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Publications (10 of 16) Show all publications
Tsog, N., Sjödin, M. & Bruhn, F. (2019). A Trade-Off between Computing Power and Energy Consumption of On-Board Data Processing in GPU Accelerated Real-Time Systems. In: : . Paper presented at The 32nd International Symposium on Space Technology and Science, Fukui, Japan.
Open this publication in new window or tab >>A Trade-Off between Computing Power and Energy Consumption of On-Board Data Processing in GPU Accelerated Real-Time Systems
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

On-board data processing is one of the prior on-orbit activities that it improves the performance capability of in-orbit space systems such as deep-space exploration, earth and atmospheric observation satellites, and CubeSat constellations. However, on-board data processing encounters with higher energy consumption compared to traditional space systems. Because traditional space systems employ simple processing units such as micro-controllers or a single-core processor as the systems require no heavy data processing on orbit. Moreover, solving the radiation hardness problem is crucial in space and adopting a new processing unit is challenging.

In this paper, we consider a GPU accelerated real-time system for on-board data processing. According to prior works, there exist radiation-tolerant GPU, and the computing capability of systems is improved by using heterogeneous computing method. We conduct experimental observations of power consumption and computing potential using this heterogeneous computing method in our GPU accelerated real-time system.The results show that the proper use of GPU increases computing potential with 10-140 times and consumes between 8-130 times less energy. Furthermore, the entire task system consumes 10-65% of less energy compared to the traditional use of processing units.

Keywords
Trade-off, Computing power, Energy consumption, on-board data processing, GPU acceleration, Real-time systems
National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45938 (URN)
Conference
The 32nd International Symposium on Space Technology and Science, Fukui, Japan
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-11-22Bibliographically approved
Tsog, N., Becker, M., Bruhn, F., Behnam, M. & Nolin, M. (2019). Static Allocation of Parallel Tasks to Improve Schedulability in CPU-GPU Heterogeneous Real-Time Systems. In: : . Paper presented at IEEE 45th Annual Conference of the Industrial Electronics Society, IECON2019.
Open this publication in new window or tab >>Static Allocation of Parallel Tasks to Improve Schedulability in CPU-GPU Heterogeneous Real-Time Systems
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2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

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%.

Keywords
Parallel task, Parallel segment, Alternative execution, CPU-GPU, Heterogeneous processors, Real-time systems
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45934 (URN)
Conference
IEEE 45th Annual Conference of the Industrial Electronics Society, IECON2019
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-12-13Bibliographically approved
Tsog, N., Nolin, M. & Bruhn, F. (2019). Using Docker in Process Level Isolation for Heterogeneous Computing on GPU Accelerated On-Board Data Processing Systems. In: : . Paper presented at 12th IAA Symposium on Small Satellites for Earth Observation, Berlin, Germany.
Open this publication in new window or tab >>Using Docker in Process Level Isolation for Heterogeneous Computing on GPU Accelerated On-Board Data Processing Systems
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The technological advancements make the intelligent on-board data processing possible on a small scale of satellites and deep-space exploration spacecraft such as CubeSats. However, the operation of satellites may fall into critical conditions when the on-board data processing interferes strongly to the basic operation functionalities of satellites. In order to avoid these issues, there exist techniques such as isolation, partitioning, and virtualization. In this paper, we present an experimental study of isolation of on-board payload data processing from the basic operations of satellites using Docker. Docker is a leading technology in process level isolation as well as continuous integration and continuous deployment (CI/CD) method. This study continues with the prior study on heterogeneous computing method, which improves the schedulability of the entire system up to 90%. Based on this heterogeneous computing method, the comparison study has been conducted between the non-isolated and isolated environments.

Keywords
Process level isolation, Docker, On-board data processing, Heterogeneous computing, cgroups, Linux
National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45939 (URN)
Conference
12th IAA Symposium on Small Satellites for Earth Observation, Berlin, Germany
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2019-11-11 Created: 2019-11-11 Last updated: 2019-12-13Bibliographically approved
Tsog, N., Sjödin, M. & Bruhn, F. (2019). Using Heterogeneous Computing on GPU Accelerated Systems to Advance On-Board Data Processing. In: European Workshop on On-Board Data Processing 2019 OBDP2019: . Paper presented at European Workshop on On-Board Data Processing 2019 OBDP2019, 25 Feb 2019, Amsterdam, Netherlands.
Open this publication in new window or tab >>Using Heterogeneous Computing on GPU Accelerated Systems to Advance On-Board Data Processing
2019 (English)In: European Workshop on On-Board Data Processing 2019 OBDP2019, 2019Conference paper, Published paper (Refereed)
Keywords
Heterogeneous Computing, GPU accelerated On-Board Data Processing, Advanced On-Board Data Processing
National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45490 (URN)
Conference
European Workshop on On-Board Data Processing 2019 OBDP2019, 25 Feb 2019, Amsterdam, Netherlands
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-10-29Bibliographically approved
Tsog, N., Sjödin, M. & Bruhn, F. (2018). Advancing On-Board Big Data Processing Using Heterogeneous System Architecture. In: ESA/CNES 4S Symposium 4S 2018: . Paper presented at ESA/CNES 4S Symposium 4S 2018, 28 May 2018, Sorrento, Italy.
Open this publication in new window or tab >>Advancing On-Board Big Data Processing Using Heterogeneous System Architecture
2018 (English)In: ESA/CNES 4S Symposium 4S 2018, 2018Conference paper, Poster (with or without abstract) (Refereed)
Keywords
Heterogeneous System Architecture (HSA)Onboard ProcessingBig DataCPU-GPUCaffe (Convolutional Architecture for Fast Feature Embedding)ROCmSmall SatelliteCubeSatImagenet
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-39269 (URN)
Conference
ESA/CNES 4S Symposium 4S 2018, 28 May 2018, Sorrento, Italy
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2018-05-23 Created: 2018-05-23 Last updated: 2018-05-23Bibliographically approved
Tsog, N., Behnam, M., Nolin, M. & Bruhn, F. (2018). Intelligent Data Processing using In-Orbit Advanced Algorithms on Heterogeneous System Architecture. In: IEEE Aerospace Conference 2018 IEEEAC2018: . Paper presented at IEEE Aerospace Conference 2018 IEEEAC2018, 03 Mar 2018, Big Sky, United States (pp. 1-8).
Open this publication in new window or tab >>Intelligent Data Processing using In-Orbit Advanced Algorithms on Heterogeneous System Architecture
2018 (English)In: IEEE Aerospace Conference 2018 IEEEAC2018, 2018, p. 1-8Conference paper, Published paper (Refereed)
Abstract [en]

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.

Series
IEEE Aerospace Conference Proceedings, ISSN 1095-323X
Keywords
Heterogeneous System Architecture (HSA)Intelligent Data ProcessingMIOpenOpenVXCubeSatCPU-GPUEnergy consumption
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-38628 (URN)10.1109/AERO.2018.8396536 (DOI)000474397401066 ()2-s2.0-85049840022 (Scopus ID)
Conference
IEEE Aerospace Conference 2018 IEEEAC2018, 03 Mar 2018, Big Sky, United States
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2020-01-10Bibliographically approved
Tsog, N., Becker, M., Larsson, M., Bruhn, F., Behnam, M. & Sjödin, M. (2016). Poster Abstract: Real-Time Capabilities of HSA Compliant COTS Platforms. In: PROCEEDINGS OF 2016 IEEE REAL-TIME SYSTEMS SYMPOSIUM (RTSS): . Paper presented at 37th IEEE Real-Time Systems Symposium (RTSS), NOV 29-DEC 02, 2016, Porto, PORTUGAL (pp. 364-364).
Open this publication in new window or tab >>Poster Abstract: Real-Time Capabilities of HSA Compliant COTS Platforms
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2016 (English)In: PROCEEDINGS OF 2016 IEEE REAL-TIME SYSTEMS SYMPOSIUM (RTSS), 2016, p. 364-364Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

During recent years, the interest in using heterogeneous computing architecture in industrial applications has increased dramatically. These architectures provide the computational power that makes them attractive for many industrial applications. However, most of these existing heterogeneous architectures suffer from the following limitations: difficulties of heterogeneous parallel programming and high communication cost between the computing units. To overcome these disadvantages, several leading hardware manufacturers have formed the HSA Foundation to develop a new hardware architecture: Heterogeneous System Architecture (HSA). In this paper, we investigate the suitability of using HSA for real-time embedded systems. A preliminary experimental study has been conducted to measure massive computing power and timing predictability of HSA.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-35361 (URN)10.1109/RTSS.2016.043 (DOI)000399156600034 ()2-s2.0-85011691127 (Scopus ID)978-1-5090-5303-2 (ISBN)
Conference
37th IEEE Real-Time Systems Symposium (RTSS), NOV 29-DEC 02, 2016, Porto, PORTUGAL
Available from: 2017-05-19 Created: 2017-05-19 Last updated: 2019-01-16Bibliographically approved
Bergman, J. E. S., Bruhn, F., Funk, P., Isham, B., Rincon-Charris, A., Capo-Lugo, P. & Åhlen, L. (2015). Exploiting Artificial Intelligence for Analysis and Data Selection on-board the Puerto Rico CubeSat. In: : . Paper presented at European Planetary Science Congress 2015, held 27 September - 2 October, 2015 in Nantes, France.
Open this publication in new window or tab >>Exploiting Artificial Intelligence for Analysis and Data Selection on-board the Puerto Rico CubeSat
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2015 (English)Conference paper, Published paper (Refereed)
Keywords
Artificial Intelligence, Cube Satellite, Heterogoeneous Computing
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-35422 (URN)
Conference
European Planetary Science Congress 2015, held 27 September - 2 October, 2015 in Nantes, France
Projects
GIMME-SPACE
Available from: 2017-06-12 Created: 2017-06-12 Last updated: 2017-06-12Bibliographically approved
Bruhn, F., Brunberg, K., Hines, J., Asplund, L. & Norgren, M. (2015). Introducing Radiation Tolerant Heterogeneous Computers for Small Satellites. In: IEEE Aerospace Conference Proceedings, vol. 2015: . Paper presented at IEEE Aerospace Conference 2015 IEEEAC2015, 7-14 Mar 2015, Big Sky, United States (pp. Article number 7119158). , 2015
Open this publication in new window or tab >>Introducing Radiation Tolerant Heterogeneous Computers for Small Satellites
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2015 (English)In: IEEE Aerospace Conference Proceedings, vol. 2015, 2015, Vol. 2015, p. Article number 7119158-Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents results and conclusions from design, manufacturing, and benchmarking of a heterogeneous computing low power fault tolerant computer, realized on an industrial Qseven® small form factor (SFF) platform. A heterogeneous computer in this context features multi-core processors (CPU), a graphical processing unit (GPU), and a field programmable gate array (FPGA). The x86 compatible CPU enables the use of vast amounts of commonly available software and operating systems, which can be used for space and harsh environments. The developed heterogeneous computer shares the same core architecture as game consoles such as Microsoft Xbox One and Sony Playstation 4 and has an aggregated computational performance in the TFLOP range. The processing power can be used for on-board intelligent data processing and higher degrees of autonomy in general. The module feature quad core 1.5 GHz 64 bit CPU (24 GFLOPs), 160 GPU shader cores (127 GFLOPs), and a 12 Mgate equivalent FPGA fabric with a safety critical ARM® Cortex-M3 MCU.

Keywords
Heterogeneous computing, heterogeneous system architecture, onboard processing
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-28127 (URN)10.1109/AERO.2015.7119158 (DOI)000380501302091 ()2-s2.0-84940703986 (Scopus ID)9781479953790 (ISBN)
Conference
IEEE Aerospace Conference 2015 IEEEAC2015, 7-14 Mar 2015, Big Sky, United States
Projects
GIMME3 - Semi-fault tolerant next generation high performance computer architecture based on screened industrial components
Available from: 2015-06-12 Created: 2015-06-08 Last updated: 2018-01-11Bibliographically approved
Behnam, M., Ciccozzi, F., Sjödin, M. & Bruhn, F. (2015). Software architecture for next generation hyperparallel cyber-physical hardware platforms: challenges and opportunities. In: ECSAW '15 Proceedings of the 2015 European Conference on Software Architecture Workshops: . Paper presented at 1st International Workshop on Software Architectures for Next-generation Cyber-physical Systems SANCS 2015, 07 Sep 2015, Dubrovnik/Cavtat, Croatia. , Article No. 19
Open this publication in new window or tab >>Software architecture for next generation hyperparallel cyber-physical hardware platforms: challenges and opportunities
2015 (English)In: ECSAW '15 Proceedings of the 2015 European Conference on Software Architecture Workshops, 2015, Vol. Article No. 19Conference paper, Published paper (Refereed)
Abstract [en]

We present what is destined to become the de-facto standard for hardware platforms for next generation cyber-physical systems. Heterogeneous System Architecture (HSA) is an initiative to harmonize the industry around a common architecture which is easier to program and is an open standard defining the key interfaces for parallel computation. Since HSA is supported by virtually all major players in the silicon market we can conjecture that HSA, with its capabilities and quirks, will highly influence both the hardware and software for next generation cyber-physical systems. In this paper we describe HSA and discuss how its nature will influence architectures of system software and application software. Specifically, we believe that the system software needs to both leverage the hyperparallel nature of HSA while providing predictable and efficient resource allocation to different parallel activities. The application software, on the other hand, should be isolated from the complexity of the hardware architecture but yet be able to efficiently use the full potential of the hyperparallel nature of HSA.

Series
ACM International Conference Proceeding Series
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-30032 (URN)10.1145/2797433.2797452 (DOI)2-s2.0-84958549426 (Scopus ID)978-1-4503-3393-1 (ISBN)
Conference
1st International Workshop on Software Architectures for Next-generation Cyber-physical Systems SANCS 2015, 07 Sep 2015, Dubrovnik/Cavtat, Croatia
Available from: 2015-12-18 Created: 2015-12-18 Last updated: 2016-03-03Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-8785-5380

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