104 research outputs found

    Software defined networking for radio telescopes: a case study on the applicability of SDN for MeerKAT

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    Scientific instruments like radio telescopes depend on high-performance networks for internal data exchange. The high bandwidth data exchange between the components of a radio telescope makes use of multicast networking. Complex multicast networks are hard to maintain and grow, and specific installations require modified network switches. This study evaluates Software Defined Networking (SDN) for use in the MeerKAT radio telescope to alleviate the management complexity and allow for a vendor-neutral implementation. The purpose of this dissertation is to verify that an SDN multicast network can produce suitable paths for data flow through the network and to see if such an implementation is easier to maintain and grow. There is little literature regarding SDN for radio telescope networks; however, there is considerable work where different aspects of SDN are discussed and demonstrated for video streaming. SDN with multicast for video streaming, although simpler, forms the background research. Considerable work was put into understanding and documenting the different aspects of a radio telescope affecting the data network. The telescope network controller generates the OpenFlow rules required by the SDN controller and is a new concept introduced in this work. The telescope network controller is fitted with two placement algorithms to demonstrate its flexibility. Both algorithms are suitable for the expected workload, but they produce very different traffic patterns. The two algorithms are not compared to one another, they were created to demonstrate the ease of adding domain specific knowledge to an SDN. The telescope network controller makes it easy to introduce and use new flow placement algorithms, thus making traffic engineering feasible for the radio telescope. Complex multicast networks are easier to maintain and grow with SDN. SDN allows customised packet forwarding rules typically unattainable with standard routing and other standard network protocols and implementations. A radio telescope with a software-defined data network is resilient, easier to maintain, vendor-neutral, and possesses advanced traffic engineering mechanisms

    Improving low latency applications for reconfigurable devices

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    This thesis seeks to improve low latency application performance via architectural improvements in reconfigurable devices. This is achieved by improving resource utilisation and access, and by exploiting the different environments within which reconfigurable devices are deployed. Our first contribution leverages devices deployed at the network level to enable the low latency processing of financial market data feeds. Financial exchanges transmit messages via two identical data feeds to reduce the chance of message loss. We present an approach to arbitrate these redundant feeds at the network level using a Field-Programmable Gate Array (FPGA). With support for any messaging protocol, we evaluate our design using the NASDAQ TotalView-ITCH, OPRA, and ARCA data feed protocols, and provide two simultaneous outputs: one prioritising low latency, and one prioritising high reliability with three dynamically configurable windowing methods. Our second contribution is a new ring-based architecture for low latency, parallel access to FPGA memory. Traditional FPGA memory is formed by grouping block memories (BRAMs) together and accessing them as a single device. Our architecture accesses these BRAMs independently and in parallel. Targeting memory-based computing, which stores pre-computed function results in memory, we benefit low latency applications that rely on: highly-complex functions; iterative computation; or many parallel accesses to a shared resource. We assess square root, power, trigonometric, and hyperbolic functions within the FPGA, and provide a tool to convert Python functions to our new architecture. Our third contribution extends the ring-based architecture to support any FPGA processing element. We unify E heterogeneous processing elements within compute pools, with each element implementing the same function, and the pool serving D parallel function calls. Our implementation-agnostic approach supports processing elements with different latencies, implementations, and pipeline lengths, as well as non-deterministic latencies. Compute pools evenly balance access to processing elements across the entire application, and are evaluated by implementing eight different neural network activation functions within an FPGA.Open Acces

    Perbaikan Internal Blocking Jaringan Interkoneksi Banyak Tingkat Topologi Omega 8x8 dengan Algoritma Look-Ahead

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    Jaringan interkoneksi banyak tingkat (Multistage Interconnection Network/MIN) hingga saat ini digunakan sebagai switching pada sentral-sentral dalam sistem-sistem Telekomunikasi. Disamping itu MIN juga digunakan sebagai switch penghubung antara prosesor dan modul memori pada sistem-sistem Komputer. Penggunaan MIN semakin diminati karena penghematan jumlah crosspoint yang dimilikinya dibandingkan dengan switch matriks konvensional yang jumlah crosspoint-nya lebih banyak. Selain itu MIN mudah dikontrol dan mampu mendukung koneksi input-output dalam skala besar. Namun MIN bersifat internal blocking, sehingga dibutuhkan suatu cara untuk menjadikannya non-blocking atau mengurangi persentase internal blocking yang dimilikinya. Salah satu cara yang dilakukan untuk maksud tersebut adalah menggunakan algoritma. Pada tulisan ini dibahas algoritma Look-Ahead untuk mengurangi internal blocking MIN topologi Omega 8x8. Dari 2 buah contoh yang dianalisis, untuk permutasi dengan koneksi input-output yang uniform tanpa algoritma Look-Ahead diperoleh hasil bahwa internal blocking sebesar 62,5% dan jika menggunakan algoritma Look-Ahead internal blocking turun menjadi menjadi 25%. Sedangkan dengan permutasi yang memiliki koneksi yang non uniform persentase internal blocking-nya menjadi lebih tinggi yaitu sebesar 87,5% jika tanpa algoritma Look-Ahead, sedangkan dengan algoritma Look-Ahead turun menjadi 50%. Jadi algoritma Look-Ahead sangat mengurangi kegagalan koneksi input-output sebuah permutasi atau dengan kata lain mengurangi internal blocking sebuah jaringan MIN secara signifikan

    Performance evaluation of data-driven techniques for the softwarized and agnostic management of an NĂ—N photonic switch

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    The emerging Software Defined Networking (SDN) paradigm paves the way for flexible and automatized management at each layer. The SDN-enabled optical network requires each network element’s software abstraction to enable complete control by the centralized network controller. Nowadays, silicon photonics due to its low energy consumption, low latency, and small footprint is a promising technology for implementing photonic switching topologies, enabling transparent lightpath routing in re-configurable add-drop multiplexers. To this aim, a model for the complete management of photonic switching systems’ control states is fundamental for network control. Typically, photonics-based switches are structured by exploiting the modern technology of Photonic Integrated Circuit (PIC) that enables complex elementary cell structures to be driven individually. Thus PIC switches’ control states are combinations of a large set of elementary controls, and their definition is a challenging task. In this scenario, we propose the use of several data-driven techniques based on Machine Learning (ML) to model the control states of a PIC N×N photonic switch in a completely blind manner. The proposed ML-based techniques are trained and tested in a completely topological and technological agnostic way, and we envision their application in a real-time control plane. The proposed techniques’ scalability and accuracy are validated by considering three different switching topologies: the Honey-Comb Rearrangeable Optical Switch (HCROS), Spanke-Beneš, and the Beneš network. Excellent results in terms of predicting the control states are achieved for all of the considered topologies

    Machine Learning for Multi-Layer Open and Disaggregated Optical Networks

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    LIPIcs, Volume 248, ISAAC 2022, Complete Volume

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    LIPIcs, Volume 248, ISAAC 2022, Complete Volum

    Advances in Optical Amplifiers

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    Optical amplifiers play a central role in all categories of fibre communications systems and networks. By compensating for the losses exerted by the transmission medium and the components through which the signals pass, they reduce the need for expensive and slow optical-electrical-optical conversion. The photonic gain media, which are normally based on glass- or semiconductor-based waveguides, can amplify many high speed wavelength division multiplexed channels simultaneously. Recent research has also concentrated on wavelength conversion, switching, demultiplexing in the time domain and other enhanced functions. Advances in Optical Amplifiers presents up to date results on amplifier performance, along with explanations of their relevance, from leading researchers in the field. Its chapters cover amplifiers based on rare earth doped fibres and waveguides, stimulated Raman scattering, nonlinear parametric processes and semiconductor media. Wavelength conversion and other enhanced signal processing functions are also considered in depth. This book is targeted at research, development and design engineers from teams in manufacturing industry, academia and telecommunications service operators
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