527 research outputs found
An Error-Detection and Self-Repairing Method for Dynamically and Partially Reconfigurable Systems
Reconfigurable systems are gaining an increasing interest in the domain of safety-critical applications, for example in the space and avionic domains. In fact, the capability of reconfiguring the system during run-time execution and the high computational power of modern Field Programmable Gate Arrays (FPGAs) make these devices suitable for intensive data processing tasks. Moreover, such systems must also guarantee the abilities of self-awareness, self-diagnosis and self-repair in order to cope with errors due to the harsh conditions typically existing in some environments. In this paper we propose a selfrepairing method for partially and dynamically reconfigurable systems applied at a fine-grain granularity level. Our method is able to detect, correct and recover errors using the run-time capabilities offered by modern SRAM-based FPGAs. Fault injection campaigns have been executed on a dynamically reconfigurable system embedding a number of benchmark circuits. Experimental results demonstrate that our method achieves full detection of single and multiple errors, while significantly improving the system availability with respect to traditional error detection and correction methods
Exploiting partial reconfiguration through PCIe for a microphone array network emulator
The current Microelectromechanical Systems (MEMS) technology enables the deployment of relatively low-cost wireless sensor networks composed of MEMS microphone arrays for accurate sound source localization. However, the evaluation and the selection of the most accurate and power-efficient network’s topology are not trivial when considering dynamic MEMS microphone arrays. Although software simulators are usually considered, they consist of high-computational intensive tasks, which require hours to days to be completed. In this paper, we present an FPGA-based platform to emulate a network of microphone arrays. Our platform provides a controlled simulated acoustic environment, able to evaluate the impact of different network configurations such as the number of microphones per array, the network’s topology, or the used detection method. Data fusion techniques, combining the data collected by each node, are used in this platform. The platform is designed to exploit the FPGA’s partial reconfiguration feature to increase the flexibility of the network emulator as well as to increase performance thanks to the use of the PCI-express high-bandwidth interface. On the one hand, the network emulator presents a higher flexibility by partially reconfiguring the nodes’ architecture in runtime. On the other hand, a set of strategies and heuristics to properly use partial reconfiguration allows the acceleration of the emulation by exploiting the execution parallelism. Several experiments are presented to demonstrate some of the capabilities of our platform and the benefits of using partial reconfiguration
New Design Techniques for Dynamic Reconfigurable Architectures
L'abstract è presente nell'allegato / the abstract is in the attachmen
Using Relocatable Bitstreams for Fault Tolerance
This research develops a method for relocating reconfigurable modules on the Virtex-II (Pro) family of Field Programmable Gate Arrays (FPGAs). A bitstream translation program is developed which correctly changes the location of a partial bitstream that implements a module on the FPGA. To take advantage of relocatable modules, three fault-tolerance circuit designs are developed and tested. This circuit can operate through a fault by efficiently removing the faulty module and replacing it with a relocated module without faults. The FPGA can recover from faults at a known location, without the need for external intervention using an embedded fault recovery system. The recovery system uses an internal PowerPC to relocate the modules and reprogram the FPGA. Due to the limited architecture of the target FPGA and Xilinx tool errors, an FPGA with automatic fault recovery could not be demonstrated. However, the various components needed to do this type of recovery have been implemented and demonstrated individually
Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack
Field Programmable Gate Array (FPGA) devices offer a suitable platform for survivable hardware architectures in mission-critical systems. In this dissertation, active dynamic redundancy-based fault-handling techniques are proposed which exploit the dynamic partial reconfiguration capability of SRAM-based FPGAs. Self-adaptation is realized by employing reconfiguration in detection, diagnosis, and recovery phases. To extend these concepts to semiconductor aging and process variation in the deep submicron era, resilient adaptable processing systems are sought to maintain quality and throughput requirements despite the vulnerabilities of the underlying computational devices. A new approach to autonomous fault-handling which addresses these goals is developed using only a uniplex hardware arrangement. It operates by observing a health metric to achieve Fault Demotion using Recon- figurable Slack (FaDReS). Here an autonomous fault isolation scheme is employed which neither requires test vectors nor suspends the computational throughput, but instead observes the value of a health metric based on runtime input. The deterministic flow of the fault isolation scheme guarantees success in a bounded number of reconfigurations of the FPGA fabric. FaDReS is then extended to the Priority Using Resource Escalation (PURE) online redundancy scheme which considers fault-isolation latency and throughput trade-offs under a dynamic spare arrangement. While deep-submicron designs introduce new challenges, use of adaptive techniques are seen to provide several promising avenues for improving resilience. The scheme developed is demonstrated by hardware design of various signal processing circuits and their implementation on a Xilinx Virtex-4 FPGA device. These include a Discrete Cosine Transform (DCT) core, Motion Estimation (ME) engine, Finite Impulse Response (FIR) Filter, Support Vector Machine (SVM), and Advanced Encryption Standard (AES) blocks in addition to MCNC benchmark circuits. A iii significant reduction in power consumption is achieved ranging from 83% for low motion-activity scenes to 12.5% for high motion activity video scenes in a novel ME engine configuration. For a typical benchmark video sequence, PURE is shown to maintain a PSNR baseline near 32dB. The diagnosability, reconfiguration latency, and resource overhead of each approach is analyzed. Compared to previous alternatives, PURE maintains a PSNR within a difference of 4.02dB to 6.67dB from the fault-free baseline by escalating healthy resources to higher-priority signal processing functions. The results indicate the benefits of priority-aware resiliency over conventional redundancy approaches in terms of fault-recovery, power consumption, and resource-area requirements. Together, these provide a broad range of strategies to achieve autonomous recovery of reconfigurable logic devices under a variety of constraints, operating conditions, and optimization criteria
Automation tools for demonstration of goal directed and self-repairing flight control systems
The coupling of expert systems and control design and analysis techniques are documented to provide a realizable self repairing flight control system. Key features of such a flight control system are identified and a limited set of rules for a simple aircraft model are presented
An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications
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
Embedded electronic systems driven by run-time reconfigurable hardware
Abstract
This doctoral thesis addresses the design of embedded electronic systems based on run-time reconfigurable hardware technology –available through SRAM-based FPGA/SoC devices– aimed at contributing to enhance the life quality of the human beings. This work does research on the conception of the system architecture and the reconfiguration engine that provides to the FPGA the capability of dynamic partial reconfiguration in order to synthesize, by means of hardware/software co-design, a given application partitioned in processing tasks which are multiplexed in time and space, optimizing thus its physical implementation –silicon area, processing time, complexity, flexibility, functional density, cost and power consumption– in comparison with other alternatives based on static hardware (MCU, DSP, GPU, ASSP, ASIC, etc.). The design flow of such technology is evaluated through the prototyping of several engineering applications (control systems, mathematical coprocessors, complex image processors, etc.), showing a high enough level of maturity for its exploitation in the industry.Resumen
Esta tesis doctoral abarca el diseño de sistemas electrĂłnicos embebidos basados en tecnologĂa hardware dinámicamente reconfigurable –disponible a travĂ©s de dispositivos lĂłgicos programables SRAM FPGA/SoC– que contribuyan a la mejora de la calidad de vida de la sociedad. Se investiga la arquitectura del sistema y del motor de reconfiguraciĂłn que proporcione a la FPGA la capacidad de reconfiguraciĂłn dinámica parcial de sus recursos programables, con objeto de sintetizar, mediante codiseño hardware/software, una determinada aplicaciĂłn particionada en tareas multiplexadas en tiempo y en espacio, optimizando asĂ su implementaciĂłn fĂsica –área de silicio, tiempo de procesado, complejidad, flexibilidad, densidad funcional, coste y potencia disipada– comparada con otras alternativas basadas en hardware estático (MCU, DSP, GPU, ASSP, ASIC, etc.). Se evalĂşa el flujo de diseño de dicha tecnologĂa a travĂ©s del prototipado de varias aplicaciones de ingenierĂa (sistemas de control, coprocesadores aritmĂ©ticos, procesadores de imagen, etc.), evidenciando un nivel de madurez viable ya para su explotaciĂłn en la industria.Resum
Aquesta tesi doctoral estĂ orientada al disseny de sistemes electrònics empotrats basats en tecnologia hardware dinĂ micament reconfigurable –disponible mitjançant dispositius lògics programables SRAM FPGA/SoC– que contribueixin a la millora de la qualitat de vida de la societat. S’investiga l’arquitectura del sistema i del motor de reconfiguraciĂł que proporcioni a la FPGA la capacitat de reconfiguraciĂł dinĂ mica parcial dels seus recursos programables, amb l’objectiu de sintetitzar, mitjançant codisseny hardware/software, una determinada aplicaciĂł particionada en tasques multiplexades en temps i en espai, optimizant aixĂ la seva implementaciĂł fĂsica –à rea de silici, temps de processat, complexitat, flexibilitat, densitat funcional, cost i potència dissipada– comparada amb altres alternatives basades en hardware estĂ tic (MCU, DSP, GPU, ASSP, ASIC, etc.). S’evalĂşa el fluxe de disseny d’aquesta tecnologia a travĂ©s del prototipat de varies aplicacions d’enginyeria (sistemes de control, coprocessadors aritmètics, processadors d’imatge, etc.), demostrant un nivell de maduresa viable ja per a la seva explotaciĂł a la indĂşstria
Dynamic path planning for reconfigurable rovers using a multi-layered grid
Autonomy on rovers is desirable in order to extend the traversed distance, and therefore, maximize the number
of places visited during the mission. It depends heavily on the information that is available for the traversed
surface on other planet. This information may come from the vehicle’s sensors as well as from orbital images.
Besides, future exploration missions may consider the use of reconfigurable rovers, which are able to execute
multiple locomotion modes to better adapt to different terrains. With these considerations, a path planning
algorithm based on the Fast Marching Method is proposed. Environment information coming from different
sources is used on a grid formed by two layers. First, the Global Layer with a low resolution, but high extension
is used to compute the overall path connecting the rover and the desired goal, using a cost function that takes
advantage of the rover locomotion modes. Second, the Local Layer with higher resolution but limited distance
is used where the path is dynamically repaired because of obstacle presence. Finally, we show simulation and
field test results based on several reconfigurable and non-reconfigurable rover prototypes and a experimental
terrain
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