Design of On-Chip Self-Testing Signature Register

Over the last few years, scan test has turn out to be too expensive to implement for industry standard designs due to increasing test data volume and test time. The test cost of a chip is mainly governed by the resource utilization of Automatic Test Equipment (ATE). Also, it directly depends upon test time that includes time required to load test program, to apply test vectors and to analyze generated test response of the chip. An issue of test time and data volume is increasingly appealing designers to use on-chip test data compactors, either on input side or output side or both. Such techniques significantly address the former issues but have little hold over increasing number of input-outputs under test mode. Further, test pins on DUT are increasing over the generations. Thus, scan channels on test floor are falling short in number for placement of such ICs. To address issues discussed above, we introduce an on-chip self-testing signature register. It comprises a response compactor and a comparator. The compactor compacts large chunk of response data to a small test signature whereas the comparator compares this test signature with desired one. The overall test result for the design is generated on single output pin. Being no storage of test response is demanded, the considerable reduction in ATE memory can be observed. Also, with only single pin to be monitored for test result, the number of tester channels and compare edges on ATE side significantly reduce at the end of the test. This cuts down maintenance and usage cost of test floor and increases its life time. Furthermore reduction in test pins gives scope for DFT engineers to increase number of scan chains so as to further reduce test time

A Hardware Security Solution against Scan-Based Attacks

Scan based Design for Test (DfT) schemes have been widely used to achieve high fault coverage for integrated circuits. The scan technique provides full access to the internal nodes of the device-under-test to control them or observe their response to input test vectors. While such comprehensive access is highly desirable for testing, it is not acceptable for secure chips as it is subject to exploitation by various attacks. In this work, new methods are presented to protect the security of critical information against scan-based attacks. In the proposed methods, access to the circuit containing secret information via the scan chain has been severely limited in order to reduce the risk of a security breach. To ensure the testability of the circuit, a built-in self-test which utilizes an LFSR as the test pattern generator (TPG) is proposed. The proposed schemes can be used as a countermeasure against side channel attacks with a low area overhead as compared to the existing solutions in literature

Characterizing, managing and monitoring the networks for the ATLAS data acquisition system

Particle physics studies the constituents of matter and the interactions between them. Many of the elementary particles do not exist under normal circumstances in nature. However, they can be created and detected during energetic collisions of other particles, as is done in particle accelerators. The Large Hadron Collider (LHC) being built at CERN will be the world's largest circular particle accelerator, colliding protons at energies of 14 TeV. Only a very small fraction of the interactions will give raise to interesting phenomena. The collisions produced inside the accelerator are studied using particle detectors. ATLAS is one of the detectors built around the LHC accelerator ring. During its operation, it will generate a data stream of 64 Terabytes/s. A Trigger and Data Acquisition System (TDAQ) is connected to ATLAS -- its function is to acquire digitized data from the detector and apply trigger algorithms to identify the interesting events. Achieving this requires the power of over 2000 computers plus an interconnecting network capable of sustaining a throughput of over 150 Gbit/s with minimal loss and delay. The implementation of this network required a detailed study of the available switching technologies to a high degree of precision in order to choose the appropriate components. We developed an FPGA-based platform (the GETB) for testing network devices. The GETB system proved to be flexible enough to be used as the ba sis of three different network-related projects. An analysis of the traffic pattern that is generated by the ATLAS data-taking applications was also possible thanks to the GETB. Then, while the network was being assembled, parts of the ATLAS detector started commissioning -- this task relied on a functional network. Thus it was imperative to be able to continuously identify existing and usable infrastructure and manage its operations. In addition, monitoring was required to detect any overload conditions with an indication where the excess demand was being generated. We developed tools to ease the maintenance of the network and to automatically produce inventory reports. We created a system that discovers the network topology and this permitted us to verify the installation and to track its progress. A real-time traffic visualization system has been built, allowing us to see at a glance which network segments are heavily utilized. Later, as the network achieves production status, it will be necessary to extend the monitoring to identify individual applications' use of the available bandwidth. We studied a traffic monitoring technology that will allow us to have a better understanding on how the network is used. This technology, based on packet sampling, gives the possibility of having a complete view of the network: not only its total capacity utilization, but also how this capacity is divided among users and software applicati ons. This thesis describes the establishment of a set of tools designed to characterize, monitor and manage complex, large-scale, high-performance networks. We describe in detail how these tools were designed, calibrated, deployed and exploited. The work that led to the development of this thesis spans over more than four years and closely follows the development phases of the ATLAS network: its design, its installation and finally, its current and future operation

Adaptive-Hybrid Redundancy for Radiation Hardening

An Adaptive-Hybrid Redundancy (AHR) mitigation strategy is proposed to mitigate the effects of Single Event Upset (SEU) and Single Event Transient (SET) radiation effects. AHR is adaptive because it switches between Triple Modular Redundancy (TMR) and Temporal Software Redundancy (TSR). AHR is hybrid because it uses hardware and software redundancy. AHR is demonstrated to run faster than TSR and use less energy than TMR. Furthermore, AHR allows space vehicle designers, mission planners, and operators the flexibility to determine how much time is spent in TMR and TSR. TMR mode provides faster processing at the expense of greater energy usage. TSR mode uses less energy at the expense of processing speed. AHR allows the user to determine the optimal balance between these modes based on their mission needs and changes can be made even after the space vehicle is operational. Radiation testing was performed to determine the SEU injection rate for simulations and analyses. A Field Programmable Gate Array (FPGA) was used to expedite testing in hardware

Autonomously Reconfigurable Artificial Neural Network on a Chip

Artificial neural network (ANN), an established bio-inspired computing paradigm, has proved very effective in a variety of real-world problems and particularly useful for various emerging biomedical applications using specialized ANN hardware. Unfortunately, these ANN-based systems are increasingly vulnerable to both transient and permanent faults due to unrelenting advances in CMOS technology scaling, which sometimes can be catastrophic. The considerable resource and energy consumption and the lack of dynamic adaptability make conventional fault-tolerant techniques unsuitable for future portable medical solutions. Inspired by the self-healing and self-recovery mechanisms of human nervous system, this research seeks to address reliability issues of ANN-based hardware by proposing an Autonomously Reconfigurable Artificial Neural Network (ARANN) architectural framework. Leveraging the homogeneous structural characteristics of neural networks, ARANN is capable of adapting its structures and operations, both algorithmically and microarchitecturally, to react to unexpected neuron failures. Specifically, we propose three key techniques --- Distributed ANN, Decoupled Virtual-to-Physical Neuron Mapping, and Dual-Layer Synchronization --- to achieve cost-effective structural adaptation and ensure accurate system recovery. Moreover, an ARANN-enabled self-optimizing workflow is presented to adaptively explore a "Pareto-optimal" neural network structure for a given application, on the fly. Implemented and demonstrated on a Virtex-5 FPGA, ARANN can cover and adapt 93% chip area (neurons) with less than 1% chip overhead and O(n) reconfiguration latency. A detailed performance analysis has been completed based on various recovery scenarios

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design

A Comprehensive Study of the Hardware Trojan and Side-Channel Attacks in Three-Dimensional (3D) Integrated Circuits (ICs)

Three-dimensional (3D) integration is emerging as promising techniques for high-performance and low-power integrated circuit (IC, a.k.a. chip) design. As 3D chips require more manufacturing phases than conventional planar ICs, more fabrication foundries are involved in the supply chain of 3D ICs. Due to the globalized semiconductor business model, the extended IC supply chain could incur more security challenges on maintaining the integrity, confidentiality, and reliability of integrated circuits and systems. In this work, we analyze the potential security threats induced by the integration techniques for 3D ICs and propose effective attack detection and mitigation methods. More specifically, we first propose a comprehensive characterization for 3D hardware Trojans in the 3D stacking structure. Practical experiment based quantitative analyses have been performed to assess the impact of 3D Trojans on computing systems. Our analysis shows that advanced attackers could exploit the limitation of the most recent 3D IC testing standard IEEE Standard 1838 to bypass the tier-level testing and successfully implement a powerful TSV-Trojan in 3D chips. We propose an enhancement for IEEE Standard 1838 to facilitate the Trojan detection on two neighboring tiers simultaneously. Next, we develop two 3D Trojan detection methods. The proposed frequency-based Trojan-activity identification (FTAI) method can differentiate the frequency changes induced by Trojans from those caused by process variation noise, outperforming the existing time-domain Trojan detection approaches by 38% in Trojan detection rate. Our invariance checking based Trojan detection method leverages the invariance among the 3D communication infrastructure, 3D network-on-chips (NoCs), to tackle the cross-tier 3D hardware Trojans, achieving a Trojan detection rate of over 94%. Furthermore, this work investigates another type of common security threat, side-channel attacks. We first propose to group the supply voltages of different 3D tiers temporally to drive the crypto unit implemented in 3D ICs such that the noise in power distribution network (PDN) can be induced to obfuscate the original power traces and thus mitigates correlation power analysis (CPA) attacks. Furthermore, we study the side-channel attack on the logic locking mechanism in monolithic 3D ICs and propose a logic-cone conjunction (LCC) method and a configuration guideline for the transistor-level logic locking to strengthen its resilience against CPA attacks

Interconnect yield analysis and fault tolerance for field programmable gate arrays

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