Testing the bus guardian unit of the FTMP

Fault-tolerant multiprocessor (FTMP) operation is discussed. Fault-modeling in the bus guardian units (BGUs) is covered. Testing the BGU is discussed. A testing algorithm is proposed

Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing

Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered

Reliable Low-Latency and Low-Complexity Viterbi Architectures Benchmarked on ASIC and FPGA

The Viterbi algorithm is commonly applied in a number of sensitive usage models including decoding convolutional codes used in communications such as satellite communication, cellular relay, and wireless local area networks. Moreover, the algorithm has been applied to automatic speech recognition and storage devices. In this thesis, efficient error detection schemes for architectures based on low-latency, low-complexity Viterbi decoders are presented. The merit of the proposed schemes is that reliability requirements, overhead tolerance, and performance degradation limits are embedded in the structures and can be adapted accordingly. We also present three variants of recomputing with encoded operands and its modifications to detect both transient and permanent faults, coupled with signature-based schemes. The instrumented decoder architecture has been subjected to extensive error detection assessments through simulations, and application-specific integrated circuit (ASIC) [32nm library] and field-programmable gate array (FPGA) [Xilinx Virtex-6 family] implementations for benchmark. The proposed fine-grained approaches can be utilized based on reliability objectives and performance/implementation metrics degradation tolerance

On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices

Redundancy management for efficient fault recovery in NASA's distributed computing system

The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance

Readiness of Quantum Optimization Machines for Industrial Applications

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum annealing machines, has the potential to outperform current classical optimization algorithms implemented on CMOS technologies. The benchmarking of these devices has been controversial. Initially, random spin-glass problems were used, however, these were quickly shown to be not well suited to detect any quantum speedup. Subsequently, benchmarking shifted to carefully crafted synthetic problems designed to highlight the quantum nature of the hardware while (often) ensuring that classical optimization techniques do not perform well on them. Even worse, to date a true sign of improved scaling with the number of problem variables remains elusive when compared to classical optimization techniques. Here, we analyze the readiness of quantum annealing machines for real-world application problems. These are typically not random and have an underlying structure that is hard to capture in synthetic benchmarks, thus posing unexpected challenges for optimization techniques, both classical and quantum alike. We present a comprehensive computational scaling analysis of fault diagnosis in digital circuits, considering architectures beyond D-wave quantum annealers. We find that the instances generated from real data in multiplier circuits are harder than other representative random spin-glass benchmarks with a comparable number of variables. Although our results show that transverse-field quantum annealing is outperformed by state-of-the-art classical optimization algorithms, these benchmark instances are hard and small in the size of the input, therefore representing the first industrial application ideally suited for testing near-term quantum annealers and other quantum algorithmic strategies for optimization problems.Comment: 22 pages, 12 figures. Content updated according to Phys. Rev. Applied versio

Education and Research Integration of Emerging Multidisciplinary Medical Devices Security

Traditional embedded systems such as secure smart cards and nano-sensor networks have been utilized in various usage models. Nevertheless, emerging secure deeply-embedded systems, e.g., implantable and wearable medical devices, have comparably larger “attack surface”. Specifically, with respect to medical devices, a security breach can be life-threatening (for which adopting traditional solutions might not be practical due to tight constraints of these often-battery-powered systems), and unlike traditional embedded systems, it is not only a matter of financial loss. Unfortunately, although emerging cryptographic engineering research mechanisms for such deeply-embedded systems have started solving this critical, vital problem, university education (at both graduate and undergraduate level) lags comparably. One of the pivotal reasons for such a lag is the multi-disciplinary nature of the emerging security bottlenecks. Based on the aforementioned motivation, in this work, at Rochester Institute of Technology, we present an effective research and education integration strategy to overcome this issue in one of the most critical deeply-embedded systems, i.e., medical devices. Moreover, we present the results of two years of implementation of the presented strategy at graduate-level through fault analysis attacks, a variant of side-channel attacks. We note that the authors also supervise an undergraduate student and the outcome of the presented work has been assessed for that student as well; however, the emphasis is on graduate-level integration. The results of the presented work show the success of the presented methodology while pinpointing the challenges encountered compared to traditional embedded system security research/teaching integration of medical devices security. We would like to emphasize that our integration approaches are general and scalable to other critical infrastructures as well

Integrating emerging cryptographic engineering research and security education

Unlike traditional embedded systems such as secure smart cards, emerging secure deeply embedded systems, e.g., implantable and wearable medical devices, have larger “attack surface”. A security breach in such systems which are embedded deeply in human bodies or objects would be life-threatening, for which adopting traditional solutions might not be practical due to tight constraints of these often-battery-powered systems. Unfortunately, although emerging cryptographic engineering research mechanisms have started solving this critical problem, university education (at both graduate and undergraduate level) lags comparably. One of the pivotal reasons for such a lag is the multi-disciplinary nature of the emerging security bottlenecks (mathematics, engineering, science, and medicine, to name a few). Based on the aforementioned motivation, in this paper, we present an effective research and education integration strategy to overcome this issue at Rochester Institute of Technology. Moreover, we present the results of more than one year implementation of the presented strategy at graduate level through “side-channel analysis attacks” case studies. The results of the presented work show the success of the presented methodology while pinpointing the challenges encountered compared to traditional embedded system security research/teaching integration

Multidisciplinary Approaches and Challenges in Integrating Emerging Medical Devices Security Research and Education

Traditional embedded systems such as secure smart cards and nano-sensor networks have been utilized in various usage models. Nevertheless, emerging secure deeply-embedded systems, e.g., implantable and wearable medical devices, have comparably larger “attack surface”. Specifically, with respect to medical devices, a security breach can be life-threatening (for which adopting traditional solutions might not be practical due to tight constraints of these often-battery-powered systems), and unlike traditional embedded systems, it is not only a matter of financial loss. Unfortunately, although emerging cryptographic engineering research mechanisms for such deeply-embedded systems have started solving this critical, vital problem, university education (at both graduate and undergraduate level) lags comparably. One of the pivotal reasons for such a lag is the multi-disciplinary nature of the emerging security bottlenecks. Based on the aforementioned motivation, in this work, at Rochester Institute of Technology, we present an effective research and education integration strategy to overcome this issue in one of the most critical deeply-embedded systems, i.e., medical devices. Moreover, we present the results of two years of implementation of the presented strategy at graduate-level through fault analysis attacks, a variant of side-channel attacks. We note that the authors also supervise an undergraduate student and the outcome of the presented work has been assessed for that student as well; however, the emphasis is on graduate-level integration. The results of the presented work show the success of the presented methodology while pinpointing the challenges encountered compared to traditional embedded system security research/teaching integration of medical devices security. We would like to emphasize that our integration approaches are general and scalable to other critical infrastructures as well

Integration of tools for the Design and Assessment of High-Performance, Highly Reliable Computing Systems (DAHPHRS), phase 1

Systems for Space Defense Initiative (SDI) space applications typically require both high performance and very high reliability. These requirements present the systems engineer evaluating such systems with the extremely difficult problem of conducting performance and reliability trade-offs over large design spaces. A controlled development process supported by appropriate automated tools must be used to assure that the system will meet design objectives. This report describes an investigation of methods, tools, and techniques necessary to support performance and reliability modeling for SDI systems development. Models of the JPL Hypercubes, the Encore Multimax, and the C.S. Draper Lab Fault-Tolerant Parallel Processor (FTPP) parallel-computing architectures using candidate SDI weapons-to-target assignment algorithms as workloads were built and analyzed as a means of identifying the necessary system models, how the models interact, and what experiments and analyses should be performed. As a result of this effort, weaknesses in the existing methods and tools were revealed and capabilities that will be required for both individual tools and an integrated toolset were identified