the advantages of intelligent onboard processing using advanced algorithms for Heterogeneous System Architecture (HSA) compliant onboard data processing systems are explored. The onboard data processing architecture is designed to handle a large amount of high-speed streaming data and provides hardware redundancy to be qualified for the space mission application domain. We conduct an experimental study to evaluate the performance analysis by using image recognition algorithms based on an open source intelligent machine library 'MIOpen' and an open standard 'OpenVX'. OpenVX is a cross-platform computer vision library.
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| 7. |
- Tsog, Nandinbaatar, et al.
(författare)
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Static Allocation of Parallel Tasks to Improve Schedulability in CPU-GPU Heterogeneous Real-Time Systems
- 2019
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Konferensbidrag (refereegranskat)abstract
- Autonomous driving is one of the main challenges of modern cars. Computer visions and intelligent on-board decision making are crucial in autonomous driving and require heterogeneous processors with high computing capability under low power consumption constraints. The progress of parallel computing using heterogeneous processing units is further supported by software frameworks like OpenCL, OpenMP, CUDA, and C++AMP. These frameworks allow the allocation of parallel computation on different compute resources. This, however, creates a difficulty in allocating the right computation segments to the right processing units in such a way that the complete system meets all its timing requirements. In this paper, we consider pre-runtime static allocations of parallel tasks to perform their execution either sequentially on CPU or in parallel using a GPU. This allows for improving any unbalanced use of GPU accelerators in a heterogeneous environment. By performing several heuristic algorithms, we show that the overuse of accelerators results in a bottle-neck of the entire system execution. The experimental results show that our allocation schemes that target a balanced use of GPU improve the system schedulability up to 90%.
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