Monthly Archives: June 2015

Experiences Implementing Tinuso in gem5

Experiences Implementing Tinuso in gem5

  • Maxwell Walter, Pascal Schleuniger, Andreas Erik Hindborg, Carl Christian Kjaergaard, Nicklas Bo Jensen, and Sven Karlsson. Experiences Implementing Tinuso in gem5. Second gem5 User Workshop, 2015.
    [BibTeX] [Abstract] [Download handouts]

    In recent years, high performance computing systems have started to make use of FPGA based hardware accelerators to improve performance and power properties. While FPGAs are becoming more competitive in terms of speed, power efficiency, and logic capacity, the effort required to program these heterogeneous systems has limited their impact. To address these issues, our lab has developed Tinuso, which is is a lightweight processor architecture we designed and optimized for implementation on FPGAs. Tinuso is designed to be multi-core and configurable for specific applications. To identify an ideal multi-core configuration for an application, we need a powerful simulation environment that can efficiently explore the design space. We use gem5 as our simulation platform, and have added support for our processor architecture. For Tinuso, we follow a hardware/software co-design approach in order to keep the hardware resource usage low. This results in processor cores that deliver significantly higher performance while requiring fewer hardware resources than commer- cial processor implementations. However, Tinuso is in many ways different from other processor architectures. To maintain high operating frequencies Tinuso includes a large number of delay slots; four for standard branch instructions. Tinuso also includes delay slots on other instructions, where the result is not available for a number of cycles after the instruction has been executed. To complicate matters, certain instruction patterns have a different number of delay slots. For example, the compare instruction normally has two delay slots, but only one when followed by a branch. We have modified the gem5 in-order CPU model to support a dynamic commit delay. This allows us to fetch instructions in the proper order, which maintains cache behavior, but still simulate the behavior of Tinuso?s delay slots. Along the way, we have found gem5 to be a very flexible platform that we have been able to use for our design space exploration and compiler verification.

    @Misc{2015-06-MAXWELL,
    title = {{Experiences Implementing Tinuso in gem5}},
    author = {Maxwell Walter and Pascal Schleuniger and Andreas Erik Hindborg and Carl Christian Kjaergaard and Nicklas Bo Jensen and Sven Karlsson},
    howpublished = {Second gem5 User Workshop},
    address = {Portland, Oregon, USA},
    date = {2015-06-14},
    year = {2015},
    handouts = {http://www.m5sim.org/wiki/images/f/f5/2015_ws_16_gem5-workshop_mwalter.pptx},
    abstract = {In recent years, high performance computing systems have started to make use of FPGA based hardware accelerators to improve performance and power properties. While FPGAs are becoming more competitive in terms of speed, power efficiency, and logic capacity, the effort required to program these heterogeneous systems has limited their impact. To address these issues, our lab has developed Tinuso, which is is a lightweight processor architecture we designed and optimized for implementation on FPGAs. Tinuso is designed to be multi-core and configurable for specific applications. To identify an ideal multi-core configuration for an application, we need a powerful simulation environment that can efficiently explore the design space. We use gem5 as our simulation platform, and have added support for our processor architecture.
    For Tinuso, we follow a hardware/software co-design approach in order to keep the hardware resource usage low. This results in processor cores that deliver significantly higher performance while requiring fewer hardware resources than commer- cial processor implementations. However, Tinuso is in many ways different from other processor architectures. To maintain high operating frequencies Tinuso includes a large number of delay slots; four for standard branch instructions.
    Tinuso also includes delay slots on other instructions, where the result is not available for a number of cycles after the instruction has been executed. To complicate matters, certain instruction patterns have a different number of delay slots. For example, the compare instruction normally has two delay slots, but only one when followed by a branch. We have modified the gem5 in-order CPU model to support a dynamic commit delay. This allows us to fetch instructions in the proper order, which maintains cache behavior, but still simulate the behavior of Tinuso?s delay slots. Along the way, we have found gem5 to be a very flexible platform that we have been able to use for our design space exploration and compiler verification.}
    }

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State of the Akvario Project

State of the Akvario Project

  • Andreas Erik Hindborg, Nicklas Bo Jensen, Pascal Schleuniger, and Sven Karlsson. State of the Akvario Project. 6th Workshop on Architectural Research Prototyping (WARP 2015), 2015.
    [BibTeX] [Download PDF]
    @Misc{2015-06-HINDBORG,
    title = {{State of the Akvario Project}},
    author = {Andreas Erik Hindborg and Nicklas Bo Jensen and Pascal Schleuniger and Sven Karlsson},
    howpublished = {6th Workshop on Architectural Research Prototyping (WARP 2015)},
    address = {Portland, Oregon, USA},
    date = {2015-06-14},
    year = {2015},
    url = {http://www.csl.cornell.edu/warp2015/abstracts/hindborg-akvario-warp2015.pdf}
    }

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Connectivity of Large-Scale WSNs in Fading Environments under Different Routing Mechanisms

Connectivity of Large-Scale WSNs in Fading Environments under Different Routing Mechanisms

  • Prodromos-Vasileios Mekikis, Elli Kartsakli, Aris S. Lalos, Angelos Antonopoulos, Luis Alonso, and Christos Verikoukis. Connectivity of Large-Scale WSNs in Fading Environments under Different Routing Mechanisms. In Proceedings of IEEE International Conference on Communications (ICC 2015), pages 6553-6558, London, UK, 2015. doi:10.1109/ICC.2015.7249369
    [BibTeX] [Abstract]

    As the number of nodes in wireless sensor networks (WSNs) increases, new challenges have to be faced in order to maintain their performance. A fundamental requirement of several applications is the correct transmission of the measurements to their final destinations. Thus, it is crucial to guarantee a high probability of connectivity, which characterizes the ability of every node to report to the fusion center. This network metric is strongly affected by both the fading characteristics and the different routing protocols that are used for the dissemination of data. In this paper, we study the probability of a network to be fully connected for two widely employed routing mechanisms, namely unicast and K-anycast. The analytical derivations and the simulations evaluate the trade-offs among the different routing mechanisms and provide useful guidelines on the design of WSNs.

    @InProceedings{2015-06-MEKIKIS,
    author = {Prodromos-Vasileios Mekikis and Elli Kartsakli and Aris S. Lalos and Angelos Antonopoulos and Luis Alonso and Christos Verikoukis},
    title = {{Connectivity of Large-Scale WSNs in Fading Environments under Different Routing Mechanisms}},
    booktitle = {{Proceedings of IEEE International Conference on Communications (ICC 2015)}},
    date = {2015-06-08/2015-06-12},
    year = {2015},
    pages = {6553-6558},
    doi = {10.1109/ICC.2015.7249369},
    address = {London, UK},
    abstract = {As the number of nodes in wireless sensor networks (WSNs) increases, new challenges have to be faced in order to maintain their performance. A fundamental requirement of several applications is the correct transmission of the measurements to their final destinations. Thus, it is crucial to guarantee a high probability of connectivity, which characterizes the ability of every node to report to the fusion center. This network metric is strongly affected by both the fading characteristics and the different routing protocols that are used for the dissemination of data. In this paper, we study the probability of a network to be fully connected for two widely employed routing mechanisms, namely unicast and K-anycast. The analytical derivations and the simulations evaluate the trade-offs among the different routing mechanisms and provide useful guidelines on the design of WSNs.}
    }

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Adaptive Cooperative Network Coding based MAC protocol for Device-to-Device Communication

Adaptive Cooperative Network Coding based MAC protocol for Device-to-Device Communication

  • Eftychia Datsika, Angelos Antonopoulos, Nizar Zorba, and Christos Verikoukis. Adaptive Cooperative Network Coding based MAC protocol for Device-to-Device Communication. In IEEE Proceedings of International Conference on Communications (ICC 2015), pages 6996-7001, London, UK, 2015. doi:10.1109/ICC.2015.7249441
    [BibTeX] [Abstract]

    Device-to-Device (D2D) communication allows the direct connection of mobile devices in a cellular network. In D2D networking, cooperative communication is inherent due to the proximity of the devices that are able to overhear and forward information. Particularly, adjacent devices can act as relays and assist the communication of other devices. Network Coding (NC) can further increase the cooperation gains, since a number of packets can be encoded and transmitted together. However, the contention among multiple relays causes channel access issues that must be regulated by effective Medium Access Control (MAC) protocols. In this context, we propose an Adaptive Cooperative Network Coding-based MAC (ACNC-MAC) protocol that utilizes cooperative relaying and exploits NC opportunities in a D2D topology. Both analytical and simulation results show that the proposed protocol is advantageous in terms of energy efficiency without sacrificing the Quality of Service (QoS).

    @InProceedings{2015-06-DATISKA,
    author = {Eftychia Datsika and Angelos Antonopoulos and Nizar Zorba and Christos Verikoukis},
    title = {{Adaptive Cooperative Network Coding based MAC protocol for Device-to-Device Communication}},
    booktitle = {{IEEE Proceedings of International Conference on Communications (ICC 2015)}},
    date = {2015-06-08/2015-06-12},
    address = {London, UK},
    year = {2015},
    pages = {6996-7001},
    doi = {10.1109/ICC.2015.7249441},
    abstract = {Device-to-Device (D2D) communication allows the direct connection of mobile devices in a cellular network. In D2D networking, cooperative communication is inherent due to the proximity of the devices that are able to overhear and forward information. Particularly, adjacent devices can act as relays and assist the communication of other devices. Network Coding (NC) can further increase the cooperation gains, since a number of packets can be encoded and transmitted together. However, the contention among multiple relays causes channel access issues that must be regulated by effective Medium Access Control (MAC) protocols. In this context, we propose an Adaptive Cooperative Network Coding-based MAC (ACNC-MAC) protocol that utilizes cooperative relaying and exploits NC opportunities in a D2D topology. Both analytical and simulation results show that the proposed protocol is advantageous in terms of energy efficiency without sacrificing the Quality of Service (QoS).}
    }

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Self-reconfiguring distributed vision

Self-reconfiguring distributed vision

  • Andrea Cavallaro. Self-reconfiguring distributed vision. Plenary talk at International work conference on artificial neural networks (IWANN), 2015.
    [BibTeX] [Abstract]

    Assistive technologies, environmental monitoring, search and rescue operations, security and entertainment applications will considerably benefit from the sensing capabilities offered by emerging networks of wireless cameras. These networks are composed of cameras that may be wearable or mounted on robotic platforms and can autonomously sense, compute, decide and communicate. These cameras and their vision algorithms need to adapt their hardware and algorithmic parameters in response to unknown or dynamic environments and to changes in their task(s), i.e. they need to self-reconfigure. Cooperation among the cameras may lead to adaptive and task-dependent visual coverage of a scene or to increased robustness and accuracy in object localization under varying poses or illumination conditions. In this talk I will cover challenges and current solutions in self-reconfiguring distributed vision using networks of wireless cameras. In particular, I will discuss how cameras may learn to improve their performance. Moreover, I will present recent methods that allow cameras to move and to interact locally forming coalitions adaptively in order to provide coordinated decisions under resource and physical constraints.

    @Misc{2015-06-CAVALLARO,
    author = {Andrea Cavallaro},
    title = {{Self-reconfiguring distributed vision}},
    howpublished = {Plenary talk at International work conference on artificial neural networks (IWANN)},
    date = {2015-06-11},
    year = {2015},
    address = {Palma de Mallorca},
    abstract = {Assistive technologies, environmental monitoring, search and rescue operations, security and entertainment applications will considerably benefit from the sensing capabilities offered by emerging networks of wireless cameras. These networks are composed of cameras that may be wearable or mounted on robotic platforms and can autonomously sense, compute, decide and communicate. These cameras and their vision algorithms need to adapt their hardware and algorithmic parameters in response to unknown or dynamic environments and to changes in their task(s), i.e. they need to self-reconfigure. Cooperation among the cameras may lead to adaptive and task-dependent visual coverage of a scene or to increased robustness and accuracy in object localization under varying poses or illumination conditions. In this talk I will cover challenges and current solutions in self-reconfiguring distributed vision using networks of wireless cameras. In particular, I will discuss how cameras may learn to improve their performance. Moreover, I will present recent methods that allow cameras to move and to interact locally forming coalitions adaptively in order to provide coordinated decisions under resource and physical constraints.}
    }

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