E-QED: Electrical Bug Localization During Post-Silicon Validation Enabled by Quick Error Detection and Formal Methods

During post-silicon validation, manufactured integrated circuits are extensively tested in actual system environments to detect design bugs. Bug localization involves identification of a bug trace (a sequence of inputs that activates and detects the bug) and a hardware design block where the bug is located. Existing bug localization practices during post-silicon validation are mostly manual and ad hoc, and, hence, extremely expensive and time consuming. This is particularly true for subtle electrical bugs caused by unexpected interactions between a design and its electrical state. We present E-QED, a new approach that automatically localizes electrical bugs during post-silicon validation. Our results on the OpenSPARC T2, an open-source 500-million-transistor multicore chip design, demonstrate the effectiveness and practicality of E-QED: starting with a failed post-silicon test, in a few hours (9 hours on average) we can automatically narrow the location of the bug to (the fan-in logic cone of) a handful of candidate flip-flops (18 flip-flops on average for a design with ~ 1 Million flip-flops) and also obtain the corresponding bug trace. The area impact of E-QED is ~2.5%. In contrast, deter-mining this same information might take weeks (or even months) of mostly manual work using traditional approaches

Automated Debugging Methodology for FPGA-based Systems

Electronic devices make up a vital part of our lives. These are seen from mobiles, laptops, computers, home automation, etc. to name a few. The modern designs constitute billions of transistors. However, with this evolution, ensuring that the devices fulfill the designer’s expectation under variable conditions has also become a great challenge. This requires a lot of design time and effort. Whenever an error is encountered, the process is re-started. Hence, it is desired to minimize the number of spins required to achieve an error-free product, as each spin results in loss of time and effort. Software-based simulation systems present the main technique to ensure the verification of the design before fabrication. However, few design errors (bugs) are likely to escape the simulation process. Such bugs subsequently appear during the post-silicon phase. Finding such bugs is time-consuming due to inherent invisibility of the hardware. Instead of software simulation of the design in the pre-silicon phase, post-silicon techniques permit the designers to verify the functionality through the physical implementations of the design. The main benefit of the methodology is that the implemented design in the post-silicon phase runs many order-of-magnitude faster than its counterpart in pre-silicon. This allows the designers to validate their design more exhaustively. This thesis presents five main contributions to enable a fast and automated debugging solution for reconfigurable hardware. During the research work, we used an obstacle avoidance system for robotic vehicles as a use case to illustrate how to apply the proposed debugging solution in practical environments. The first contribution presents a debugging system capable of providing a lossless trace of debugging data which permits a cycle-accurate replay. This methodology ensures capturing permanent as well as intermittent errors in the implemented design. The contribution also describes a solution to enhance hardware observability. It is proposed to utilize processor-configurable concentration networks, employ debug data compression to transmit the data more efficiently, and partially reconfiguring the debugging system at run-time to save the time required for design re-compilation as well as preserve the timing closure. The second contribution presents a solution for communication-centric designs. Furthermore, solutions for designs with multi-clock domains are also discussed. The third contribution presents a priority-based signal selection methodology to identify the signals which can be more helpful during the debugging process. A connectivity generation tool is also presented which can map the identified signals to the debugging system. The fourth contribution presents an automated error detection solution which can help in capturing the permanent as well as intermittent errors without continuous monitoring of debugging data. The proposed solution works for designs even in the absence of golden reference. The fifth contribution proposes to use artificial intelligence for post-silicon debugging. We presented a novel idea of using a recurrent neural network for debugging when a golden reference is present for training the network. Furthermore, the idea was also extended to designs where golden reference is not present

Securing IEEE P1687 On-chip Instrumentation Access Using PUF

As the complexity of VLSI designs grows, the amount of embedded instrumentation in system-on-a-chip designs increases at an exponential rate. Such structures serve various purposes throughout the life-cycle of VLSI circuits, e.g. in post-silicon validation and debug, production test and diagnosis, as well as during in-field test and maintenance. Reliable access mechanisms for embedded instruments are therefore key to rapid chip development and secure system maintenance. Reconfigurable scan networks defined by IEEE Std. P1687 emerge as a scalable and cost-effective access medium for on-chip instrumentation. The accessibility offered by reconfigurable scan networks contradicts security and safety requirements for embedded instrumentation. Embedded instrumentation is an integral system component that remains functional throughout the lifetime of a chip. To prevent harmful activities, such as tampering with safety-critical systems, and reduce the risk of intellectual property infringement, the access to embedded instrumentation requires protection. This thesis provides a novel, Physical Unclonable Function (PUF) based secure access method for on-chip instruments which enhances the security of IJTAG network at low hardware cost and with less routing congestion

SoK: Design Tools for Side-Channel-Aware Implementations

Side-channel attacks that leak sensitive information through a computing device's interaction with its physical environment have proven to be a severe threat to devices' security, particularly when adversaries have unfettered physical access to the device. Traditional approaches for leakage detection measure the physical properties of the device. Hence, they cannot be used during the design process and fail to provide root cause analysis. An alternative approach that is gaining traction is to automate leakage detection by modeling the device. The demand to understand the scope, benefits, and limitations of the proposed tools intensifies with the increase in the number of proposals. In this SoK, we classify approaches to automated leakage detection based on the model's source of truth. We classify the existing tools on two main parameters: whether the model includes measurements from a concrete device and the abstraction level of the device specification used for constructing the model. We survey the proposed tools to determine the current knowledge level across the domain and identify open problems. In particular, we highlight the absence of evaluation methodologies and metrics that would compare proposals' effectiveness from across the domain. We believe that our results help practitioners who want to use automated leakage detection and researchers interested in advancing the knowledge and improving automated leakage detection

Polymeric Microsensors for Intraoperative Contact Pressure Measurement

Biocompatible sensors have been demonstrated using traditional microfabrication techniques modified for polymer substrates and utilize only materials suitable for implantation or bodily contact. Sensor arrays for the measurement of the load condition of polyethylene spacers in the total knee arthroplasty (TKA) prosthesis have been developed. Arrays of capacitive sensors are used to determine the three-dimensional strain within the polyethylene prosthesis component. Data from these sensors can be used to give researchers a better understanding of component motion, loading, and wear phenomena for a large range of activities. This dissertation demonstrates both analytically and experimentally the fabrication of these sensor arrays using biocompatible polymer substrates and dielectrics while preserving industry-standard microfabrication processing for micron-level resolution. An array of sensors for real-time measurement of pressure profiles is the long-term goal of this research. A custom design using capacitive-based sensors is an excellent selection for such measurement, giving high spatial resolution across the sensing surface and high load resolution for pressures applied normal to that surface while operating at low power