Magnetic racetrack memory: from physics to the cusp of applications within a decade

Racetrack memory (RTM) is a novel spintronic memory-storage technology that has the potential to overcome fundamental constraints of existing memory and storage devices. It is unique in that its core differentiating feature is the movement of data, which is composed of magnetic domain walls (DWs), by short current pulses. This enables more data to be stored per unit area compared to any other current technologies. On the one hand, RTM has the potential for mass data storage with unlimited endurance using considerably less energy than today's technologies. On the other hand, RTM promises an ultrafast nonvolatile memory competitive with static random access memory (SRAM) but with a much smaller footprint. During the last decade, the discovery of novel physical mechanisms to operate RTM has led to a major enhancement in the efficiency with which nanoscopic, chiral DWs can be manipulated. New materials and artificially atomically engineered thin-film structures have been found to increase the speed and lower the threshold current with which the data bits can be manipulated. With these recent developments, RTM has attracted the attention of the computer architecture community that has evaluated the use of RTM at various levels in the memory stack. Recent studies advocate RTM as a promising compromise between, on the one hand, power-hungry, volatile memories and, on the other hand, slow, nonvolatile storage. By optimizing the memory subsystem, significant performance improvements can be achieved, enabling a new era of cache, graphical processing units, and high capacity memory devices. In this article, we provide an overview of the major developments of RTM technology from both the physics and computer architecture perspectives over the past decade. We identify the remaining challenges and give an outlook on its future

High-Performance Energy-Efficient and Reliable Design of Spin-Transfer Torque Magnetic Memory

In this dissertation new computing paradigms, architectures and design philosophy are proposed and evaluated for adopting the STT-MRAM technology as highly reliable, energy efficient and fast memory. For this purpose, a novel cross-layer framework from the cell-level all the way up to the system- and application-level has been developed. In these framework, the reliability issues are modeled accurately with appropriate fault models at different abstraction levels in order to analyze the overall failure rates of the entire memory and its Mean Time To Failure (MTTF) along with considering the temperature and process variation effects. Design-time, compile-time and run-time solutions have been provided to address the challenges associated with STT-MRAM. The effectiveness of the proposed solutions is demonstrated in extensive experiments that show significant improvements in comparison to state-of-the-art solutions, i.e. lower-power, higher-performance and more reliable STT-MRAM design

Designs for increasing reliability while reducing energy and increasing lifetime

In the last decades, the computing technology experienced tremendous developments. For instance, transistors' feature size shrank to half at every two years as consistently from the first time Moore stated his law. Consequently, number of transistors and core count per chip doubles at each generation. Similarly, petascale systems that have the capability of processing more than one billion calculation per second have been developed. As a matter of fact, exascale systems are predicted to be available at year 2020. However, these developments in computer systems face a reliability wall. For instance, transistor feature sizes are getting so small that it becomes easier for high-energy particles to temporarily flip the state of a memory cell from 1-to-0 or 0-to-1. Also, even if we assume that fault-rate per transistor stays constant with scaling, the increase in total transistor and core count per chip will significantly increase the number of faults for future desktop and exascale systems. Moreover, circuit ageing is exacerbated due to increased manufacturing variability and thermal stresses, therefore, lifetime of processor structures are becoming shorter. On the other side, due to the limited power budget of the computer systems such that mobile devices, it is attractive to scale down the voltage. However, when the voltage level scales to beyond the safe margin especially to the ultra-low level, the error rate increases drastically. Nevertheless, new memory technologies such as NAND flashes present only limited amount of nominal lifetime, and when they exceed this lifetime, they can not guarantee storing of the data correctly leading to data retention problems. Due to these issues, reliability became a first-class design constraint for contemporary computing in addition to power and performance. Moreover, reliability even plays increasingly important role when computer systems process sensitive and life-critical information such as health records, financial information, power regulation, transportation, etc. In this thesis, we present several different reliability designs for detecting and correcting errors occurring in processor pipelines, L1 caches and non-volatile NAND flash memories due to various reasons. We design reliability solutions in order to serve three main purposes. Our first goal is to improve the reliability of computer systems by detecting and correcting random and non-predictable errors such as bit flips or ageing errors. Second, we aim to reduce the energy consumption of the computer systems by allowing them to operate reliably at ultra-low voltage level. Third, we target to increase the lifetime of new memory technologies by implementing efficient and low-cost reliability schemes

Doctor of Philosophy in Computing

dissertationThe demand for main memory capacity has been increasing for many years and will continue to do so. In the past, Dynamic Random Access Memory (DRAM) process scaling has enabled this increase in memory capacity. Along with continued DRAM scaling, the emergence of new technologies like 3D-stacking, buffered Dual Inline Memory Modules (DIMMs), and crosspoint nonvolatile memory promise to continue this trend in the years ahead. However, these technologies will bring with them their own gamut of problems. In this dissertation, I look at the problems facing these technologies from a current delivery perspective. 3D-stacking increases memory capacity available per package, but the increased current requirement means that more pins on the package have to be now dedicated to provide Vdd/Vss, hence increasing cost. At the system level, using buffered DIMMs to increase the number of DRAM ranks increases the peak current requirements of the system if all the DRAM chips in the system are Refreshed simultaneously. Crosspoint memories promise to greatly increase bit densities but have long read latencies because of sneak currents in the cross-bar. In this dissertation, I provide architectural solutions to each of these problems. We observe that smart data placement by the architecture and the Operating System (OS) is a vital ingredient in all of these solutions. We thereby mitigate major bottlenecks in these technologies, hence enabling higher memory densities

Design and Code Optimization for Systems with Next-generation Racetrack Memories

With the rise of computationally expensive application domains such as machine learning, genomics, and fluids simulation, the quest for performance and energy-efficient computing has gained unprecedented momentum. The significant increase in computing and memory devices in modern systems has resulted in an unsustainable surge in energy consumption, a substantial portion of which is attributed to the memory system. The scaling of conventional memory technologies and their suitability for the next-generation system is also questionable. This has led to the emergence and rise of nonvolatile memory ( NVM ) technologies. Today, in different development stages, several NVM technologies are competing for their rapid access to the market. Racetrack memory ( RTM ) is one such nonvolatile memory technology that promises SRAM -comparable latency, reduced energy consumption, and unprecedented density compared to other technologies. However, racetrack memory ( RTM ) is sequential in nature, i.e., data in an RTM cell needs to be shifted to an access port before it can be accessed. These shift operations incur performance and energy penalties. An ideal RTM , requiring at most one shift per access, can easily outperform SRAM . However, in the worst-cast shifting scenario, RTM can be an order of magnitude slower than SRAM . This thesis presents an overview of the RTM device physics, its evolution, strengths and challenges, and its application in the memory subsystem. We develop tools that allow the programmability and modeling of RTM -based systems. For shifts minimization, we propose a set of techniques including optimal, near-optimal, and evolutionary algorithms for efficient scalar and instruction placement in RTMs . For array accesses, we explore schedule and layout transformations that eliminate the longer overhead shifts in RTMs . We present an automatic compilation framework that analyzes static control flow programs and transforms the loop traversal order and memory layout to maximize accesses to consecutive RTM locations and minimize shifts. We develop a simulation framework called RTSim that models various RTM parameters and enables accurate architectural level simulation. Finally, to demonstrate the RTM potential in non-Von-Neumann in-memory computing paradigms, we exploit its device attributes to implement logic and arithmetic operations. As a concrete use-case, we implement an entire hyperdimensional computing framework in RTM to accelerate the language recognition problem. Our evaluation shows considerable performance and energy improvements compared to conventional Von-Neumann models and state-of-the-art accelerators

Application Centric Networks-On-Chip Design Solutions for Future Multicore Systems

With advances in technology, future multicore systems scaled to 100s and 1000s of cores/accelerators are being touted as an effective solution for extracting huge performance gains using parallel programming paradigms. However with the failure of Dennard Scaling all the components on the chip cannot be run simultaneously without breaking the power and thermal constraints leading to strict chip power envelops. The scaling up of the number of on chip components has also brought upon Networks-On-Chip (NoC) based interconnect designs like 2D mesh. The contribution of NoC to the total on chip power and overall performance has been increasing steadily and hence high performance power-efficient NoC designs are becoming crucial. Future multicore paradigms can be broadly classified, based on the applications they are tailored to, into traditional Chip Multi processor(CMP) based application based systems, characterized by low core and NoC utilization, and emerging big data application based systems, characterized by large amounts of data movement necessitating high throughput requirements. To this order, we propose NoC design solutions for power-savings in future CMPs tailored to traditional applications and higher effective throughput gains in multicore systems tailored to bandwidth intensive applications. First, we propose Fly-over, a light-weight distributed mechanism for power-gating routers attached to switched off cores to reduce NoC power consumption in low load CMP environment. Secondly, we plan on utilizing a promising next generation memory technology, Spin-Transfer Torque Magnetic RAM(STT-MRAM), to achieve enhanced NoC performance to satisfy the high throughput demands in emerging bandwidth intensive applications, while reducing the power consumption simultaneously. Thirdly, we present a hardware data approximation framework for NoCs, APPROX-NoC, with an online data error control mechanism, which can leverage the approximate computing paradigm in the emerging data intensive big data applications to attain higher performance per watt

Fast Packet Processing on High Performance Architectures

The rapid growth of Internet and the fast emergence of new network applications have brought great challenges and complex issues in deploying high-speed and QoS guaranteed IP network. For this reason packet classication and network intrusion detection have assumed a key role in modern communication networks in order to provide Qos and security. In this thesis we describe a number of the most advanced solutions to these tasks. We introduce NetFPGA and Network Processors as reference platforms both for the design and the implementation of the solutions and algorithms described in this thesis. The rise in links capacity reduces the time available to network devices for packet processing. For this reason, we show different solutions which, either by heuristic and randomization or by smart construction of state machine, allow IP lookup, packet classification and deep packet inspection to be fast in real devices based on high speed platforms such as NetFPGA or Network Processors

Dependable design for low-cost ultra-low-power processors

Emerging applications in the Internet of Things (IoT) domain, such as wearables, implantables, smart tags, and wireless sensor networks put severe power, cost, reliability, and security constraints on hardware system design. This dissertation focuses on the architecture and design of dependable ultra-low power computing systems. Specifically, it proposes architecture and design techniques that exploit the unique application and usage characteristics of future computing systems to deliver low power, while meeting the reliability and security constraints of these systems. First, this dissertation considers the challenge of achieving both low power and high reliability in SRAM memories. It proposes both an architectural technique to reduce the overheads of error correction and a technique that uses the nature of error correcting codes to allow lower voltage operation without sacrificing reliability. Next, this dissertation considers low power and low cost. By leveraging the fact that many IoT systems are embedded in nature and will run the same application for their entire lifetime, fine-grained usage characteristics of the hardware-software system can be determined at design time. This dissertation presents a novel hardware-software co-analysis based on symbolic simulation that can determine the possible states of the processor throughout any execution of a specific application. This enables power-gating where more gates are turned off for longer, bespoke processors customized to specific applications, and stricter determination of peak power bounds. Finally, this dissertation considers achieving secure IoT systems at low cost and power overhead. By leveraging the hardware-software co-analysis, this dissertation shows that gate-level information flow security guarantees can be provided without hardware overheads

Broadcast-oriented wireless network-on-chip : fundamentals and feasibility

Premi extraordinari doctorat UPC curs 2015-2016, àmbit Enginyeria de les TICRecent years have seen the emergence and ubiquitous adoption of Chip Multiprocessors (CMPs), which rely on the coordinated operation of multiple execution units or cores. Successive CMP generations integrate a larger number of cores seeking higher performance with a reasonable cost envelope. For this trend to continue, however, important scalability issues need to be solved at different levels of design. Scaling the interconnect fabric is a grand challenge by itself, as new Network-on-Chip (NoC) proposals need to overcome the performance hurdles found when dealing with the increasingly variable and heterogeneous communication demands of manycore processors. Fast and flexible NoC solutions are needed to prevent communication become a performance bottleneck, situation that would severely limit the design space at the architectural level and eventually lead to the use of software frameworks that are slow, inefficient, or less programmable. The emergence of novel interconnect technologies has opened the door to a plethora of new NoCs promising greater scalability and architectural flexibility. In particular, wireless on-chip communication has garnered considerable attention due to its inherent broadcast capabilities, low latency, and system-level simplicity. Most of the resulting Wireless Network-on-Chip (WNoC) proposals have set the focus on leveraging the latency advantage of this paradigm by creating multiple wireless channels to interconnect far-apart cores. This strategy is effective as the complement of wired NoCs at moderate scales, but is likely to be overshadowed at larger scales by technologies such as nanophotonics unless bandwidth is unrealistically improved. This dissertation presents the concept of Broadcast-Oriented Wireless Network-on-Chip (BoWNoC), a new approach that attempts to foster the inherent simplicity, flexibility, and broadcast capabilities of the wireless technology by integrating one on-chip antenna and transceiver per processor core. This paradigm is part of a broader hybrid vision where the BoWNoC serves latency-critical and broadcast traffic, tightly coupled to a wired plane oriented to large flows of data. By virtue of its scalable broadcast support, BoWNoC may become the key enabler of a wealth of unconventional hardware architectures and algorithmic approaches, eventually leading to a significant improvement of the performance, energy efficiency, scalability and programmability of manycore chips. The present work aims not only to lay the fundamentals of the BoWNoC paradigm, but also to demonstrate its viability from the electronic implementation, network design, and multiprocessor architecture perspectives. An exploration at the physical level of design validates the feasibility of the approach at millimeter-wave bands in the short term, and then suggests the use of graphene-based antennas in the terahertz band in the long term. At the link level, this thesis provides an insightful context analysis that is used, afterwards, to drive the design of a lightweight protocol that reliably serves broadcast traffic with substantial latency improvements over state-of-the-art NoCs. At the network level, our hybrid vision is evaluated putting emphasis on the flexibility provided at the network interface level, showing outstanding speedups for a wide set of traffic patterns. At the architecture level, the potential impact of the BoWNoC paradigm on the design of manycore chips is not only qualitatively discussed in general, but also quantitatively assessed in a particular architecture for fast synchronization. Results demonstrate that the impact of BoWNoC can go beyond simply improving the network performance, thereby representing a possible game changer in the manycore era.Avenços en el disseny de multiprocessadors han portat a una àmplia adopció dels Chip Multiprocessors (CMPs), que basen el seu potencial en la operació coordinada de múltiples nuclis de procés. Generacions successives han anat integrant més nuclis en la recerca d'alt rendiment amb un cost raonable. Per a que aquesta tendència continuï, però, cal resoldre importants problemes d'escalabilitat a diferents capes de disseny. Escalar la xarxa d'interconnexió és un gran repte en ell mateix, ja que les noves propostes de Networks-on-Chip (NoC) han de servir un tràfic eminentment variable i heterogeni dels processadors amb molts nuclis. Són necessàries solucions ràpides i flexibles per evitar que les comunicacions dins del xip es converteixin en el pròxim coll d'ampolla de rendiment, situació que limitaria en gran mesura l'espai de disseny a nivell d'arquitectura i portaria a l'ús d'arquitectures i models de programació lents, ineficients o poc programables. L'aparició de noves tecnologies d'interconnexió ha possibilitat la creació de NoCs més flexibles i escalables. En particular, la comunicació intra-xip sense fils ha despertat un interès considerable en virtut de les seva baixa latència, simplicitat, i bon rendiment amb tràfic broadcast. La majoria de les Wireless NoC (WNoC) proposades fins ara s'han centrat en aprofitar l'avantatge en termes de latència d'aquest nou paradigma creant múltiples canals sense fils per interconnectar nuclis allunyats entre sí. Aquesta estratègia és efectiva per complementar a NoCs clàssiques en escales mitjanes, però és probable que altres tecnologies com la nanofotònica puguin jugar millor aquest paper a escales més grans. Aquesta tesi presenta el concepte de Broadcast-Oriented WNoC (BoWNoC), un nou enfoc que intenta rendibilitzar al màxim la inherent simplicitat, flexibilitat, i capacitats broadcast de la tecnologia sense fils integrant una antena i transmissor/receptor per cada nucli del processador. Aquest paradigma forma part d'una visió més àmplia on un BoWNoC serviria tràfic broadcast i urgent, mentre que una xarxa convencional serviria fluxos de dades més pesats. En virtut de la escalabilitat i del seu suport broadcast, BoWNoC podria convertir-se en un element clau en una gran varietat d'arquitectures i algoritmes poc convencionals que milloressin considerablement el rendiment, l'eficiència, l'escalabilitat i la programabilitat de processadors amb molts nuclis. El present treball té com a objectius no només estudiar els aspectes fonamentals del paradigma BoWNoC, sinó també demostrar la seva viabilitat des dels punts de vista de la implementació, i del disseny de xarxa i arquitectura. Una exploració a la capa física valida la viabilitat de l'enfoc usant tecnologies longituds d'ona milimètriques en un futur proper, i suggereix l'ús d'antenes de grafè a la banda dels terahertz ja a més llarg termini. A capa d'enllaç, la tesi aporta una anàlisi del context de l'aplicació que és, més tard, utilitzada per al disseny d'un protocol d'accés al medi que permet servir tràfic broadcast a baixa latència i de forma fiable. A capa de xarxa, la nostra visió híbrida és avaluada posant èmfasi en la flexibilitat que aporta el fet de prendre les decisions a nivell de la interfície de xarxa, mostrant grans millores de rendiment per una àmplia selecció de patrons de tràfic. A nivell d'arquitectura, l'impacte que el concepte de BoWNoC pot tenir sobre el disseny de processadors amb molts nuclis no només és debatut de forma qualitativa i genèrica, sinó també avaluat quantitativament per una arquitectura concreta enfocada a la sincronització. Els resultats demostren que l'impacte de BoWNoC pot anar més enllà d'una millora en termes de rendiment de xarxa; representant, possiblement, un canvi radical a l'era dels molts nuclisAward-winningPostprint (published version