Voltage regulation of a series stacked system of digital loads by differential power processing

A modern high-end multi-core microprocessor has very stringent power supply requirements. It can draw hundreds of amperes of current at supply voltages as low as 0.8 V. As the supply voltages keep decreasing, the power delivery to meet the supply requirements is becoming increasingly difficult and inefficient. However, the presence of multiple cores in the microprocessor offers us a way to power it at a higher voltage by series-stacking the cores. Differential power processing has been shown to be an efficient way to series-stack server loads. In this work we study the dynamics of the element-to-element DPP topology implemented with bi-directional buck-boost converters. Some of its dynamic drawbacks are pointed out and a topological modification to counter those drawbacks is proposed. We then develop a linear control to regulate processor core voltages in a series stack of 4 cores. A hysteretic control to accommodate light load modes in the bi-directional regulating converters is also discussed. Both the linear and the hysteretic controller are implemented successfully in hardware and efficiency improvement due to light-load modes is demonstrated

Scalable System-on-Chip Design

The crisis of technology scaling led the industry of semiconductors towards the adoption of disruptive technologies and innovations to sustain the evolution of microprocessors and keep under control the timing of the design cycle. Multi-core and many-core architectures sought more energy-efficient computation by replacing a power-hungry processor with multiple simpler cores exploiting parallelism. Multi-core processors alone, however, turned out to be insufficient to sustain the ever growing demand for energy and power-efficient computation without compromising performance. Therefore, designers were pushed to drift from homogeneous architectures towards more complex heterogeneous systems that employ the large number of available transistors to incorporate a combination of customized energy-efficient accelerators, along with the general-purpose processor cores. Meanwhile, enhancements in manufacturing processes allowed designers to move a variety of peripheral components and analog devices into the chip. This paradigm shift defined the concept of {\em system-on-chip} (SoC) as a single-chip design that integrates several heterogeneous components. The rise of SoCs corresponds to a rapid decrease of the opportunity cost for integrating accelerators. In fact, on one hand, employing more transistors for powerful cores is not feasible anymore, because transistors cannot be active all at once within reasonable power budgets. On the other hand, increasing the number of homogeneous cores incurs more and more diminishing returns. The availability of cost effective silicon area for specialized hardware creates an opportunity to enter the market of semiconductors for new small players: engineers from several different scientific areas can develop competitive algorithms suitable for acceleration for domain-specific applications, such as multimedia systems, self-driving vehicles, robotics, and more. However, turning these algorithms into SoC components, referred to as {\em intellectual property}, still requires expert hardware designers who are typically not familiar with the specific domain of the target application. Furthermore, heterogeneity makes SoC design and programming much more difficult, especially because of the challenges of the integration process. This is a fine art in the hands of few expert engineers who understand system-level trade-offs, know how to design good hardware, how to handle memory and power management, how to shape and balance the traffic over an interconnect, and are able to deal with many different hardware-software interfaces. Designers need solutions enabling them to build scalable and heterogeneous SoCs. My thesis is that {\em the key to scalable SoC designs is a regular and flexible architecture that hides the complexity of heterogeneous integration from designers, while helping them focus on the important aspects of domain-specific applications through a companion system-level design methodology.} I open a path towards this goal by proposing an architecture that mitigates heterogeneity with regularity and addresses the challenges of heterogeneous component integration by implementing a set of {\em platform services}. These are hardware and software interfaces that from a system-level viewpoint give the illusion of working with a homogeneous SoC, thus making it easier to reuse accelerators and port applications across different designs, each with its own target workload and cost-performance trade-off point. A companion system-level design methodology exploits the regularity of the architecture to guide designers in implementing their intellectual property and enables an extensive design-space exploration across multiple levels of abstraction. Throughout the dissertation, I present a fully automated flow to deploy heterogeneous SoCs on single or multiple field-programmable-gate-array devices. The flow provides non-expert designers with a set of knobs for tuning system-level features based on the given mix of accelerators that they have integrated. Many contributions of my dissertation have already influenced other research projects as well as the content of an advanced course for graduate and senior undergraduate students, which aims to form a new generation of system-level designers. These new professionals need not to be circuit or register-transfer level design experts, and not even gurus of operating systems. Instead, they are trained to design efficient intellectual property by considering system-level trade-offs, while the architecture and the methodology that I describe in this dissertation empower them to integrate their components into an SoC. Finally, with the open-source release of the entire infrastructure, including the SoC-deployment flow and the software stack, I hope I will be able to inspire other research groups and help them implement ideas that further reduce the cost and design-time of future heterogeneous systems