https://www.mdu.se/

mdu.sePublikationer
Ändra sökning
Avgränsa sökresultatet
1 - 16 av 16
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Binios, A.
    et al.
    Aalto University, Espoo, Finland.
    Leverone, F.
    Delft University of Technology, Delft, Netherlands.
    Stavrakakis, H. -A
    National Technical University of Athens, Athens, Greece.
    Tsog, Nandinbaatar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Haslam, S.
    Finnish Meteorological Institute, Helsinki, Finland.
    Dalbins, J.
    University of Tartu, Tartu, Estonia.
    Ivaškeviciute-Povilauskiene, R.
    Vilnius University, Vilnius, Lithuania.
    Jain, A.
    University of Tartu, Tartu, Estonia.
    Keskinen, M.
    Aalto University, Espoo, Finland.
    Kivastik, J.
    University of Tartu, Tartu, Estonia.
    Mikkola, J.
    Aalto University, Espoo, Finland.
    Oro, E.
    University of Tartu, Tartu, Estonia.
    Ruusmann, L.
    University of Tartu, Tartu, Estonia.
    Sate, J.
    Stockholm University, Stockholm, Sweden.
    Pai, K.
    University of Tartu, Tartu, Estonia.
    Geppert, W.
    Stockholm University, Stockholm, Sweden.
    Praks, J.
    Aalto University, Espoo, Finland.
    Laufer, R.
    Baylor University, Waco, TX, United States.
    Moon compact satellite for hazard assessment (MOOCHA) - Proposing an international Earth-Moon small satellite constellation2019Ingår i: Proceedings of the International Astronautical Congress, IAC, International Astronautical Federation, IAF , 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    The recent developments in space exploration have reinstated the Moon as a primary target for near future space missions. The principal reasons include the Moon being the closest test bed and analogue for planetary space missions and the prospect of scientific lunar bases and orbital stations within the next decade. Previous space missions have vastly improved our understanding on hazards of human spaceflights but not fully regarding the threats affecting a prospective lunar base or orbital station. The micrometeorite hazard has been partially addressed as an issue which can potentially impact both astronauts' health and safety as well as create issues for lunar bases and orbital stations, such as degradation or permanent damage of equipment and facilities. The current understanding is based partly on dust and micrometeoroid flux measurements and impact flash observations. However, observations with improved spatial and temporal resolution are imperative for advancing existing hazard models. In this paper, a mission concept of a constellation of nanosatellites is proposed that can both observe larger parts of cis-lunar and trans-lunar space while providing higher temporal resolution. Nanosatellite missions are a cost-effective solution providing data for significant improvement of our current understanding of lunar micrometeoroid flux models, and thus directly the scale of hazards caused by micrometeoroid impacts to future lunar missions. Additionally, such a distributed constellation mission will offer countless opportunities for academia, students and young scientists worldwide. The mission concept (Moon Compact Satellite for Hazard Assessment - MOOCHA) is a result of the Nordic-European Astrobiology Campus Summer School 2018 themed “Microsatellites in Planetary and Atmospheric Research” and was further developed during the 2019 follow-up summer school “Design of Small Satellite Missions for Planetary Studies”, both taking place in Tartu, Estonia and co-organized by the Stockholm University Astrobiology Centre, the University of Tartu, the European Astrobiology Campus and the Nordic Network of Astrobiology and supported by European Union's European Regional Development Fund and Estonia.

  • 2.
    Bruhn, Fredrik
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB Publ, Uppsala, Sweden.;Bruhnspace AB, Uppsala, Sweden..
    Tsog, Nandinbaatar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Kunkel, Fabian
    Unibap AB Publ, Uppsala, Sweden..
    Flordal, Oskar
    Unibap AB Publ, Uppsala, Sweden..
    Troxel, Ian
    Troxel Aerosp Ind Inc, Gainesville, USA..
    Enabling radiation tolerant heterogeneous GPU-based onboard data processing in space2020Ingår i: CEAS Space Journal, ISSN 1868-2502, E-ISSN 1868-2510, Vol. 12, nr 4, s. 551-564Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The last decade has seen a dramatic increase in small satellite missions for commercial, public, and government intelligence applications. Given the rapid commercialization of constellation-driven services in Earth Observation, situational domain awareness, communications including machine-to-machine interface, exploration etc., small satellites represent an enabling technology for a large growth market generating truly Big Data. Examples of modern sensors that can generate very large amounts of data are optical sensing, hyperspectral, Synthetic Aperture Radar (SAR), and Infrared imaging. Traditional handling and downloading of Big Data from space requires a large onboard mass storage and high bandwidth downlink with a trend towards optical links. Many missions and applications can benefit significantly from onboard cloud computing similarly to Earth-based cloud services. Hence, enabling space systems to provide near real-time data and enable low latency distribution of critical and time sensitive information to users. In addition, the downlink capability can be more effectively utilized by applying more onboard processing to reduce the data and create high value information products. This paper discusses current implementations and roadmap for leveraging high performance computing tools and methods on small satellites with radiation tolerant hardware. This includes runtime analysis with benchmarks of convolutional neural networks and matrix multiplications using industry standard tools (e.g., TensorFlow and PlaidML). In addition, a 1/2 CubeSat volume unit (0.5U) (10 x 10 x 5 cm(3)) cloud computing solution, called SpaceCloud (TM) iX5100 based on AMD 28 nm APU technology is presented as an example of heterogeneous computer solution. An evaluation of the AMD 14 nm Ryzen APU is presented as a candidate for future advanced onboard processing for space vehicles.

  • 3.
    Danielsson, Jakob
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Tsog, Nandinbaatar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Kunnappilly, Ashalatha
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    A systematic mapping study on real-Time cloud services2018Ingår i: Proceedings - 11th IEEE/ACM International Conference on Utility and Cloud Computing Companion, UCC Companion 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, s. 245-251, artikel-id 8605787Konferensbidrag (Refereegranskat)
    Abstract [en]

    Cloud computing is relatively a new technique to host and use the services and applications from the internet. Although it offers a multitude of advantages like scalability, low operating cost, accessibility and maintainability, etc., they are often not utilized to the fullest due to the lack of timeliness property associated with the cloud. Cloud services are mainly designed to maximize throughput and utilization of resources and hence incorporating predictable execution time properties in to the cloud is arduous. Nevertheless, cloud still remains a highly attractive platform for hosting real-Time applications and services owing to features like elasticity, multi-Tenancy, ability to survive hardware failures, virtualization support and abstraction layer support which provides flexibility and portability. In order for real-Time safety-critical applications to exploit the potential of cloud computing, it is essential to ensure the predictable real-Time behavior of cloud services. In this paper, we perform a systematic mapping study on real-Time cloud services to identify the current research directions and potential research gaps. Our study focuses on analyzing the current architectures and software techniques that are available at present to incorporate real-Time property of the cloud services. We also aim at investigating the current challenges involved in realizing a predictable real-Time behavior of cloud services. 

  • 4.
    Johansson, Stephanie Liza
    et al.
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Said, Hassan Omer
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Forsberg, Håkan
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Tsog, Nandinbaatar
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Flordal, O.
    Unibap AB, Chief Technology Officer, Uppsala, Sweden.
    Comparing Ext4 and ZFS for Onboard Data Processing: A Systematic Mapping and Experimental Evaluation2023Ingår i: Proc. European Data Handl. Data Process. Conf. Space, EDHPC, Institute of Electrical and Electronics Engineers Inc. , 2023Konferensbidrag (Refereegranskat)
    Abstract [en]

    Selecting the correct file system is critical for space applications where risks are present. This study systematically maps and tests Ext4 versus ZFS for onboard data processing on the iX10-100 and iX5-100 payload processors. The test sets are presented along with results on several performance metrics. The conclusion is that both ZFS and Ext4 are useful, but based on certain considerations of onboard data processing, Ext4 is better than the other.

  • 5.
    Tsog, Nandinbaatar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Improving On-Board Data Processing using CPU-GPU Heterogeneous Architectures for Real-Time Systems2019Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    Denna avhandling undersöker effektiviteten hos heterogena datorarkitekturer i realtidssystem. Målet med avhandlingen är tvåfaldigt. Till att börja med, att undersöka olika egenskaper hos plattformar baserade på Heterogeneous System Architecture, med fokus på datorprestanda och strömförbrukning. Undersökningen är inriktad på tekniker som kan öka datorbehandlingssystemen ombord i satelliter och rymdskepp. För det andra förbättra användningen av heterogena arkitekturer genom att införa en teknik för statisk allokering av parallella programsegment.

    Undersökningen och den experimentella utvärderingen visar att vår metod för effektiv användning av GPU-allokering för parallella programsegment är den mest energieffektiva jämfört med någon annan studerad allokering. Undersökningarna har genomförts i olika typer av miljöer, såsom processisolerad miljö, olika mjukvarustackar, inklusive kernel, och olika uppsättningsscenarier. Utvärderingsresultaten indikerar dessutom att en balanserad användning av heterogena beräkningsenheter (CPU och GPU) kan förbättra schemaläggningen för vissa program upp till 90% jämfört med de tidigare föreslagna allokeringsteknikerna.

    Ladda ner fulltext (pdf)
    fulltext
  • 6.
    Tsog, Nandinbaatar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Space Computing using COTS Heterogeneous Platforms: Intelligent On-Board Data Processing in Space Systems2021Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    Rymddata berikar rymdaktiviteter som utforskningar i djupa rymden och intelligent beslutsfattande i omloppsbana. Medvetenheten om rymddatorn ökar på grund av de tekniska framstegen inom högpresterande commercial off-the-shelf (COTS). Utrymme erbjuder utvecklare, forskare och människor en komplex, begränsad och utmanande miljö. Utmaningarna är storlek, vikt och effekt (SWaP), realtidskrav, kommunikationsbegränsningar samt strålningseffekter. Forskningen som bedrivs i denna avhandling syftar till att undersöka och stödja intelligent omborddatabehandling med hjälp av COTS heterogena datorplattformar i rymdsystem. Dessa plattformar bäddar in minst en Central Processing Unit (CPU) och en Graphics Processing Unit (GPU) på samma chip.

    Huvudmålet för den forskning som presenteras i denna avhandling är tvåfaldigt. För det första att undersöka de heterogena dataplattformarna i syfte att föreslå en lösning för att hantera ovan nämnda utmaningar i rymdsystem. För det andra, för att komplettera den föreslagna lösningen med nya schemaläggningstekniker för realtidsapplikationer som körs på COTS heterogena plattformar under tuffa miljöer som rymden.

    De föreslagna teknikerna är baserade på systemmodellen som överväger användningen av alternativa utföranden av parallella segment av uppgifter. Även om avlastning av ett parallellt segment till en parallell beräkningsenhet (t.ex. GPU) förbättrar de bästa tillämpningstiderna för de flesta applikationer, kan det öka svarstiderna för uppgifter i vissa applikationer på grund av överanvändning av GPU. Därför kan användningen av den föreslagna uppgiftsmodellen vara en nyckel för att minska responstiderna för uppgifter och förbättra systemets schemaläggning. De serverbaserade föreslagna schemaläggningsteknikerna stöder den föreslagna uppgiftsmodellen genom att garantera exekveringsplatsen för parallella segment på CPU (er).

    Den experimentella utvärderingen som utförs i denna avhandling visar att den föreslagna uppgiftsmodellen kan förbättra schemaläggningen för realtidssystem upp till 90% med statisk tilldelning av applikationer. Dessutom kan den dynamiska tilldelningsmetoden som använder den serverbaserade schemaläggningen med den föreslagna uppgiftsmodellen förbättra schemaläggningen med upp till 16%. Slutligen presenterar avhandlingen ett simuleringsverktyg som simulerar applikationer i realtid med hjälp av den föreslagna uppgiftsmodellen samtidigt som man beaktar de olika nivåerna av strålningstolerans för olika behandlingsenheter.

    Ladda ner fulltext (pdf)
    fulltext
  • 7.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Becker, Matthias
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Behnam, Moris
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Nolin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Static Allocation of Parallel Tasks to Improve Schedulability in CPU-GPU Heterogeneous Real-Time Systems2019Konferensbidrag (Refereegranskat)
    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%.

  • 8.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Behnam, Moris
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Nolin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Intelligent Data Processing using In-Orbit Advanced Algorithms on Heterogeneous System Architecture2018Ingår i: IEEE Aerospace Conference 2018 IEEEAC2018, 2018, s. 1-8Konferensbidrag (Refereegranskat)
    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.

  • 9.
    Tsog, Nandinbaatar
    et al.
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Gallardo, Marielle
    Volvo Autonomous Solutions, Sweden.
    Chakraborty, Sweta
    Mälardalens universitet.
    Martinson, Torbjörn
    Volvo Autonomous Solutions, Sweden.
    Hengl, Alexandra
    Mälardalens universitet.
    Moberg, Magnus
    Volvo Autonomous Solutions, Sweden.
    Sen, Adem
    Mälardalens universitet.
    Ahmed, Mobyen Uddin
    Volvo Autonomous Solutions, Sweden.
    Begum, Shahina
    Volvo Autonomous Solutions, Sweden.
    Behnam, Moris
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Mubeen, Saad
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Supporting Autonomous Vehicle Applications on the Heterogeneous System Architecture2021Ingår i: ACM International Conference Proceeding Series, Association for Computing Machinery , 2021Konferensbidrag (Refereegranskat)
    Abstract [en]

    The contemporary processors are unable to meet the increasing data-intensive and computation-demanding requirements in autonomous vehicle software applications. Recently, the new Heterogeneous System Architecture (HSA) has emerged as a promising solution to meet these requirements. The HSA reduces the latency of data exchange between the compute units and cache-coherent shared memory, which is not supported by the non-HSA compliant heterogeneous platforms with acceleration support. The main goal of the paper is to investigate the performance gain by the HSA and conduct a comparative evaluation of the HSA and non-HSA compliant heterogeneous platforms. The paper aims at evaluating these platforms by using two computation-intensive software functions in autonomous vehicles, namely the object detection and vehicle movement. In order to achieve this goal, the CUDA-accelerated source code of the functions is ported from a non-HSA compliant heterogeneous platform to the HSA platform. In this regard, the paper presents the architecture of a proof-of-concept prototype and provides evaluation using the prototype.

  • 10.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Mubeen, Saad
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Behnam, Moris
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. ES (Embedded Systems).
    Simulation and Analysis of In-Orbit Applications under Radiation Effects on COTS Platforms2021Ingår i: 42nd IEEE Aerospace Conference 2021 IEEEAC2021, 2021Konferensbidrag (Refereegranskat)
    Abstract [en]

    Radiation effects research is crucial as it defines risk to both human bodies and spacecraft. Employing radiation-hardened products is one way to mitigate radiation effects on in-orbit systems. However, radiation effects prohibit most of the state-of-the-art commercial off-the-shelf (COTS) technologies from use in space. Furthermore, radiation effects on software components are less studied compared to hardware components. In this work, we introduce a simulation tool that analyzes the impact of radiation effects on schedulability of task sets executing on COTS system-on-chip (SoC) platforms in the in-orbit systems. In order to provide a meaningful verification environment, single-event effects (SEEs) are introduced as aleatory disturbances characterized by probability distribution of occurrence using their predefined models. The tool supports interoperability with several other tools as it uses the extensible markup language (XML) model files for input and output, i.e., for importing input task sets and radiation effects and exporting the simulation results.

  • 11.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Mubeen, Saad
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB, Sweden.
    Behnam, Moris
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Offloading Accelerator-intensive Workloads in CPU-GPU Heterogeneous Processors2021Ingår i: 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021, 2021Konferensbidrag (Refereegranskat)
    Abstract [en]

    Autonomous vehicular systems require computer vision and intelligent on-board decision making functionalities that include a mix of sequential and parallel workloads. The execution times of the workloads and power consumption in these functionalities can be lowered by utilizing the accelerators (e.g., GPU) instead of running the workloads entirely on the host processing units (CPU). However, allocating all the parallelizable workload to accelerators can create a computation bottleneck in the accelerators that, in turn, can have an adverse effect on schedulability of the systems. This paper presents a novel framework that can allocate the accelerate-intensive workloads to the accelerators as well as to the non-accelerated host processing units. Within the context of this framework, the paper introduces five offloading techniques to mitigate the accelerator-intensive workloads by utilizing excess capacity of non-accelerated processing units under dynamic scheduling in CPU-GPU heterogeneous processors. The proposed techniques are evaluated using simulation experiments. The evaluation results indicate that one of the proposed techniques can achieve up to 16% improvement in schedulability of the task sets compared to the traditional non-offloading technique.

  • 12.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Mubeen, Saad
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB (Publ.).
    A Trade-Off between Computing Power and Energy Consumption of On-Board Data Processing in GPU Accelerated In-Orbit Space Systems2021Ingår i: Transactions of the Japan Society for Aeronautical and Space Sciences, Aerospace Technology Japan, E-ISSN 1884-0485, Vol. 19, nr 5, s. 700-708, artikel-id 19.700Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    On-board data processing is one of the prior on-orbit activities that 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 higher energy consumption compared to traditional on-board space systems. This is because the traditional space systems employ simple processing units such as single-core microprocessors as the systems do not require heavy data processing. Moreover, solving the radiation hardness problem is crucial in space, and adopting a new processing unit is challenging.

    In this paper, we consider a Graphics Processing Unit (GPU) accelerated in-orbit space 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 energy consumption and computing potential using this heterogeneous computing method in our GPU accelerated in-orbit space systems.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.

  • 13.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Nolin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Using Docker in Process Level Isolation for Heterogeneous Computing on GPU Accelerated On-Board Data Processing Systems2019Konferensbidrag (Refereegranskat)
    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.

  • 14.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB, Uppsala, Sweden.
    A Trade-Off between Computing Power and Energy Consumption of On-Board Data Processing in GPU Accelerated Real-Time Systems2019Konferensbidrag (Refereegranskat)
    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.

  • 15.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Advancing On-Board Big Data Processing Using Heterogeneous System Architecture2018Ingår i: ESA/CNES 4S Symposium 4S 2018, 2018Konferensbidrag (Refereegranskat)
  • 16.
    Tsog, Nandinbaatar
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Sjödin, Mikael
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. ES (Embedded Systems).
    Bruhn, Fredrik
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. Unibap AB, Sweden.
    Using Heterogeneous Computing on GPU Accelerated Systems to Advance On-Board Data Processing2019Ingår i: European Workshop on On-Board Data Processing 2019 OBDP2019, 2019Konferensbidrag (Refereegranskat)
1 - 16 av 16
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf