2,013 research outputs found

    Neuromorphic hardware for somatosensory neuroprostheses

    Get PDF
    In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies

    FireFly: A High-Throughput and Reconfigurable Hardware Accelerator for Spiking Neural Networks

    Full text link
    Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high energy efficiency. With the introduction of the backpropagation algorithm and surrogate gradient, the structure of spiking neural networks has become more complex, and the performance gap with artificial neural networks has gradually decreased. However, most SNN hardware implementations for field-programmable gate arrays (FPGAs) cannot meet arithmetic or memory efficiency requirements, which significantly restricts the development of SNNs. They do not delve into the arithmetic operations between the binary spikes and synaptic weights or assume unlimited on-chip RAM resources by using overly expensive devices on small tasks. To improve arithmetic efficiency, we analyze the neural dynamics of spiking neurons, generalize the SNN arithmetic operation to the multiplex-accumulate operation, and propose a high-performance implementation of such operation by utilizing the DSP48E2 hard block in Xilinx Ultrascale FPGAs. To improve memory efficiency, we design a memory system to enable efficient synaptic weights and membrane voltage memory access with reasonable on-chip RAM consumption. Combining the above two improvements, we propose an FPGA accelerator that can process spikes generated by the firing neuron on-the-fly (FireFly). FireFly is implemented on several FPGA edge devices with limited resources but still guarantees a peak performance of 5.53TSOP/s at 300MHz. As a lightweight accelerator, FireFly achieves the highest computational density efficiency compared with existing research using large FPGA devices

    EuFRATE: European FPGA Radiation-hardened Architecture for Telecommunications

    Get PDF
    The EuFRATE project aims to research, develop and test radiation-hardening methods for telecommunication payloads deployed for Geostationary-Earth Orbit (GEO) using Commercial-Off-The-Shelf Field Programmable Gate Arrays (FPGAs). This project is conducted by Argotec Group (Italy) with the collaboration of two partners: Politecnico di Torino (Italy) and Technische Universit¨at Dresden (Germany). The idea of the project focuses on high-performance telecommunication algorithms and the design and implementation strategies for connecting an FPGA device into a robust and efficient cluster of multi-FPGA systems. The radiation-hardening techniques currently under development are addressing both device and cluster levels, with redundant datapaths on multiple devices, comparing the results and isolating fatal errors. This paper introduces the current state of the project’s hardware design description, the composition of the FPGA cluster node, the proposed cluster topology, and the radiation hardening techniques. Intermediate stage experimental results of the FPGA communication layer performance and fault detection techniques are presented. Finally, a wide summary of the project’s impact on the scientific community is provided

    A survey of trends and motivations regarding Communication Service Providers' metro area network implementations

    Full text link
    Relevance of research on telecommunications networks is predicated upon the implementations which it explicitly claims or implicitly subsumes. This paper supports researchers through a survey of Communications Service Providers current implementations within the metro area, and trends that are expected to shape the next-generation metro area network. The survey is composed of a quantitative component, complemented by a qualitative component carried out among field experts. Among the several findings, it has been found that service providers with large subscriber base sizes, are less agile in their response to technological change than those with smaller subscriber base sizes: thus, copper media are still an important component in the set of access network technologies. On the other hand, service providers with large subscriber base sizes are strongly committed to deploying distributed access architectures, notably using remote access nodes like remote OLT and remote MAC-PHY. This study also shows that the extent of remote node deployment for multi-access edge computing is about the same as remote node deployment for distributed access architectures, indicating that these two aspects of metro area networks are likely to be co-deployed.Comment: 84 page

    ACiS: smart switches with application-level acceleration

    Full text link
    Network performance has contributed fundamentally to the growth of supercomputing over the past decades. In parallel, High Performance Computing (HPC) peak performance has depended, first, on ever faster/denser CPUs, and then, just on increasing density alone. As operating frequency, and now feature size, have levelled off, two new approaches are becoming central to achieving higher net performance: configurability and integration. Configurability enables hardware to map to the application, as well as vice versa. Integration enables system components that have generally been single function-e.g., a network to transport data—to have additional functionality, e.g., also to operate on that data. More generally, integration enables compute-everywhere: not just in CPU and accelerator, but also in network and, more specifically, the communication switches. In this thesis, we propose four novel methods of enhancing HPC performance through Advanced Computing in the Switch (ACiS). More specifically, we propose various flexible and application-aware accelerators that can be embedded into or attached to existing communication switches to improve the performance and scalability of HPC and Machine Learning (ML) applications. We follow a modular design discipline through introducing composable plugins to successively add ACiS capabilities. In the first work, we propose an inline accelerator to communication switches for user-definable collective operations. MPI collective operations can often be performance killers in HPC applications; we seek to solve this bottleneck by offloading them to reconfigurable hardware within the switch itself. We also introduce a novel mechanism that enables the hardware to support MPI communicators of arbitrary shape and that is scalable to very large systems. In the second work, we propose a look-aside accelerator for communication switches that is capable of processing packets at line-rate. Functions requiring loops and states are addressed in this method. The proposed in-switch accelerator is based on a RISC-V compatible Coarse Grained Reconfigurable Arrays (CGRAs). To facilitate usability, we have developed a framework to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator. In the third work, we extend ACiS to support fused collectives and the combining of collectives with map operations. We observe that there is an opportunity of fusing communication (collectives) with computation. Since the computation can vary for different applications, ACiS support should be programmable in this method. In the fourth work, we propose that switches with ACiS support can control and manage the execution of applications, i.e., that the switch be an active device with decision-making capabilities. Switches have a central view of the network; they can collect telemetry information and monitor application behavior and then use this information for control, decision-making, and coordination of nodes. We evaluate the feasibility of ACiS through extensive RTL-based simulation as well as deployment in an open-access cloud infrastructure. Using this simulation framework, when considering a Graph Convolutional Network (GCN) application as a case study, a speedup of on average 3.4x across five real-world datasets is achieved on 24 nodes compared to a CPU cluster without ACiS capabilities

    Assembling Single RbCs Molecules with Optical Tweezers

    Get PDF
    Optical tweezer arrays are useful tools for manipulating single atoms and molecules. An exciting avenue for research with optical tweezers is using the interactions between polar molecules for quantum computation or quantum simulation. Molecules can be assembled in an optical tweezer array starting from pairs of atoms. The atoms must be initialised in the relative motional ground state of a common trap. This work outlines the design of a Raman sideband cooling protocol which is implemented to prepare an 87-Rubidium atom in the motional ground state of an 817 nm tweezer, and a 133-Caesium atom in the motional ground state of a 938 nm tweezer. The protocol circumvents strong heating and dephasing associated with the trap by operating at lower trap depths and cooling from outside the Lamb-Dicke regime. By analysing several sources of heating, we design and implement a merging sequence that transfers the Rb atom and the Cs atom to a common trap with minimal motional excitation. Subsequently, we perform a detailed characterisation of AC Stark shifts caused by the tweezer light, and identify several situations in which the confinement of the atom pair influences their interactions. Then, we demonstrate the preparation of a molecular bound state after an adiabatic ramp across a magnetic Feshbach resonance. Measurements of molecular loss rates provide evidence that the atoms are in fact associated during the merging sequence, before the magnetic field ramp. By preparing a weakly-bound molecule in an optical tweezer, we carry out important steps towards assembling an array of ultracold RbCs molecules in their rovibrational ground states

    Analog Photonics Computing for Information Processing, Inference and Optimisation

    Full text link
    This review presents an overview of the current state-of-the-art in photonics computing, which leverages photons, photons coupled with matter, and optics-related technologies for effective and efficient computational purposes. It covers the history and development of photonics computing and modern analogue computing platforms and architectures, focusing on optimization tasks and neural network implementations. The authors examine special-purpose optimizers, mathematical descriptions of photonics optimizers, and their various interconnections. Disparate applications are discussed, including direct encoding, logistics, finance, phase retrieval, machine learning, neural networks, probabilistic graphical models, and image processing, among many others. The main directions of technological advancement and associated challenges in photonics computing are explored, along with an assessment of its efficiency. Finally, the paper discusses prospects and the field of optical quantum computing, providing insights into the potential applications of this technology.Comment: Invited submission by Journal of Advanced Quantum Technologies; accepted version 5/06/202

    Toward Open Integrated Access and Backhaul with O-RAN

    Get PDF
    Millimeter wave (mmWave) communications has been recently standardized for use in the fifth generation (5G) of cellular networks, fulfilling the promise of multi-gigabit mobile throughput of current and future mobile radio network generations. In this context, the network densification required to overcome the difficult mmWave propagation will result in increased deployment costs. Integrated Access and Backhaul (IAB) has been proposed as an effective mean of reducing densification costs by deploying a wireless mesh network of base stations, where backhaul and access transmissions share the same radio technology. However, IAB requires sophisticated control mechanisms to operate efficiently and address the increased complexity. The Open Radio Access Network (RAN) paradigm represents the ideal enabler of RAN intelligent control, but its current specifications are not compatible with IAB. In this work, we discuss the challenges of integrating IAB into the Open RAN ecosystem, detailing the required architectural extensions that will enable dynamic control of 5G IAB networks. We implement the proposed integrated architecture into the first publiclyavailable Open-RAN-enabled experimental framework, which allows prototyping and testing Open-RAN-based solutions over end-to-end 5G IAB networks. Finally, we validate the framework with both ideal and realistic deployment scenarios exploiting the large-scale testing capabilities of publicly available experimental platforms

    Laser absorption spectroscopic tomography with a customised spatial resolution for combustion diagnosis

    Get PDF
    Combustion is a widely used energy conversion technology. However, post-combustion gas emissions have adverse effects on climate change. To address the urgent need for carbon neutrality, efforts are being made to develop cleaner fuels and improve combustion efficiency. Accurate in situ measurements of temperature and species concentration are crucial for analysing and diagnosing the combustion process. In industrial applications, probed-based measurement methods are commonly used to detect temperature and species concentration in the combustion, favoured by their simplicity. However, the probe-based techniques are limited in their spatial resolution, as only point-wise measurements can be provided by them. Additionally, their principle often restricts their temporal resolution, which limits their ability to capture the dynamics of the combustion process. To overcome these limitations, researchers are actively working on developing rapid and multi-dimensional in situ techniques for temperature and species concentration monitoring. Laser Absorption Spectroscopy (LAS) has gained significant attention for its non-intrusive nature and fast response in combustion diagnostics. LAS techniques use an emitter-receiver configuration to measure the line-of-sight light intensity absorbed by species in the gaseous medium. By collecting multiple line-of-sight measurements from different angles, LAS enables tomographic measurement of the combustion process. However, implementations of LAS tomography face challenges due to the physical dimensions of the emitter and receiver and the optical access to industrial combustors. These limitations lead to incomplete measurements, which are key factors of ill-posed problems and artefacts in the reconstructed images. The artefacts lead to inaccuracy and unreliability of the diagnostic results. Increasing physical sampling density is one of the most straightforward ways to alleviate the ill-posed problem caused by inadequate line-of-sight measurements. Improvements in sensors have been demonstrated in previous research, such as optimising laser beam arrangement and reducing the spacing of neighbouring laser beams. In this work, a novel design of a miniature and modular sensor is firstly introduced. It reduces the beam spacing between adjacent laser beams, allowing for a more precise and detailed reconstruction of temperature and species concentration distributions. Meanwhile, modular design allows for customisation and adaptation to various measurement requirements. This flexibility in deployment reduces the cost of the LAS technique. The application of small beam spacing in characterising the non-uniformity of the combustion process has also been demonstrated in this thesis. A multi-channel LAS sensor is developed and applied to exhaust measurements of a commercial auxiliary power unit. The results show that the small beam spacing allows a detailed understanding of the exhaust plume at the mixing zone between the exhaust gas and surrounding air. This spatial information can be used to improve the accuracy of temperature and species concentration measurements. On the other hand, prior knowledge, such as smoothness and sparsity of the measurement target and beam arrangement of the LAS tomographic sensor is used to provide extra physical information to the ill-posed inverse problem. To incorporate the beam arrangement information into the reconstruction process, a new meshing scheme is proposed in this thesis. The scheme dynamically allocates smaller meshes in the beam-dense regions and coarser meshes in the beam-loose regions. This adaptive meshing scheme ensures a finer resolution in detailing the combustion zone where the beams are closely spaced while maintaining the integrity of the physical model by using less resolved reconstruction in the bypass flows or regions where the beams are further apart. As a result, the proposed meshing scheme improves the reconstruction accuracy of the combustion zone. Overall, this PhD project designed and developed LAS tomographic sensors and methods that enable accurate and fast measurement of gas temperature and species concentration in combustion processes with a customised spatial resolution. The main contributions of this thesis include the design and prototyping of a miniature and modular optical sensor for flexible LAS tomography; the development of a multi-channel LAS sensor for simultaneously monitoring exhaust gas temperature and water vapour concentration in gas turbine engines; and the development of a size-adaptive hybrid meshing scheme to improve the reconstruction of target flow fields

    A review of networked microgrid protection: Architectures, challenges, solutions, and future trends

    Get PDF
    The design and selection of advanced protection schemes have become essential for the reliable and secure operation of networked microgrids. Various protection schemes that allow the correct operation of microgrids have been proposed for individual systems in different topologies and connections. Nevertheless, the protection schemes for networked microgrids are still in development, and further research is required to design and operate advanced protection in interconnected systems. The interconnection of these microgrids in different nodes with various interconnection technologies increases the fault occurrence and complicates the protection operation. This paper aims to point out the challenges in developing protection for networked microgrids, potential solutions, and research areas that need to be addressed for their development. First, this article presents a systematic analysis of the different microgrid clusters proposed since 2016, including several architectures of networked microgrids, operation modes, components, and utilization of renewable sources, which have not been widely explored in previous review papers. Second, the paper presents a discussion on the protection systems currently available for microgrid clusters, current challenges, and solutions that have been proposed for these systems. Finally, it discusses the trend of protection schemes in networked microgrids and presents some conclusions related to implementation
    • …
    corecore