Cross-Layer Pathfinding for Off-Chip Interconnects

Off-chip interconnects for integrated circuits (ICs) today induce a diverse design space, spanning many different applications that require transmission of data at various bandwidths, latencies and link lengths. Off-chip interconnect design solutions are also variously sensitive to system performance, power and cost metrics, while also having a strong impact on these metrics. The costs associated with off-chip interconnects include die area, package (PKG) and printed circuit board (PCB) area, technology and bill of materials (BOM). Choices made regarding off-chip interconnects are fundamental to product definition, architecture, design implementation and technology enablement. Given their cross-layer impact, it is imperative that a cross-layer approach be employed to architect and analyze off-chip interconnects up front, so that a top-down design flow can comprehend the cross-layer impacts and correctly assess the system performance, power and cost tradeoffs for off-chip interconnects. Chip architects are not exposed to all the tradeoffs at the physical and circuit implementation or technology layers, and often lack the tools to accurately assess off-chip interconnects. Furthermore, the collaterals needed for a detailed analysis are often lacking when the chip is architected; these include circuit design and layout, PKG and PCB layout, and physical floorplan and implementation. To address the need for a framework that enables architects to assess the system-level impact of off-chip interconnects, this thesis presents power-area-timing (PAT) models for off-chip interconnects, optimization and planning tools with the appropriate abstraction using these PAT models, and die/PKG/PCB co-design methods that help expose the off-chip interconnect cross-layer metrics to the die/PKG/PCB design flows. Together, these models, tools and methods enable cross-layer optimization that allows for a top-down definition and exploration of the design space and helps converge on the correct off-chip interconnect implementation and technology choice. The tools presented cover off-chip memory interfaces for mobile and server products, silicon photonic interfaces, 2.5D silicon interposers and 3D through-silicon vias (TSVs). The goal of the cross-layer framework is to assess the key metrics of the interconnect (such as timing, latency, active/idle/sleep power, and area/cost) at an appropriate level of abstraction by being able to do this across layers of the design flow. In additional to signal interconnect, this thesis also explores the need for such cross-layer pathfinding for power distribution networks (PDN), where the system-on-chip (SoC) floorplan and pinmap must be optimized before the collateral layouts for PDN analysis are ready. Altogether, the developed cross-layer pathfinding methodology for off-chip interconnects enables more rapid and thorough exploration of a vast design space of off-chip parallel and serial links, inter-die and inter-chiplet links and silicon photonics. Such exploration will pave the way for off-chip interconnect technology enablement that is optimized for system needs. The basis of the framework can be extended to cover other interconnect technology as well, since it fundamentally relates to system-level metrics that are common to all off-chip interconnects

PHY Link Design and Optimization For High-Speed Low-Power Communication Systems

The ever-growing demands for high-bandwidth data transfer have been pushing towards advancing research efforts in the field of high-performing communication systems. Studies on the performance of single chip, e.g. faster multi-core processors and higher system memory capacity, have been explored. To further enhance the system performance, researches have been focused on the improvement of data-transfer bandwidth for chip-to-chip communication in the high-speed serial link. Many solutions have been addressed to overcome the bottleneck caused by the non-idealties such as bandwidth-limited electrical channel that connects two link devices and varieties of undesired noise in the communication systems. Nevertheless, with these solutions data have run into limitations of the timing margins for high-speed interfaces running at multiple gigabits per second data rates on low-cost Printed Circuit Board (PCB) material with constrained power budget. Therefore, the challenge in designing a physical layer (PHY) link for high-speed communication systems turns out to be power-efficient, reliable and cost-effective. In this context, this dissertation is intended to focus on architectural design, system-level and circuit-level verification of a PHY link as well as system performance optimization in respective of power, reliability and adaptability in high-speed communication systems. The PHY is mainly composed of clock data recovery (CDR), equalizers (EQs) and high- speed I/O drivers. Symmetrical structure of the PHY link is usually duplicated in both link devices for bidirectional data transmission. By introducing training mechanisms into high-speed communication systems, the timing in one link device is adaptively aligned to the timing condition specified in the other link device despite of different skews or induced jitter resulting from process, voltage and temperature (PVT) variations in the individual link. With reliable timing relationships among the interface signals provided, the total system bandwidth is dramatically improved. On the other hand, interface training offers high flexibility for reuse without further investigation on high demanding components involved in high costs. In the training mode, a CDR module is essential for reconstructing the transmitted bitstream to achieve the best data eye and to detect the edges of data stream in asynchronous systems or source-synchronous systems. Generally, the CDR works as a feedback control system that aligns its output clock to the center of the received data. In systems that contain multiple data links, the overall CDR power consumption increases linearly with the increase in number of links as one CDR is required for each link. Therefore, a power-efficient CDR plays a significant role in such systems with parallel links. Furthermore, a high performance CDR requires low jitter generation in spite of high input jitter. To minimize the trade-off between power consumption and CDR jitter, a novel CDR architecture is proposed by utilizing the proportional-integral (PI) controller and three times sampling scheme. Meanwhile, signal integrity (SI) becomes critical as the data rate exceeds several gigabits per second. Distorted data due to the non-idealties in systems are likely to reduce the signal quality aggressively and result in intolerable transmission errors in worst case scenarios, thus affect the system effective bandwidth. Hence, additional trainings such as transmitter (Tx) and receiver (Rx) EQ trainings for SI purpose are inserted into the interface training. Besides, a simplified system architecture with unsymmetrical placement of adaptive Rx and Tx EQs in a single link device is proposed and analyzed by using different coefficient adaptation algorithms. This architecture enables to reduce a large number of EQs through the training, especially in case of parallel links. Meanwhile, considerable power and chip area are saved. Finally, high-speed I/O driver against PVT variations is discussed. Critical issues such as overshoot and undershoot interfering with the data are primarily accompanied by impedance mismatch between the I/O driver and its transmitting channel. By applying PVT compensation technique I/O driver impedances can be effectively calibrated close to the target value. Different digital impedance calibration algorithms against PVT variations are implemented and compared for achieving fast calibration and low power requirements

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position