258 research outputs found

    Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

    Get PDF
    ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

    NASA SpaceCube Next-Generation Artificial-Intelligence Computing for STP-H9-SCENIC on ISS

    Get PDF
    Recently, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have seen an exponential increase in interest from academia and industry that can be a disruptive, transformative development for future missions. Specifically, AI/ML concepts for edge computing can be integrated into future missions for autonomous operation, constellation missions, and onboard data analysis. However, using commercial AI software frameworks onboard spacecraft is challenging because traditional radiation-hardened processors and common spacecraft processors cannot provide the necessary onboard processing capability to effectively deploy complex AI models. Advantageously, embedded AI microchips being developed for the mobile market demonstrate remarkable capability and follow similar size, weight, and power constraints that could be imposed on a space-based system. Unfortunately, many of these devices have not been qualified for use in space. Therefore, Space Test Program - Houston 9 - SpaceCube Edge-Node Intelligent Collaboration (STP-H9-SCENIC) will demonstrate inflight, cutting-edge AI applications on multiple space-based devices for next-generation onboard intelligence. SCENIC will characterize several embedded AI devices in a relevant space environment and will provide NASA and DoD with flight heritage data and lessons learned for developers seeking to enable AI/ML on future missions. Finally, SCENIC also includes new CubeSat form-factor GPS and SDR cards for guidance and navigation

    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

    Fault Tolerant Nanosatellite Computing on a Budget

    Get PDF
    In this contribution, we present a CubeSat-compatible on-board computer (OBC) architecture that offers strong fault tolerance to enable the use of such spacecraft in critical and long-term missions. We describe in detail the design of our OBC’s breadboard setup, and document its composition from the component-level, all the way down to the software level. Fault tolerance in this OBC is achieved without resorting to radiation hardening, just intelligent through software. The OBC ages graceful, and makes use of FPGA-reconfiguration and mixed criticality. It can dynamically adapt to changing performance requirements throughout a space mission. We developed a proof-of-concept with several Xilinx Ultrascale and Ultrascale+ FPGAs. With the smallest Kintex Ultrascale+ KU3P device, we achieve 1.94W total power consumption at 300Mhz, well within the power budget range of current 2U CubeSats. To our knowledge, this is the first scalable and COTS-based, widely reproducible OBC solution which can offer strong fault coverage even for small CubeSats. To reproduce this OBC architecture, no custom-written, proprietary, or protected IP is needed, and the needed design tools are available free-of-charge to academics. All COTS components required to construct this architecture can be purchased on the open market, and are affordable even for academic and scientific CubeSat developers

    An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications

    Get PDF
    As reconfigurable devices\u27 capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART\u27s availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to five nines (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability

    OLT(RE)2: an On-Line on-demand Testing approach for permanent Radiation Effects in REconfigurable systems

    Get PDF
    Reconfigurable systems gained great interest in a wide range of application fields, including aerospace, where electronic devices are exposed to a very harsh working environment. Commercial SRAM-based FPGA devices represent an extremely interesting hardware platform for this kind of systems since they combine low cost with the possibility to utilize state-of-the-art processing power as well as the flexibility of reconfigurable hardware. In this paper we present OLT(RE)2: an on-line on-demand approach to test permanent faults induced by radiation in reconfigurable systems used in space missions. The proposed approach relies on a test circuit and on custom place-and-route algorithms. OLT(RE)2 exploits partial dynamic reconfigurability offered by today’s SRAM-based FPGAs to place the test circuits at run-time. The goal of OLT(RE)2 is to test unprogrammed areas of the FPGA before using them, thus preventing functional modules of the reconfigurable system to be placed on areas with faulty resources. Experimental results have shown that (i) it is possible to generate, place and route the test circuits needed to detect on average more than 99 % of the physical wires and on average about 97 % of the programmable interconnection points of an arbitrary large region of the FPGA in a reasonable time and that (ii) it is possible to download and run the whole test suite on the target device without interfering with the normal functioning of the system

    FPGA acceleration of a quantized neural network for remote-sensed cloud detection

    Get PDF
    The capture and transmission of remote-sensed imagery for Earth observation is both computationally and bandwidth expensive. In the analyses of remote-sensed imagery in the visual band, atmospheric cloud cover can obstruct up to two-thirds of observations, resulting in costly imagery being discarded. Mission objectives and satellite operational details vary; however, assuming a cloud-free observation requirement, a doubling of useful data downlinked with an associated halving of delivery cost is possible through effective cloud detection. A minimal-resource, real-time inference neural network is ideally suited to perform automatic cloud detection, both for pre-processing captured images prior to transmission and preventing unnecessary images being taken by larger payload sensors. Much of the hardware complexity of modern neural network implementations resides in high-precision floating-point calculation pipelines. In recent years, research has been conducted in identifying quantized, or low-integer precision equivalents to known deep learning models, which do not require the extensive resources of their floating-point, full-precision counterparts. Our work leverages existing research on binary and quantized neural networks to develop a real-time, remote-sensed cloud detection solution using a commodity field-programmable gate array. This follows on developments of the Forwards Looking Imager for predictive cloud detection developed by Craft Prospect, a space engineering practice based in Glasgow, UK. The synthesized cloud detection accelerator achieved an inference throughput of 358.1 images per second with a maximum power consumption of 2.4 W. This throughput is an order of magnitude faster than alternate algorithmic options for the Forwards Looking Imager at around one third reduction in classification accuracy, and approximately two orders of magnitude faster than the CloudScout deep neural network, deployed with HyperScout 2 on the European Space Agency PhiSat-1 mission. Strategies for incorporating fault tolerance mechanisms are expounded

    Fault-tolerant satellite computing with modern semiconductors

    Get PDF
    Miniaturized satellites enable a variety space missions which were in the past infeasible, impractical or uneconomical with traditionally-designed heavier spacecraft. Especially CubeSats can be launched and manufactured rapidly at low cost from commercial components, even in academic environments. However, due to their low reliability and brief lifetime, they are usually not considered suitable for life- and safety-critical services, complex multi-phased solar-system-exploration missions, and missions with a longer duration. Commercial electronics are key to satellite miniaturization, but also responsible for their low reliability: Until 2019, there existed no reliable or fault-tolerant computer architectures suitable for very small satellites. To overcome this deficit, a novel on-board-computer architecture is described in this thesis.Robustness is assured without resorting to radiation hardening, but through software measures implemented within a robust-by-design multiprocessor-system-on-chip. This fault-tolerant architecture is component-wise simple and can dynamically adapt to changing performance requirements throughout a mission. It can support graceful aging by exploiting FPGA-reconfiguration and mixed-criticality.  Experimentally, we achieve 1.94W power consumption at 300Mhz with a Xilinx Kintex Ultrascale+ proof-of-concept, which is well within the powerbudget range of current 2U CubeSats. To our knowledge, this is the first COTS-based, reproducible on-board-computer architecture that can offer strong fault coverage even for small CubeSats.European Space AgencyComputer Systems, Imagery and Medi

    A Sustainable Autonomic Architecture for Organically Reconfigurable Computing Systems

    Get PDF
    A Sustainable Autonomic Architecture for Organically Reconfigurable Computing System based on SRAM Field Programmable Gate Arrays (FPGAs) is proposed, modeled analytically, simulated, prototyped, and measured. Low-level organic elements are analyzed and designed to achieve novel self-monitoring, self-diagnosis, and self-repair organic properties. The prototype of a 2-D spatial gradient Sobel video edge-detection organic system use-case developed on a XC4VSX35 Xilinx Virtex-4 Video Starter Kit is presented. Experimental results demonstrate the applicability of the proposed architecture and provide the infrastructure to quantify the performance and overcome fault-handling limitations. Dynamic online autonomous functionality restoration after a malfunction or functionality shift due to changing requirements is achieved at a fine granularity by exploiting dynamic Partial Reconfiguration (PR) techniques. A Genetic Algorithm (GA)-based hardware/software platform for intrinsic evolvable hardware is designed and evaluated for digital circuit repair using a variety of well-accepted benchmarks. Dynamic bitstream compilation for enhanced mutation and crossover operators is achieved by directly manipulating the bitstream using a layered toolset. Experimental results on the edge-detector organic system prototype have shown complete organic online refurbishment after a hard fault. In contrast to previous toolsets requiring many milliseconds or seconds, an average of 0.47 microseconds is required to perform the genetic mutation, 4.2 microseconds to perform the single point conventional crossover, 3.1 microseconds to perform Partial Match Crossover (PMX) as well as Order Crossover (OX), 2.8 microseconds to perform Cycle Crossover (CX), and 1.1 milliseconds for one input pattern intrinsic evaluation. These represent a performance advantage of three orders of magnitude over the JBITS software framework and more than seven orders of magnitude over the Xilinx design flow. Combinatorial Group Testing (CGT) technique was combined with the conventional GA in what is called CGT-pruned GA to reduce repair time and increase system availability. Results have shown up to 37.6% convergence advantage using the pruned technique. Lastly, a quantitative stochastic sustainability model for reparable systems is formulated to evaluate the Sustainability of FPGA-based reparable systems. This model computes at design-time the resources required for refurbishment to meet mission availability and lifetime requirements in a given fault-susceptible missions. By applying this model to MCNC benchmark circuits and the Sobel Edge-Detector in a realistic space mission use-case on Xilinx Virtex-4 FPGA, we demonstrate a comprehensive model encompassing the inter-relationships between system sustainability and fault rates, utilized, and redundant hardware resources, repair policy parameters and decaying reparability

    SpaceCube: A NASA Family of Reconfigurable Hybrid On-Board Science Data Processors

    Get PDF
    SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science-data processing systems developed at NASA Goddard Space Flight Center. This presentation provides an overview to the Future In-Space Operations Telecon Working Group
    • …
    corecore