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

Novel Multicarrier Memory Channel Architecture Using Microwave Interconnects: Alleviating the Memory Wall

abstract: The increase in computing power has simultaneously increased the demand for input/output (I/O) bandwidth. Unfortunately, the speed of I/O and memory interconnects have not kept pace. Thus, processor-based systems are I/O and interconnect limited. The memory aggregated bandwidth is not scaling fast enough to keep up with increasing bandwidth demands. The term "memory wall" has been coined to describe this phenomenon. A new memory bus concept that has the potential to push double data rate (DDR) memory speed to 30 Gbit/s is presented. We propose to map the conventional DDR bus to a microwave link using a multicarrier frequency division multiplexing scheme. The memory bus is formed using a microwave signal carried within a waveguide. We call this approach multicarrier memory channel architecture (MCMCA). In MCMCA, each memory signal is modulated onto an RF carrier using 64-QAM format or higher. The carriers are then routed using substrate integrated waveguide (SIW) interconnects. At the receiver, the memory signals are demodulated and then delivered to SDRAM devices. We pioneered the usage of SIW as memory channel interconnects and demonstrated that it alleviates the memory bandwidth bottleneck. We demonstrated SIW performance superiority over conventional transmission line in immunity to cross-talk and electromagnetic interference. We developed a methodology based on design of experiment (DOE) and response surface method techniques that optimizes the design of SIW interconnects and minimizes its performance fluctuations under material and manufacturing variations. Along with using SIW, we implemented a multicarrier architecture which enabled the aggregated DDR bandwidth to reach 30 Gbit/s. We developed an end-to-end system model in Simulink and demonstrated the MCMCA performance for ultra-high throughput memory channel. Experimental characterization of the new channel shows that by using judicious frequency division multiplexing, as few as one SIW interconnect is sufficient to transmit the 64 DDR bits. Overall aggregated bus data rate achieves 240 GBytes/s data transfer with EVM not exceeding 2.26% and phase error of 1.07 degree or less.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Doctor of Philosophy

dissertationThe internet-based information infrastructure that has powered the growth of modern personal/mobile computing is composed of powerful, warehouse-scale computers or datacenters. These heavily subscribed datacenters perform data-processing jobs under intense quality of service guarantees. Further, high-performance compute platforms are being used to model and analyze increasingly complex scientific problems and natural phenomena. To ensure that the high-performance needs of these machines are met, it is necessary to increase the efficiency of the memory system that supplies data to the processing cores. Many of the microarchitectural innovations that were designed to scale the memory wall (e.g., out-of-order instruction execution, on-chip caches) are being rendered less effective due to several emerging trends (e.g., increased emphasis on energy consumption, limited access locality). This motivates the optimization of the main memory system itself. The key to an efficient main memory system is the memory controller. In particular, the scheduling algorithm in the memory controller greatly influences its performance. This dissertation explores this hypothesis in several contexts. It develops tools to better understand memory scheduling and develops scheduling innovations for CPUs and GPUs. We propose novel memory scheduling techniques that are strongly aware of the access patterns of the clients as well as the microarchitecture of the memory device. Based on these, we present (i) a Dynamic Random Access Memory (DRAM) chip microarchitecture optimized for reducing write-induced slowdown, (ii) a memory scheduling algorithm that exploits these features, (iii) several memory scheduling algorithms to reduce the memory-related stall experienced by irregular General Purpose Graphics Processing Unit (GPGPU) applications, and (iv) the Utah Simulated Memory Module (USIMM), a detailed, validated simulator for DRAM main memory that we use for analyzing and proposing scheduler algorithms