Achieving Functional Correctness in Large Interconnect Systems.

In today's semi-conductor industry, large chip-multiprocessors and systems-on-chip are being developed, integrating a large number of components on a single chip. The sheer size of these designs and the intricacy of the communication patterns they exhibit have propelled the development of network-on-chip (NoC) interconnects as the basis for the communication infrastructure in these systems. Faced with the interconnect's growing size and complexity, several challenges hinder its effective validation. During the interconnect's development, the functional verification process relies heavily on the use of emulation and post-silicon validation platforms. However, detecting and debugging errors on these platforms is a difficult endeavour due to the limited observability, and in turn the low verification capabilities, they provide. Additionally, with the inherent incompleteness of design-time validation efforts, the potential of design bugs escaping into the interconnect of a released product is also a concern, as these bugs can threaten the viability of the entire system. This dissertation provides solutions to enable the development of functionally correct interconnect designs. We first address the challenges encountered during design-time verification efforts, by providing two complementary mechanisms that allow emulation and post-silicon verification frameworks to capture a detailed overview of the functional behaviour of the interconnect. Our first solution re-purposes the contents of in-flight traffic to log debug data from the interconnect's execution. This approach enables the validation of the interconnect using synthetic traffic workloads, while attaining over 80% observability of the routes followed by packets and capturing valuable debugging information. We also develop an alternative mechanism that boosts observability by taking periodic snapshots of execution, thus extending the verification capabilities to run both synthetic traffic and real-application workloads. The collected snapshots enhance detection and debugging support, and they provide observability of over 50% of packets and reconstructs at least half of each of their routes. Moreover, we also develop error detection and recovery solutions to address the threat of design bugs escaping into the interconnect's runtime operation. Our runtime techniques can overcome communication errors without needing to store replicate copies of all in-flight packets, thereby achieving correctness at minimal area costsPhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116741/1/rawanak_1.pd

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

Low-cost error detection through high-level synthesis

System-on-chip design is becoming increasingly complex as technology scaling enables more and more functionality on a chip. This scaling and complexity has resulted in a variety of reliability and validation challenges including logic bugs, hot spots, wear-out, and soft errors. To make matters worse, as we reach the limits of Dennard scaling, efforts to improve system performance and energy efficiency have resulted in the integration of a wide variety of complex hardware accelerators in SoCs. Thus the challenge is to design complex, custom hardware that is efficient, but also correct and reliable. High-level synthesis shows promise to address the problem of complex hardware design by providing a bridge from the high-productivity software domain to the hardware design process. Much research has been done on high-level synthesis efficiency optimizations. This thesis shows that high-level synthesis also has the power to address validation and reliability challenges through two solutions. One solution for circuit reliability is modulo-3 shadow datapaths: performing lightweight shadow computations in modulo-3 space for each main computation. We leverage the binding and scheduling flexibility of high-level synthesis to detect control errors through diverse binding and minimize area cost through intelligent checkpoint scheduling and modulo-3 reducer sharing. We introduce logic and dataflow optimizations to further reduce cost. We evaluated our technique with 12 high-level synthesis benchmarks from the arithmetic-oriented PolyBench benchmark suite using FPGA emulated netlist-level error injection. We observe coverages of 99.1% for stuck-at faults, 99.5% for soft errors, and 99.6% for timing errors with a 25.7% area cost and negligible performance impact. Leveraging a mean error detection latency of 12.75 cycles (4150x faster than end result check) for soft errors, we also explore a rollback recovery method with an additional area cost of 28.0%, observing a 175x increase in reliability against soft errors. Another solution for rapid post-silicon validation of accelerator designs is Hybrid Quick Error Detection (H-QED): inserting signature generation logic in a hardware design to create a heavily compressed signature stream that captures the internal behavior of the design at a fine temporal and spatial granularity for comparison with a reference set of signatures generated by high-level simulation to detect bugs. Using H-QED, we demonstrate an improvement in error detection latency (time elapsed from when a bug is activated to when it manifests as an observable failure) of two orders of magnitude and a threefold improvement in bug coverage compared to traditional post-silicon validation techniques. H-QED also uncovered previously unknown bugs in the CHStone benchmark suite, which is widely used by the HLS community. H-QED incurs less than 10% area overhead for the accelerator it validates with negligible performance impact, and we also introduce techniques to minimize any possible intrusiveness introduced by H-QED

Multi Language Interpreter Embedding Tool for Shift Left Pre-Silicon Validation

Throughout the years, digital and analog designs have evolved meaningfully towards performance improvement, cost reduction and new features enablement. As a result, complexity has increased rapidly, demanding the development of better validation techniques in order to meet the time-to-market pressure calls with a bug free device. The primary choice of silicon development companies to validate software before the hardware becomes available, until now, is the FPGA based emulation platform, which leads to a big gap as it loads a register transfer level code that is usually not validated with SW-like flows in the early development stages. SW flows, mainly drivers, are validated in parallel to HW on SW emulation platforms. In order to fill the validation gap and push the finding of certain bugs to an earlier development stage, the idea of running SW tests with no or little modification in simulation environments would represent a big return of investment, rising the reliability of the system before manufacturing it, reducing time to market and development cost of the system on chip. This thesis explains the complete development of a framework able to run python scripts in VCS simulation by implementing the OVM Multi Language capability

Real-time fault injection using enhanced on-chip debug infrastructures

The rapid increase in the use of microprocessor-based systems in critical areas, where failures imply risks to human lives, to the environment or to expensive equipment, significantly increased the need for dependable systems, able to detect, tolerate and eventually correct faults. The verification and validation of such systems is frequently performed via fault injection, using various forms and techniques. However, as electronic devices get smaller and more complex, controllability and observability issues, and sometimes real time constraints, make it harder to apply most conventional fault injection techniques. This paper proposes a fault injection environment and a scalable methodology to assist the execution of real-time fault injection campaigns, providing enhanced performance and capabilities. Our proposed solutions are based on the use of common and customized on-chip debug (OCD) mechanisms, present in many modern electronic devices, with the main objective of enabling the insertion of faults in microprocessor memory elements with minimum delay and intrusiveness. Different configurations were implemented starting from basic Components Off-The-Shelf (COTS) microprocessors, equipped with real-time OCD infrastructures, to improved solutions based on modified interfaces, and dedicated OCD circuitry that enhance fault injection capabilities and performance. All methodologies and configurations were evaluated and compared concerning performance gain and silicon overhead