Energy and Reliability in Future NOC Interconnected CMPS

In this dissertation, I explore energy and reliability in future NoC (Network-on-Chip) interconnected CMPs (chip multiprocessors) as they have become a first-order constraint in future CMP design. In the first part, we target the root cause of network energy consumption through techniques that reduce link and router-level switching activity. We specifically focus on memory subsystem traffic, as it comprises the bulk of NoC load in a CMP. By transmitting only the flits that contain words that we predicted would be useful using a novel spatial locality predictor, our scheme seeks to reduce network activity. We aim to further lower NoC energy consumption through microarchitectural mechanisms that inhibit datapath switching activity caused by unused words in individual flits. Using simulation-based performance studies and detailed energy models based on synthesized router designs and different link wire types, we show that (a) the pre- diction mechanism achieves very high accuracy, with an average rate of false-unused prediction of just 2.5%; (b) the combined NoC energy savings enabled by the predictor and microarchitectural support are 36% on average and up to 57% in the best case; and (c) there is no system performance penalty as a result of this technique. In the second part, we present a method for dynamic voltage/frequency scaling of networks-on-chip and last level caches in CMP designs, where the shared resources form a single voltage/frequency domain. We develop a new technique for monitoring and control and validate it by running PARSEC benchmarks through full system simulations. These techniques reduce energy-delay product by 46% compared to a state-of-the-art prior work. In the third part, we develop critical path models for HCI- and NBTI-induced wear assuming stress caused under realistic workload conditions, and apply them onto the interconnect microarchitecture. A key finding from this modeling is that, counter to prevailing wisdom, wearout in the CMP on-chip interconnect is correlated with a lack of load observed in the NoC routers, rather than high load. We then develop a novel wearout-decelerating scheme in which routers under low load have their wearout-sensitive components exercised without significantly impacting the router’s cycle time, pipeline depth, and area or power consumption. We subsequently show that the proposed design yields a 13.8∼65× increase in CMP lifetime

Cross-Layer Approaches for an Aging-Aware Design of Nanoscale Microprocessors

Thanks to aggressive scaling of transistor dimensions, computers have revolutionized our life. However, the increasing unreliability of devices fabricated in nanoscale technologies emerged as a major threat for the future success of computers. In particular, accelerated transistor aging is of great importance, as it reduces the lifetime of digital systems. This thesis addresses this challenge by proposing new methods to model, analyze and mitigate aging at microarchitecture-level and above

Efficient and Scalable Computing for Resource-Constrained Cyber-Physical Systems: A Layered Approach

With the evolution of computing and communication technology, cyber-physical systems such as self-driving cars, unmanned aerial vehicles, and mobile cognitive robots are achieving increasing levels of multifunctionality and miniaturization, enabling them to execute versatile tasks in a resource-constrained environment. Therefore, the computing systems that power these resource-constrained cyber-physical systems (RCCPSs) have to achieve high efficiency and scalability. First of all, given a fixed amount of onboard energy, these computing systems should not only be power-efficient but also exhibit sufficiently high performance to gracefully handle complex algorithms for learning-based perception and AI-driven decision-making. Meanwhile, scalability requires that the current computing system and its components can be extended both horizontally, with more resources, and vertically, with emerging advanced technology. To achieve efficient and scalable computing systems in RCCPSs, my research broadly investigates a set of techniques and solutions via a bottom-up layered approach. This layered approach leverages the characteristics of each system layer (e.g., the circuit, architecture, and operating system layers) and their interactions to discover and explore the optimal system tradeoffs among performance, efficiency, and scalability. At the circuit layer, we investigate the benefits of novel power delivery and management schemes enabled by integrated voltage regulators (IVRs). Then, between the circuit and microarchitecture/architecture layers, we present a voltage-stacked power delivery system that offers best-in-class power delivery efficiency for many-core systems. After this, using Graphics Processing Units (GPUs) as a case study, we develop a real-time resource scheduling framework at the architecture and operating system layers for heterogeneous computing platforms with guaranteed task deadlines. Finally, fast dynamic voltage and frequency scaling (DVFS) based power management across the circuit, architecture, and operating system layers is studied through a learning-based hierarchical power management strategy for multi-/many-core systems

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing

Energy Aware Runtime Systems for Elastic Stream Processing Platforms

Following an invariant growth in the required computational performance of processors, the multicore revolution started around 20 years ago. This revolution was mainly an answer to power dissipation constraints restricting the increase of clock frequency in single-core processors. The multicore revolution not only brought in the challenge of parallel programming, i.e. being able to develop software exploiting the entire capabilities of manycore architectures, but also the challenge of programming heterogeneous platforms. The question of “on which processing element to map a specific computational unit?”, is well known in the embedded community. With the introduction of general-purpose graphics processing units (GPGPUs), digital signal processors (DSPs) along with many-core processors on different system-on-chip platforms, heterogeneous parallel platforms are nowadays widespread over several domains, from consumer devices to media processing platforms for telecom operators. Finding mapping together with a suitable hardware architecture is a process called design-space exploration. This process is very challenging in heterogeneous many-core architectures, which promise to offer benefits in terms of energy efficiency. The main problem is the exponential explosion of space exploration. With the recent trend of increasing levels of heterogeneity in the chip, selecting the parameters to take into account when mapping software to hardware is still an open research topic in the embedded area. For example, the current Linux scheduler has poor performance when mapping tasks to computing elements available in hardware. The only metric considered is CPU workload, which as was shown in recent work does not match true performance demands from the applications. Doing so may produce an incorrect allocation of resources, resulting in a waste of energy. The origin of this research work comes from the observation that these approaches do not provide full support for the dynamic behavior of stream processing applications, especially if these behaviors are established only at runtime. This research will contribute to the general goal of developing energy-efficient solutions to design streaming applications on heterogeneous and parallel hardware platforms. Streaming applications are nowadays widely spread in the software domain. Their distinctive characiteristic is the retrieving of multiple streams of data and the need to process them in real time. The proposed work will develop new approaches to address the challenging problem of efficient runtime coordination of dynamic applications, focusing on energy and performance management.Efter en oföränderlig tillväxt i prestandakrav hos processorer, började den flerkärniga processor-revolutionen för ungefär 20 år sedan. Denna revolution skedde till största del som en lösning till begränsningar i energieffekten allt eftersom klockfrekvensen kontinuerligt höjdes i en-kärniga processorer. Den flerkärniga processor-revolutionen medförde inte enbart utmaningen gällande parallellprogrammering, m.a.o. förmågan att utveckla mjukvara som använder sig av alla delelement i de flerkärniga processorerna, men också utmaningen med programmering av heterogena plattformar. Frågeställningen ”på vilken processorelement skall en viss beräkning utföras?” är väl känt inom ramen för inbyggda datorsystem. Efter introduktionen av grafikprocessorer för allmänna beräkningar (GPGPU), signalprocesserings-processorer (DSP) samt flerkärniga processorer på olika system-on-chip plattformar, är heterogena parallella plattformar idag omfattande inom många domäner, från konsumtionsartiklar till mediaprocesseringsplattformar för telekommunikationsoperatörer. Processen att placera beräkningarna på en passande hårdvaruplattform kallas för utforskning av en designrymd (design-space exploration). Denna process är mycket utmanande för heterogena flerkärniga arkitekturer, och kan medföra fördelar när det gäller energieffektivitet. Det största problemet är att de olika valmöjligheterna i designrymden kan växa exponentiellt. Enligt den nuvarande trenden som förespår ökad heterogeniska aspekter i processorerna är utmaningen att hitta den mest passande placeringen av beräkningarna på hårdvaran ännu en forskningsfråga inom ramen för inbyggda datorsystem. Till exempel, den nuvarande schemaläggaren i Linux operativsystemet är inkapabel att hitta en effektiv placering av beräkningarna på den underliggande hårdvaran. Det enda mätsättet som används är processorns belastning vilket, som visats i tidigare forskning, inte motsvarar den verkliga prestandan i applikationen. Användning av detta mätsätt vid resursallokering resulterar i slöseri med energi. Denna forskning härstammar från observationerna att dessa tillvägagångssätt inte stöder det dynamiska beteendet hos ström-processeringsapplikationer (stream processing applications), speciellt om beteendena bara etableras vid körtid. Denna forskning kontribuerar till det allmänna målet att utveckla energieffektiva lösningar för ström-applikationer (streaming applications) på heterogena flerkärniga hårdvaruplattformar. Ström-applikationer är numera mycket vanliga i mjukvarudomän. Deras distinkta karaktär är inläsning av flertalet dataströmmar, och behov av att processera dem i realtid. Arbetet i denna forskning understöder utvecklingen av nya sätt för att lösa det utmanade problemet att effektivt koordinera dynamiska applikationer i realtid och fokus på energi- och prestandahantering

Energy efficient core designs for upcoming process technologies

Energy efficiency has been a first order constraint in the design of micro processors for the last decade. As Moore's law sunsets, new technologies are being actively explored to extend the march in increasing the computational power and efficiency. It is essential for computer architects to understand the opportunities and challenges in utilizing the upcoming process technology trends in order to design the most efficient processors. In this work, we consider three process technology trends and propose core designs that are best suited for each of the technologies. The process technologies are expected to be viable over a span of timelines. We first consider the most popular method currently available to improve the energy efficiency, i.e. by lowering the operating voltage. We make key observations regarding the limiting factors in scaling down the operating voltage for general purpose high performance processors. Later, we propose our novel core design, ScalCore, one that can work in high performance mode at nominal Vdd, and in a very energy-efficient mode at low Vdd. The resulting core design can operate at much lower voltages providing higher parallel performance while consuming lower energy. While lowering Vdd improves the energy efficiency, CMOS devices are fundamentally limited in their low voltage operation. Therefore, we next consider an upcoming device technology -- Tunneling Field-Effect Transistors (TFETs), that is expected to supplement CMOS device technology in the near future. TFETs can attain much higher energy efficiency than CMOS at low voltages. However, their performance saturates at high voltages and, therefore, cannot entirely replace CMOS when high performance is needed. Ideally, we desire a core that is as energy-efficient as TFET and provides as much performance as CMOS. To reach this goal, we characterize the TFET device behavior for core design and judiciously integrate TFET units, CMOS units in a single core. The resulting core, called HetCore, can provide very high energy efficiency while limiting the slowdown when compared to a CMOS core. Finally, we analyze Monolithic 3D (M3D) integration technology that is widely considered to be the only way to integrate more transistors on a chip. We present the first analysis of the architectural implications of using M3D for core design and show how to partition the core across different layers. We also address one of the key challenges in realizing the technology, namely, the top layer performance degradation. We propose a critical path based partitioning for logic stages and asymmetric bit/port partitioning for storage stages. The result is a core that performs nearly as well as a core without any top layer slowdown. When compared to a 2D baseline design, an M3D core not only provides much higher performance, it also reduces the energy consumption at the same time. In summary, this thesis addresses one of the fundamental challenges in computer architecture -- overcoming the fact that CMOS is not scaling anymore. As we increase the computing power on a single chip, our ability to power the entire chip keeps decreasing. This thesis proposes three solutions aimed at solving this problem over different timelines. Across all our solutions, we improve energy efficiency without compromising the performance of the core. As a result, we are able to operate twice as many cores with in the same power budget as regular cores, significantly alleviating the problem of dark silicon