Multi-port Memory Design for Advanced Computer Architectures

In this thesis, we describe and evaluate novel memory designs for multi-port on-chip and off-chip use in advanced computer architectures. We focus on combining multi-porting and evaluating the performance over a range of design parameters. Multi-porting is essential for caches and shared-data systems, especially multi-core System-on-chips (SOC). It can significantly increase the memory access throughput. We evaluate FinFET voltage-mode multi-port SRAM cells using different metrics including leakage current, static noise margin and read/write performance. Simulation results show that single-ended multi-port FinFET SRAMs with isolated read ports offer improved read stability and flexibility over classical double-ended structures at the expense of write performance. By increasing the size of the access transistors, we show that the single-ended multi-port structures can achieve equivalent write performance to the classical double-ended multi-port structure for 9% area overhead. Moreover, compared with CMOS SRAM, FinFET SRAM has better stability and standby power. We also describe new methods for the design of FinFET current-mode multi-port SRAM cells. Current-mode SRAMs avoid the full-swing of the bitline, reducing dynamic power and access time. However, that comes at the cost of voltage drop, which compromises stability. The design proposed in this thesis utilizes the feature of Independent Gate (IG) mode FinFET, which can leverage threshold voltage by controlling the back gate voltage, to merge two transistors into one through high-Vt and low-Vt transistors. This design not only reduces the voltage drop, but it also reduces the area in multi-port current-mode SRAM design. For off-chip memory, we propose a novel two-port 1-read, 1-write (1R1W) phasechange memory (PCM) cell, which significantly reduces the probability of blocking at the bank levels. Different from the traditional PCM cell, the access transistors are at the top and connected to the bitline. We use Verilog-A to model the behavior of Ge2Sb2Te5 (GST: the storage component). We evaluate the performance of the two-port cell by transistor sizing and voltage pumping. Simulation results show that pMOS transistor is more practical than nMOS transistor as the access device when both area and power are considered. The estimated area overhead is 1.7�, compared to single-port PCM cell. In brief, the contribution we make in this thesis is that we propose and evaluate three different kinds of multi-port memories that are favorable for advanced computer architectures

Design techniques for dense embedded memory in advanced CMOS technologies

University of Minnesota Ph.D. dissertation. February 2012. Major: Electrical Engineering. Advisor: Chris H. Kim. 1 computer file (PDF); viii, 116 pages.On-die cache memory is a key component in advanced processors since it can boost micro-architectural level performance at a moderate power penalty. Demand for denser memories only going to increase as the number of cores in a microprocessor goes up with technology scaling. A commensurate increase in the amount of cache memory is needed to fully utilize the larger and more powerful processing units. 6T SRAMs have been the embedded memory of choice for modern microprocessors due to their logic compatibility, high speed, and refresh-free operation. However, the relatively large cell size and conflicting requirements for read and write make aggressive scaling of 6T SRAMs challenging in sub-22 nm. In this dissertation, circuit techniques and simulation methodologies are presented to demonstrate the potential of alternative options such as gain cell eDRAMs and spin-torque-transfer magnetic RAMs (STT-MRAMs) for high density embedded memories.Three unique test chip designs are presented to enhance the retention time and access speed of gain cell eDRAMs. Proposed bit-cells utilize preferential boostings, beneficial couplings, and aggregated cell leakages for expanding signal window between data `1' and `0'. The design space of power-delay product can be further enhanced with various assist schemes that harness the innate properties of gain cell eDRAMs. Experimental results from the test chips demonstrate that the proposed gain cell eDRAMs achieve overall faster system performances and lower static power dissipations than SRAMs in a generic 65 nm low-power (LP) CMOS process. A magnetic tunnel junction (MTJ) scaling scenario and an efficient HSPICE simulation methodology are proposed for exploring the scalability of STT-MRAMs under variation effects from 65 nm to 8 nm. A constant JC0*RA/VDD scaling method is adopted to achieve optimal read and write performances of STT-MRAMs and thermal stabilities for a 10 year retention are achieved by adjusting free layer thicknesses as well as projecting crystalline anisotropy improvements. Studies based on the proposed methodology show that in-plane STT-MRAM will outperform SRAM from 15 nm node, while its perpendicular counterpart requires further innovations in MTJ material properties in order to overcome the poor write performance from 22 nm node

Low-Power, Low-Voltage SRAM Circuits Design For Nanometric CMOS Technologies

Embedded SRAM memory is a vital component in modern SoCs. More than 80% of the System-on-Chip (SoC) die area is often occupied by SRAM arrays. As such, system reliability and yield is largely governed by the SRAM's performance and robustness. The aggressive scaling trend in CMOS device minimum feature size, coupled with the growing demand in high-capacity memory integration, has imposed the use of minimal size devices to realize a memory bitcell. The smallest 6T SRAM bitcell to date occupies a 0.1um2 in silicon area. SRAM bitcells continue to benefit from an aggressive scaling trend in CMOS technologies. Unfortunately, other system components, such as interconnects, experience a slower scaling trend. This has resulted in dramatic deterioration in a cell's ability to drive a heavily-loaded interconnects. Moreover, the growing fluctuation in device properties due to Process, Voltage, and Temperature (PVT) variations has added more uncertainty to SRAM operation. Thus ensuring the ability of a miniaturized cell to drive heavily-loaded bitlines and to generate adequate voltage swing is becoming challenging. A large percentage of state-of-the-art SoC system failures are attributed to the inability of SRAM cells to generate the targeted bitline voltage swing within a given access time. The use of read-assist mechanisms and current mode sense amplifiers are the two key strategies used to surmount bitline loading effects. On the other hand, new bitcell topologies and cell supply voltage management are used to overcome fluctuations in device properties. In this research we tackled conventional 6T SRAM bitcell limited drivability by introducing new integrated voltage sensing schemes and current-mode sense amplifiers. The proposed schemes feature a read-assist mechanism. The proposed schemes' functionality and superiority over existing schemes are verified using transient and statistical SPICE simulations. Post-layout extracted views of the devices are used for realistic simulation results. Low-voltage operated SRAM reliability and yield enhancement is investigated and a wordline boost technique is proposed as a means to manage the cell's WL operating voltage. The proposed wordline driver design shows a significant improvement in reliability and yield in a 400-mV 6T SRAM cell. The proposed wordline driver design exploit the cell's Dynamic Noise Margin (DNM), therefore boost peak level and boost decay rate programmability features are added. SPICE transient and statistical simulations are used to verify the proposed design's functionality. Finally, at a bitcell-level, we proposed a new five-transistor (5T) SRAM bitcell which shows competitive performance and reliability figures of merit compared to the conventional 6T bitcell. The functionality of the proposed cell is verified by post-layout SPICE simulations. The proposed bitcell topology is designed, implemented and fabricated in a standard ST CMOS 65nm technology process. A 1.2_ 1.2 mm2 multi-design project test chip consisting of four 32-Kbit (256-row x 128-column) SRAM macros with the required peripheral and timing control units is fabricated. Two of the designed SRAM macros are dedicated for this work, namely, a 32-Kbit 5T macro and a 32-Kbit 6T macro which is used as a comparison reference. Other macros belong to other projects and are not discussed in this document

Interconnect and Memory Design for Intelligent Mobile System

Technology scaling has driven the transistor to a smaller area, higher performance and lower power consuming which leads us into the mobile and edge computing era. However, the benefits of technology scaling are diminishing today, as the wire delay and energy scales far behind that of the logics, which makes communication more expensive than computation. Moreover, emerging data centric algorithms like deep learning have a growing demand on SRAM capacity and bandwidth. High access energy and huge leakage of the large on-chip SRAM have become the main limiter of realizing an energy efficient low power smart sensor platform. This thesis presents several architecture and circuit solutions to enable intelligent mobile systems, including voltage scalable interconnect scheme, Compute-In-Memory (CIM), low power memory system from edge deep learning processor and an ultra-low leakage stacked voltage domain SRAM for low power smart image signal processor (ISP). Four prototypes are implemented for demonstration and verification. The first two seek the solutions to the slow and high energy global on-chip interconnect: the first prototype proposes a reconfigurable self-timed regenerator based global interconnect scheme to achieve higher performance and energy-efficiency in wide voltage range, while the second one presents a non Von Neumann architecture, a hybrid in-/near-memory Compute SRAM (CRAM), to address the locality issue. The next two works focus on low-power low-leakage SRAM design for Intelligent sensors. The third prototype is a low power memory design for a deep learning processor with 270KB custom SRAM and Non-Uniform Memory Access architecture. The fourth prototype is an ultra-low leakage SRAM for motion-triggered low power smart imager sensor system with voltage domain stacking and a novel array swapping mechanism. The work presented in this dissertation exploits various optimizations in both architecture level (exploiting temporal and spatial locality) and circuit customization to overcome the main challenges in making extremely energy-efficient battery-powered intelligent mobile devices. The impact of the work is significant in the era of Internet-of-Things (IoT) and the age of AI when the mobile computing systems get ubiquitous, intelligent and longer battery life, powered by these proposed solutions.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155232/1/jiwang_1.pd

Ultra Low Power Digital Circuit Design for Wireless Sensor Network Applications

Ny forskning innenfor feltet trådløse sensornettverk åpner for nye og innovative produkter og løsninger. Biomedisinske anvendelser er blant områdene med størst potensial og det investeres i dag betydelige beløp for å bruke denne teknologien for å gjøre medisinsk diagnostikk mer effektiv samtidig som man åpner for fjerndiagnostikk basert på trådløse sensornoder integrert i et ”helsenett”. Målet er å forbedre tjenestekvalitet og redusere kostnader samtidig som brukerne skal oppleve forbedret livskvalitet som følge av økt trygghet og mulighet for å tilbringe mest mulig tid i eget hjem og unngå unødvendige sykehusbesøk og innleggelser. For å gjøre dette til en realitet er man avhengige av sensorelektronikk som bruker minst mulig energi slik at man oppnår tilstrekkelig batterilevetid selv med veldig små batterier. I sin avhandling ” Ultra Low power Digital Circuit Design for Wireless Sensor Network Applications” har PhD-kandidat Farshad Moradi fokusert på nye løsninger innenfor konstruksjon av energigjerrig digital kretselektronikk. Avhandlingen presenterer nye løsninger både innenfor aritmetiske og kombinatoriske kretser, samtidig som den studerer nye statiske minneelementer (SRAM) og alternative minnearkitekturer. Den ser også på utfordringene som oppstår når silisiumteknologien nedskaleres i takt med mikroprosessorutviklingen og foreslår løsninger som bidrar til å gjøre kretsløsninger mer robuste og skalerbare i forhold til denne utviklingen. De viktigste konklusjonene av arbeidet er at man ved å introdusere nye konstruksjonsteknikker både er i stand til å redusere energiforbruket samtidig som robusthet og teknologiskalerbarhet øker. Forskningen har vært utført i samarbeid med Purdue University og vært finansiert av Norges Forskningsråd gjennom FRINATprosjektet ”Micropower Sensor Interface in Nanometer CMOS Technology”