Exceeding Conservative Limits: A Consolidated Analysis on Modern Hardware Margins

Modern large-scale computing systems (data centers, supercomputers, cloud and edge setups and high-end cyber-physical systems) employ heterogeneous architectures that consist of multicore CPUs, general-purpose many-core GPUs, and programmable FPGAs. The effective utilization of these architectures poses several challenges, among which a primary one is power consumption. Voltage reduction is one of the most efficient methods to reduce power consumption of a chip. With the galloping adoption of hardware accelerators (i.e., GPUs and FPGAs) in large datacenters and other large-scale computing infrastructures, a comprehensive evaluation of the safe voltage reduction levels for each different chip can be employed for efficient reduction of the total power. We present a survey of recent studies in voltage margins reduction at the system level for modern CPUs, GPUs and FPGAs. The pessimistic voltage guardbands inserted by the silicon vendors can be exploited in all devices for significant power savings. On average, voltage reduction can reach 12% in multicore CPUs, 20% in manycore GPUs and 39% in FPGAs.Comment: Accepted for publication in IEEE Transactions on Device and Materials Reliabilit

Characterization of voltage noise in big, small and single-ISA heterogeneous systems

Sensitivity of the microprocessor to voltage fluctuations is becoming a major concern with growing emphasis on designing power-efficient microprocessors. Voltage fluctuations that exceed a certain threshold cause "emergencies" that can lead to timing errors in the processor, thus risking reliability. To guarantee correctness under such conditions, large voltage guardbands are employed, at the cost of reduced performance and wastage of power. Trends in microprocessor technology indicate that worst-case operating voltage margins are not sustainable. Since voltage emergencies occur only infrequently, resilient architectures with aggressive guardbands are needed. However, to enable the exploration of the design space of resilient processors, it is important to have a deep understanding of the characteristics of voltage noise in different system configurations. Prior research in this area has mostly focused on systems with very few cores. Given the increasing relevance of large multi-core systems, this thesis presents a detailed characterization of voltage noise on chip multi-processors, consisting of large number of cores. The data indicates that while the worst case voltage droop increases with increase in the number of cores, the frequency of occurrence of the droops is not greatly impacted, emphasizing the feasibility of employing resilient microarchitectures with aggressive voltage margins. The thesis also presents a comparative study of voltage noise in CMPs consisting of either high-performant out-of-order cores and power-efficient in-order cores. The study highlights that the out-of-order cores experience much larger voltage variations when compared to the in-order cores, but offer a clear advantage in terms of performance. Experiments indicate that in-order configurations that offer equivalent performance to the out-of-order cores result in large energy-delay product, indicating the trade-offs involved in designing for performance, power and reliability. The thesis also presents a study of voltage noise in single-ISA heterogeneous configurations, to highlight the benefits of such systems towards lowering the worst-case voltage margins, which improve both performance and power. The experimental results indicate that the worst-case voltage droop in such heterogeneous systems lies in between the out-of-order and in-order cores and provide reasonable power-efficiency and performance. Further, the work highlights the importance of exploring the design-space of heterogeneous systems considering reliability as an important design criteria.Computer Science

Active timing margin management to improve microprocessor power efficiency

Improving power/performance efficiency is critical for today’s micro- processors. From edge devices to datacenters, lower power or higher performance always produces better systems, measured by lower cost of ownership or longer battery time. This thesis studies improving microprocessor power/performance efficiency by optimizing the pipeline timing margin. In particular, this thesis focuses on improving the efficacy of Active Timing Margin, a young technology that dynamically adjusts the margin. Active timing margin trims down the pipeline timing margin with a control loop that adjusts voltage and frequency based on real-time chip environment monitoring. The key insight of this thesis is that in order to maximize active timing margin’s efficiency enhancement benefits, synergistic management from processor architecture design and system software scheduling are needed. To that end, this thesis covers the major consumers of pipeline timing margin, including temperature, voltage, and process variation. For temperature variation, the thesis proposes a table-lookup based active timing margin mechanism, and an associated temperature management scheme to minimize power consumption. For voltage variation, the thesis characterizes the limiting factors of adaptive clocking’s power saving and proposes application scheduling to maximize total system power reduction. For process variation, the thesis proposes core-level adaptive clocking reconfiguration to automatically expose inter-core variation and discusses workload scheduling and throttling management to control critical application performance. The author believes the optimization presented in this thesis can potentially benefit a variety of processor architectures as the conclusions are based on the solid measurement on state-of-the-art processors, and the research objective, active timing margin, already has wide applicability in the latest microprocessors by the time this thesis is written.Electrical and Computer Engineerin

Low-Power and Error-Resilient VLSI Circuits and Systems.

Efficient low-power operation is critically important for the success of the next-generation signal processing applications. Device and supply voltage have been continuously scaled to meet a more constrained power envelope, but scaling has created resiliency challenges, including increasing timing faults and soft errors. Our research aims at designing low-power and robust circuits and systems for signal processing by drawing circuit, architecture, and algorithm approaches. To gain an insight into the system faults due to supply voltage reduction, we researched the two primary effects that determine the minimum supply voltage (VMIN) in Intel’s tri-gate CMOS technology, namely process variations and gate-dielectric soft breakdown. We determined that voltage scaling increases the timing window that sequential circuits are vulnerable. Thus, we proposed a new hold-time violation metric to define hold-time VMIN, which has been adopted as a new design standard. Device scaling increases soft errors which affect circuit reliability. Through extensive soft error characterization using two 65nm CMOS test chips, we studied the soft error mechanisms and its dependence on supply voltage and clock frequency. This study laid the foundation of the first 65nm DSP chip design for a NASA spaceflight project. To mitigate such random errors, we proposed a new confidence-driven architecture that effectively enhances the error resiliency of deeply scaled CMOS and post-CMOS circuits. Designing low-power resilient systems can effectively leverage application-specific algorithmic approaches. To explore design opportunities in the algorithmic domain, we demonstrate an application-specific detection and decoding processor for multiple-input multiple-output (MIMO) wireless communication. To enhance the receive error rate for a robust wireless communication, we designed a joint detection and decoding technique by enclosing detection and decoding in an iterative loop to enhance both interference cancellation and error reduction. A proof-of-concept chip design was fabricated for the next-generation 4x4 256QAM MIMO systems. Through algorithm-architecture optimizations and low-power circuit techniques, our design achieves significant improvements in throughput, energy efficiency and error rate, paving the way for future developments in this area.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110323/1/uchchen_1.pd

Toward Reliable, Secure, and Energy-Efficient Multi-Core System Design

Computer hardware researchers have perennially focussed on improving the performance of computers while stipulating the energy consumption under a strict budget. While several innovations over the years have led to high performance and energy efficient computers, more challenges have also emerged as a fallout. For example, smaller transistor devices in modern multi-core systems are afflicted with several reliability and security concerns, which were inconceivable even a decade ago. Tackling these bottlenecks happens to negatively impact the power and performance of the computers. This dissertation explores novel techniques to gracefully solve some of the pressing challenges of the modern computer design. Specifically, the proposed techniques improve the reliability of on-chip communication fabric under a high power supply noise, increase the energy-efficiency of low-power graphics processing units, and demonstrate an unprecedented security loophole of the low-power computing paradigm through rigorous hardware-based experiments

Reliability in the face of variability in nanometer embedded memories

In this thesis, we have investigated the impact of parametric variations on the behaviour of one performance-critical processor structure - embedded memories. As variations manifest as a spread in power and performance, as a first step, we propose a novel modeling methodology that helps evaluate the impact of circuit-level optimizations on architecture-level design choices. Choices made at the design-stage ensure conflicting requirements from higher-levels are decoupled. We then complement such design-time optimizations with a runtime mechanism that takes advantage of adaptive body-biasing to lower power whilst improving performance in the presence of variability. Our proposal uses a novel fully-digital variation tracking hardware using embedded DRAM (eDRAM) cells to monitor run-time changes in cache latency and leakage. A special fine-grain body-bias generator uses the measurements to generate an optimal body-bias that is needed to meet the required yield targets. A novel variation-tolerant and soft-error hardened eDRAM cell is also proposed as an alternate candidate for replacing existing SRAM-based designs in latency critical memory structures. In the ultra low-power domain where reliable operation is limited by the minimum voltage of operation (Vddmin), we analyse the impact of failures on cache functional margin and functional yield. Towards this end, we have developed a fully automated tool (INFORMER) capable of estimating memory-wide metrics such as power, performance and yield accurately and rapidly. Using the developed tool, we then evaluate the #effectiveness of a new class of hybrid techniques in improving cache yield through failure prevention and correction. Having a holistic perspective of memory-wide metrics helps us arrive at design-choices optimized simultaneously for multiple metrics needed for maintaining lifetime requirements

Design methodology for reliable and energy efficient self-tuned on-chip voltage regulators

The energy-efficiency needs in computing systems, ranging from high performance processors to low-power devices is steadily on the rise, resulting in increasing popularity of on-chip voltage regulators (VR). The high-frequency and high bandwidth on-chip voltage regulators such as Inductive voltage regulators (IVR) and Digital Low Dropout regulators (DLDO) significantly enhance the energy-efficiency of a SoC by reducing supply noise and enabling faster voltage transitions. However, IVRs and DLDOs need to cope with the higher variability that exists in the deep nanometer digital nodes since they are fabricated on the same die as the digital core affecting performance of both the VR and digital core. Moreover, in most modern SoCs where multiple power domains are preferred, each VR needs to be designed and optimized for a target load demand which significantly increases the design time and time to market for VR assisted SoCs. This thesis investigates a performance-based auto-tuning algorithm utilizing performance of digital core to tune VRs against variations and improve performance of both VR and the core. We further propose a fully synthesizable VR architecture and an auto-generation tool flow that can be used to design and optimize a VR for given target specifications and auto-generate a GDS layout. This would reduce the design time drastically. And finally, a flexible precision IVR architecture is also explored to further improve transient performance and tolerance to process variations. The proposed IVR and DLDO designs with an AES core and auto-tuning circuits are prototyped in two testchips in 130nm CMOS process and one test chip in 65nm CMOS process. The measurements demonstrate improved performance of IVR and AES core due to performance-based auto-tuning. Moreover, the synthesizable architectures of IVR and DLDO implemented using auto-generation tool flow showed competitive performance with state of art full custom designs with orders of magnitude reduction in design time. Additional improvement in transient performance of IVR is also observed due to the flexible precision feedback loop design.Ph.D

Voltage drop tolerance by adaptive voltage scaling using clock-data compensation

Proyecto de Graduación (Maestría en Ingeniería en Electrónica) Instituto Tecnológico de Costa Rica, Escuela de Ingeniería Electrónica, 2019.El ruido de alta frecuencia en la red de alimentación compromete el rendimiento y la eficiencia energética de los sistemas electrónicos con microprocesadores, restringiendo la frecuencia máxima de operación de los sistemas y disminuyendo la confiabilidad de los dispositivos. La frecuencia máxima será determinada por la ruta de datos más crítica (la ruta de datos más lenta). De esta manera, es necesario configurar una banda de guarda para tolerar caídas de voltaje sin tener ningún problema de ejecución, pero sacrificando el rendimiento eléctrico. Este trabajo evalúa el impacto de la caída de voltaje en el rendimiento de los circuitos CMOS de alta densidad, estableciendo un conjunto de casos de prueba que contienen diferentes configuraciones de circuitos. Se desarrolló una técnica adaptable y escalable para mejorar la tolerancia a la caída de voltaje en los circuitos CMOS a través del escalado adaptativo, aprovechando el efecto de compensación de datos del reloj. La solución propuesta se validó aplicándola a diferentes casos de prueba en una tecnología FinFet-CMOS a nivel de simulación del diseño físico.High-frequency power supply noise compromises performance and energy efficiency of microprocessor-based products, restricting the maximum frequency of operation for electronic systems and decreasing device reliability. The maximum frequency is going to be determine by the most critical data path (the slowest data path). In this way, a guard band needs to be set in order to tolerate voltage drops without having any execution problem, but leading to a performance reduction. This work evaluates the impact of voltage drop in the performance of CMOS circuits by establishing a set of test cases containing different circuit configurations. An adaptive and scalable technique is proposed to enhance voltage drop tolerance in CMOS circuits through adaptive scaling, taking advantage of the clock-data compensation effect. The proposed solution is validated by applying it to different test cases in a FinFet CMOS technology at a post-layout simulation level

Energy Efficient Hardware Design for Securing the Internet-of-Things

The Internet of Things (IoT) is a rapidly growing field that holds potential to transform our everyday lives by placing tiny devices and sensors everywhere. The ubiquity and scale of IoT devices require them to be extremely energy efficient. Given the physical exposure to malicious agents, security is a critical challenge within the constrained resources. This dissertation presents energy-efficient hardware designs for IoT security. First, this dissertation presents a lightweight Advanced Encryption Standard (AES) accelerator design. By analyzing the algorithm, a novel method to manipulate two internal steps to eliminate storage registers and replace flip-flops with latches to save area is discovered. The proposed AES accelerator achieves state-of-art area and energy efficiency. Second, the inflexibility and high Non-Recurring Engineering (NRE) costs of Application-Specific-Integrated-Circuits (ASICs) motivate a more flexible solution. This dissertation presents a reconfigurable cryptographic processor, called Recryptor, which achieves performance and energy improvements for a wide range of security algorithms across public key/secret key cryptography and hash functions. The proposed design employs circuit techniques in-memory and near-memory computing and is more resilient to power analysis attack. In addition, a simulator for in-memory computation is proposed. It is of high cost to design and evaluate new-architecture like in-memory computing in Register-transfer level (RTL). A C-based simulator is designed to enable fast design space exploration and large workload simulations. Elliptic curve arithmetic and Galois counter mode are evaluated in this work. Lastly, an error resilient register circuit, called iRazor, is designed to tolerate unpredictable variations in manufacturing process operating temperature and voltage of VLSI systems. When integrated into an ARM processor, this adaptive approach outperforms competing industrial techniques such as frequency binning and canary circuits in performance and energy.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147546/1/zhyiqun_1.pd