Microprocessor fault-tolerance via on-the-fly partial reconfiguration

This paper presents a novel approach to exploit FPGA dynamic partial reconfiguration to improve the fault tolerance of complex microprocessor-based systems, with no need to statically reserve area to host redundant components. The proposed method not only improves the survivability of the system by allowing the online replacement of defective key parts of the processor, but also provides performance graceful degradation by executing in software the tasks that were executed in hardware before a fault and the subsequent reconfiguration happened. The advantage of the proposed approach is that thanks to a hardware hypervisor, the CPU is totally unaware of the reconfiguration happening in real-time, and there's no dependency on the CPU to perform it. As proof of concept a design using this idea has been developed, using the LEON3 open-source processor, synthesized on a Virtex 4 FPG

Detailed Modeling and Reliability Analysis of Fault-Tolerant Processor Arrays

Recent advances in VLSI/WSI technology have led to the design of processor arrays with a large number of processing elements confined in small areas. The use of redundancy to increase fault-tolerance has the effect of reducing the ratio of area dedicated to processing elements over the area occupied by other resources in the array. The assumption of fault-free hardware support (switches, buses, interconnection links, etc.,), leads at best to conservative reliability estimates. However, detailed modeling entails not only an explosive growth in the model state space but also a difficult model construction process. To address the latter problem, a systematic method to construct Markov models for the reliability evaluation of processor arrays is proposed. This method is based on the premise that the fault behavior of a processor array can be modeled by a Stochastic Petri Net (SPN). However, in order to obtain a more compact representation, a set of attributes is associated with each transition in the Petri net model. This representation is referred to as a Modified Stochastic Petri Net (MSPN) model. A MSPN allows the construction of the corresponding Markov model as the reachability graph is being generated. The Markov model generated can include the effect of failures of several different components of the array as well as the effect of a peculiar distribution of faults when the reconfiguration occurs. Specific reconfiguration schemes such as Successive Row Elimination (SRE), Alternate Row-Column Elimination (ARCE) and Direct Reconfiguration (DR), are analyze

Algorithm Based Fault Tolerance in Massively Parallel Systems

An A complex computer system consists of billions of transistors, miles of wires, and many interactions with an unpredictable environment. Correct results must be produced despite faults that dynamically occur in some of these components. Many techniques have been developed for fault tolerant computation. General purpose methods are independent of the application, yet incur an overhead cost which may be unacceptable for massively parallel systems. Algorithm-specific methods, which can operate at lower cost, are a developing alternative [1, 72]. This paper first reviews the general-purpose approach and then focuses on the algorithm-specific method, with an eye toward massively parallel processors. Algorithm-based fault tolerance has the attraction of low overhead; furthermore it addresses both the detection and also the correction problems. The principle is to build low-cost checking and correcting mechanism based exclusively on the redundancies inherent in the system

High Performance VLSI Signal Processing: Innovative Architectures and Algorithms

The book intends to address the important aspects of high-performance signal processing with a focus on the recent development of VLSI technology for signal processing.\nThe editors collect much of all the research efforts and findings that have made high performance implementation of signal processing possible in the last decade in two volumes

Enhancing Real-time Embedded Image Processing Robustness on Reconfigurable Devices for Critical Applications

Nowadays, image processing is increasingly used in several application fields, such as biomedical, aerospace, or automotive. Within these fields, image processing is used to serve both non-critical and critical tasks. As example, in automotive, cameras are becoming key sensors in increasing car safety, driving assistance and driving comfort. They have been employed for infotainment (non-critical), as well as for some driver assistance tasks (critical), such as Forward Collision Avoidance, Intelligent Speed Control, or Pedestrian Detection. The complexity of these algorithms brings a challenge in real-time image processing systems, requiring high computing capacity, usually not available in processors for embedded systems. Hardware acceleration is therefore crucial, and devices such as Field Programmable Gate Arrays (FPGAs) best fit the growing demand of computational capabilities. These devices can assist embedded processors by significantly speeding-up computationally intensive software algorithms. Moreover, critical applications introduce strict requirements not only from the real-time constraints, but also from the device reliability and algorithm robustness points of view. Technology scaling is highlighting reliability problems related to aging phenomena, and to the increasing sensitivity of digital devices to external radiation events that can cause transient or even permanent faults. These faults can lead to wrong information processed or, in the worst case, to a dangerous system failure. In this context, the reconfigurable nature of FPGA devices can be exploited to increase the system reliability and robustness by leveraging Dynamic Partial Reconfiguration features. The research work presented in this thesis focuses on the development of techniques for implementing efficient and robust real-time embedded image processing hardware accelerators and systems for mission-critical applications. Three main challenges have been faced and will be discussed, along with proposed solutions, throughout the thesis: (i) achieving real-time performances, (ii) enhancing algorithm robustness, and (iii) increasing overall system's dependability. In order to ensure real-time performances, efficient FPGA-based hardware accelerators implementing selected image processing algorithms have been developed. Functionalities offered by the target technology, and algorithm's characteristics have been constantly taken into account while designing such accelerators, in order to efficiently tailor algorithm's operations to available hardware resources. On the other hand, the key idea for increasing image processing algorithms' robustness is to introduce self-adaptivity features at algorithm level, in order to maintain constant, or improve, the quality of results for a wide range of input conditions, that are not always fully predictable at design-time (e.g., noise level variations). This has been accomplished by measuring at run-time some characteristics of the input images, and then tuning the algorithm parameters based on such estimations. Dynamic reconfiguration features of modern reconfigurable FPGA have been extensively exploited in order to integrate run-time adaptivity into the designed hardware accelerators. Tools and methodologies have been also developed in order to increase the overall system dependability during reconfiguration processes, thus providing safe run-time adaptation mechanisms. In addition, taking into account the target technology and the environments in which the developed hardware accelerators and systems may be employed, dependability issues have been analyzed, leading to the development of a platform for quickly assessing the reliability and characterizing the behavior of hardware accelerators implemented on reconfigurable FPGAs when they are affected by such faults

Design and Validation for FPGA Trust under Hardware Trojan Attacks

Field programmable gate arrays (FPGAs) are being increasingly used in a wide range of critical applications, including industrial, automotive, medical, and military systems. Since FPGA vendors are typically fabless, it is more economical to outsource device production to off-shore facilities. This introduces many opportunities for the insertion of malicious alterations of FPGA devices in the foundry, referred to as hardware Trojan attacks, that can cause logical and physical malfunctions during field operation. The vulnerability of these devices to hardware attacks raises serious security concerns regarding hardware and design assurance. In this paper, we present a taxonomy of FPGA-specific hardware Trojan attacks based on activation and payload characteristics along with Trojan models that can be inserted by an attacker. We also present an efficient Trojan detection method for FPGA based on a combined approach of logic-testing and side-channel analysis. Finally, we propose a novel design approach, referred to as Adapted Triple Modular Redundancy (ATMR), to reliably protect against Trojan circuits of varying forms in FPGA devices. We compare ATMR with the conventional TMR approach. The results demonstrate the advantages of ATMR over TMR with respect to power overhead, while maintaining the same or higher level of security and performances as TMR. Further improvement in overhead associated with ATMR is achieved by exploiting reconfiguration and time-sharing of resources

Testing and reconfiguration of VLSI linear arrays

AbstractAchieving fault tolerance through incorporation of redundancy and reconfiguration is quite common. In this paper we study the fault tolerance of linear arrays of N processors with k bypass links whose maximum length is g. We consider both arrays with bidirectional links and unidirectional links.We first consider the problem of testing whether a set of n faulty processors is catastrophic, i.e., precludes reconfiguration. We provide new testing algorithms which improve and generalize known testing algorithms. For bidirectional arrays we provide an O(kn) time testing algorithm and for unidirectional arrays we provide an O(n) time algorithm for the case k = 1, and an O(kn log k) time algorithm, for the case k 1.When the fault pattern is not catastrophic we study the problem of finding an optimal reconfiguration of the array. We consider optimality with respect to two parameters: the size of the reconfigured array and the number of redundant links to activate. Considering optimality with respect to the size of the reconfigured array, we prove that the problem is NP-hard in the strong sense if the bypass links are bidirectional, while it can be solved in O(kng) time if the bypass links are unidirectional. Considering optimality with respect to the number of bypass links to activate, we prove that the problem can be solved in O(kn) time if the bypass links are bidirectional, and in O(kng) time if the bypass links are unidirectional

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Fault Tolerant Nanosatellite Computing on a Budget

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