A design methodology for robust, energy-efficient, application-aware memory systems

Memory design is a crucial component of VLSI system design from area, power and performance perspectives. To meet the increasingly challenging system specifications, architecture, circuit and device level innovations are required for existing memory technologies. Emerging memory solutions are widely explored to cater to strict budgets. This thesis presents design methodologies for custom memory design with the objective of power-performance benefits across specific applications. Taking example of STTRAM (spin transfer torque random access memory) as an emerging memory candidate, the design space is explored to find optimal energy design solution. A thorough thermal reliability study is performed to estimate detection reliability challenges and circuit solutions are proposed to ensure reliable operation. Adoption of the application-specific optimal energy solution is shown to yield considerable energy benefits in a read-heavy application called MBC (memory based computing). Circuit level customizations are studied for the volatile SRAM (static random access memory) memory, which will provide improved energy-delay product (EDP) for the same MBC application. Memory design has to be aware of upcoming challenges from not only the application nature but also from the packaging front. Taking 3D die-folding as an example, SRAM performance shift under die-folding is illustrated. Overall the thesis demonstrates how knowledge of the system and packaging can help in achieving power efficient and high performance memory design.Ph.D

Hardware/Software Co-Design of Ultra-Low Power Biomedical Monitors

Ongoing changes in world demographics and the prevalence of unhealthy lifestyles are imposing a paradigm shift in healthcare delivery. Nowadays, chronic ailments such as cardiovascular diseases, hypertension and diabetes, represent the most common causes of death according to the World Health Organization. It is estimated that 63% of deaths worldwide are directly or indirectly related to these non-communicable diseases (NCDs), and by 2030 it is predicted that the health delivery cost will reach an amount comparable to 75% of the current GDP. In this context, technologies based on Wireless Sensor Nodes (WSNs) effectively alleviate this burden enabling the conception of wearable biomedical monitors composed of one or several devices connected through a Wireless Body Sensor Network (WBSN). Energy efficiency is of paramount importance for these devices, which must operate for prolonged periods of time with a single battery charge. In this thesis I propose a set of hardware/software co-design techniques to drastically increase the energy efficiency of bio-medical monitors. To this end, I jointly explore different alternatives to reduce the required computational effort at the software level while optimizing the power consumption of the processing hardware by employing ultra-low power multi-core architectures that exploit DSP application characteristics. First, at the sensor level, I study the utilization of a heartbeat classifier to perform selective advanced DSP on state-of-the-art ECG bio-medical monitors. To this end, I developed a framework to design and train real-time, lightweight heartbeat neuro-fuzzy classifiers, detail- ing the required optimizations to efficiently execute them on a resource-constrained platform. Then, at the network level I propose a more complex transmission-aware WBSN for activity monitoring that provides different tradeoffs between classification accuracy and transmission volume. In this work, I study the combination of a minimal set of WSNs with a smartphone, and propose two classification schemes that trade accuracy for transmission volume. The proposed method can achieve accuracies ranging from 88% to 97% and can save up to 86% of wireless transmissions, outperforming the state-of-the-art alternatives. Second, I propose a synchronization-based low-power multi-core architecture for bio-signal processing. I introduce a hardware/software synchronization mechanism that allows to achieve high energy efficiency while parallelizing the execution of multi-channel DSP applications. Then, I generalize the methodology to support bio-signal processing applications with an arbitrarily high degree of parallelism. Due to the benefits of SIMD execution and software pipelining, the architecture can reduce its power consumption by up 38% when compared to an equivalent low-power single-core alternative. Finally, I focused on the optimization of the multi-core memory subsystem, which is the major contributor to the overall system power consumption. First I considered a hybrid memory subsystem featuring a small reliable partition that can operate at ultra-low voltage enabling low-power buffering of data and obtaining up to 50% energy savings. Second, I explore a two-level memory hierarchy based on non-volatile memories (NVM) that allows for aggressive fine-grained power gating enabled by emerging low-power NVM technologies and monolithic 3D integration. Experimental results show that, by adopting this memory hierarchy, power consumption can be reduced by 5.42x in the DSP stage

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Error Characterization and Correction Techniques for Reliable STT-RAM Designs

The concerns on the continuous scaling of mainstream memory technologies have motivated tremendous investment to emerging memories. Being a promising candidate, spin-transfer torque random access memory (STT-RAM) offers nanosecond access time comparable to SRAM, high integration density close to DRAM, non-volatility as Flash memory, and good scalability. It is well positioned as the replacement of SRAM and DRAM for on-chip cache and main memory applications. However, reliability issue continues being one of the major challenges in STT-RAM memory designs due to the process variations and unique thermal fluctuations, i.e., the stochastic resistance switching property of magnetic devices. In this dissertation, I decoupled the reliability issues as following three-folds: First, the characterization of STT-RAM operation errors often require expensive Monte-Carlo runs with hybrid magnetic-CMOS simulation steps, making it impracticable for architects and system designs; Second, the state of the art does not have sufficiently understanding on the unique reliability issue of STT-RAM, and conventional error correction codes (ECCs) cannot efficiently handle such errors; Third, while the information density of STT-RAM can be boosted by multi-level cell (MLC) design, the more prominent reliability concerns and the complicated access mechanism greatly limit its applications in memory subsystems. Thus, I present a novel through solution set to both characterize and tackle the above reliability challenges in STT-RAM designs. In the first part of the dissertation, I introduce a new characterization method that can accurately and efficiently capture the multi-variable design metrics of STT-RAM cells; Second, a novel ECC scheme, namely, content-dependent ECC (CD-ECC), is developed to combat the characterized asymmetric errors of STT-RAM at 0->1 and 1->0 bit flipping's; Third, I present a circuit-architecture design, namely state-restricted multi-level cell (SR-MLC) STT-RAM design, which simultaneously achieves high information density, good storage reliability and fast write speed, making MLC STT-RAM accessible for system designers under current technology node. Finally, I conclude that efficient robust (or ECC) designs for STT-RAM require a deep holistic understanding on three different levels-device, circuit and architecture. Innovative ECC schemes and their architectural applications, still deserve serious research and investigation in the near future

Fabrication, Characterization and Integration of Resistive Random Access Memories

The functionalities and performances of today's computing systems are increasingly dependent on the memory block. This phenomenon, also referred as the Von Neumann bottleneck, is the main motivation for the research on memory technologies. Despite CMOS technology has been improved in the last 50 years by continually increasing the device density, today's mainstream memories, such as SRAM, DRAM and Flash, are facing fundamental limitations to continue this trend. These memory technologies, based on charge storage mechanisms, are suffering from the easy loss of the stored state for devices scaled below 10 nm. This results in a degradation of the performance, reliability and noise margin. The main motivation for the development of emerging non volatile memories is the study of a different mechanism to store the digital state in order to overcome this challenge. Among these emerging technologies, one of the strongest candidate is Resistive Random Access Memory (ReRAM), which relies on the formation or rupture of a conductive filament inside a dielectric layer. This thesis focuses on the fabrication, characterization and integration of ReRAM devices. The main subject is the qualitative and quantitative description of the main factors that influence the resistive memory electrical behavior. Such factors can be related either to the memory fabrication or to the test environment. The first category includes variations in the fabrication process steps, in the device geometry or composition. We discuss the effect of each variation, and we use the obtained database to gather insights on the ReRAM working mechanism and the adopted methodology by using statistical methods. The second category describes how differences in the electrical stimuli sent to the device change the memory performances. We show how these factors can influence the memory resistance states, and we propose an empirical model to describe such changes. We also discuss how it is possible to control the resistance states by modulating the number of input pulses applied to the device. In the second part of this work, we present the integration of the fabricated devices in a CMOS technology environment. We discuss a Verilog-A model used to simulate the device characteristics, and we show two solutions to limit the sneak-path currents for ReRAM crossbars: a dedicated read circuit and the development of selector devices. We describe the selector fabrication, as well as the electrical characterization and the combination with our ReRAMs in a 1S1R configuration. Finally, we show two methods to integrate ReRAM devices in the BEoL of CMOS chips

Gestión de jerarquías de memoria híbridas a nivel de sistema

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadoras y Automática y de Ku Leuven, Arenberg Doctoral School, Faculty of Engineering Science, leída el 11/05/2017.In electronics and computer science, the term ‘memory’ generally refers to devices that are used to store information that we use in various appliances ranging from our PCs to all hand-held devices, smart appliances etc. Primary/main memory is used for storage systems that function at a high speed (i.e. RAM). The primary memory is often associated with addressable semiconductor memory, i.e. integrated circuits consisting of silicon-based transistors, used for example as primary memory but also other purposes in computers and other digital electronic devices. The secondary/auxiliary memory, in comparison provides program and data storage that is slower to access but offers larger capacity. Examples include external hard drives, portable flash drives, CDs, and DVDs. These devices and media must be either plugged in or inserted into a computer in order to be accessed by the system. Since secondary storage technology is not always connected to the computer, it is commonly used for backing up data. The term storage is often used to describe secondary memory. Secondary memory stores a large amount of data at lesser cost per byte than primary memory; this makes secondary storage about two orders of magnitude less expensive than primary storage. There are two main types of semiconductor memory: volatile and nonvolatile. Examples of non-volatile memory are ‘Flash’ memory (sometimes used as secondary, sometimes primary computer memory) and ROM/PROM/EPROM/EEPROM memory (used for firmware such as boot programs). Examples of volatile memory are primary memory (typically dynamic RAM, DRAM), and fast CPU cache memory (typically static RAM, SRAM, which is fast but energy-consuming and offer lower memory capacity per are a unit than DRAM). Non-volatile memory technologies in Si-based electronics date back to the 1990s. Flash memory is widely used in consumer electronic products such as cellphones and music players and NAND Flash-based solid-state disks (SSDs) are increasingly displacing hard disk drives as the primary storage device in laptops, desktops, and even data centers. The integration limit of Flash memories is approaching, and many new types of memory to replace conventional Flash memories have been proposed. The rapid increase of leakage currents in Silicon CMOS transistors with scaling poses a big challenge for the integration of SRAM memories. There is also the case of susceptibility to read/write failure with low power schemes. As a result of this, over the past decade, there has been an extensive pooling of time, resources and effort towards developing emerging memory technologies like Resistive RAM (ReRAM/RRAM), STT-MRAM, Domain Wall Memory and Phase Change Memory(PRAM). Emerging non-volatile memory technologies promise new memories to store more data at less cost than the expensive-to build silicon chips used by popular consumer gadgets including digital cameras, cell phones and portable music players. These new memory technologies combine the speed of static random-access memory (SRAM), the density of dynamic random-access memory (DRAM), and the non-volatility of Flash memory and so become very attractive as another possibility for future memory hierarchies. The research and information on these Non-Volatile Memory (NVM) technologies has matured over the last decade. These NVMs are now being explored thoroughly nowadays as viable replacements for conventional SRAM based memories even for the higher levels of the memory hierarchy. Many other new classes of emerging memory technologies such as transparent and plastic, three-dimensional(3-D), and quantum dot memory technologies have also gained tremendous popularity in recent years...En el campo de la informática, el término ‘memoria’ se refiere generalmente a dispositivos que son usados para almacenar información que posteriormente será usada en diversos dispositivos, desde computadoras personales (PC), móviles, dispositivos inteligentes, etc. La memoria principal del sistema se utiliza para almacenar los datos e instrucciones de los procesos que se encuentre en ejecución, por lo que se requiere que funcionen a alta velocidad (por ejemplo, DRAM). La memoria principal está implementada habitualmente mediante memorias semiconductoras direccionables, siendo DRAM y SRAM los principales exponentes. Por otro lado, la memoria auxiliar o secundaria proporciona almacenaje(para ficheros, por ejemplo); es más lenta pero ofrece una mayor capacidad. Ejemplos típicos de memoria secundaria son discos duros, memorias flash portables, CDs y DVDs. Debido a que estos dispositivos no necesitan estar conectados a la computadora de forma permanente, son muy utilizados para almacenar copias de seguridad. La memoria secundaria almacena una gran cantidad de datos aun coste menor por bit que la memoria principal, siendo habitualmente dos órdenes de magnitud más barata que la memoria primaria. Existen dos tipos de memorias de tipo semiconductor: volátiles y no volátiles. Ejemplos de memorias no volátiles son las memorias Flash (algunas veces usadas como memoria secundaria y otras veces como memoria principal) y memorias ROM/PROM/EPROM/EEPROM (usadas para firmware como programas de arranque). Ejemplos de memoria volátil son las memorias DRAM (RAM dinámica), actualmente la opción predominante a la hora de implementar la memoria principal, y las memorias SRAM (RAM estática) más rápida y costosa, utilizada para los diferentes niveles de cache. Las tecnologías de memorias no volátiles basadas en electrónica de silicio se remontan a la década de1990. Una variante de memoria de almacenaje por carga denominada como memoria Flash es mundialmente usada en productos electrónicos de consumo como telefonía móvil y reproductores de música mientras NAND Flash solid state disks(SSDs) están progresivamente desplazando a los dispositivos de disco duro como principal unidad de almacenamiento en computadoras portátiles, de escritorio e incluso en centros de datos. En la actualidad, hay varios factores que amenazan la actual predominancia de memorias semiconductoras basadas en cargas (capacitivas). Por un lado, se está alcanzando el límite de integración de las memorias Flash, lo que compromete su escalado en el medio plazo. Por otra parte, el fuerte incremento de las corrientes de fuga de los transistores de silicio CMOS actuales, supone un enorme desafío para la integración de memorias SRAM. Asimismo, estas memorias son cada vez más susceptibles a fallos de lectura/escritura en diseños de bajo consumo. Como resultado de estos problemas, que se agravan con cada nueva generación tecnológica, en los últimos años se han intensificado los esfuerzos para desarrollar nuevas tecnologías que reemplacen o al menos complementen a las actuales. Los transistores de efecto campo eléctrico ferroso (FeFET en sus siglas en inglés) se consideran una de las alternativas más prometedores para sustituir tanto a Flash (por su mayor densidad) como a DRAM (por su mayor velocidad), pero aún está en una fase muy inicial de su desarrollo. Hay otras tecnologías algo más maduras, en el ámbito de las memorias RAM resistivas, entre las que cabe destacar ReRAM (o RRAM), STT-RAM, Domain Wall Memory y Phase Change Memory (PRAM)...Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu