Traffic Characteristics of a Distributed Memory System

We believe that many distributed computing systems of the future will use distributed shared memory as a technique for interprocess communication. Thus, traffic generated by memory requests will be a major component of the traffic for any networks which connect nodes in such a system. In this paper, we study memory reference strings gathered with a tracing program we devised. We study several models. First, we look at raw reference data, as would be seen if the network were a backplane. Second, we examine references in units of blocks , first using a one-block cache model and then with an infinite cache. Finally, we study the effect of predictive prepaging of these blocks on the traffic. We provide a novel representation of memory reference data which can be used to calculate interarrival distributions directly. Integrating communication with computation can be used to control both traffic and performance

Side-Channel Attacks on Intel SGX: How SGX Amplifies The Power of Cache Attack

In modern computing environments, hardware resources are commonly shared, and parallel computation is more widely used. Users run their services in parallel on the same hardware and process information with different confidentiality levels every day. Running parallel tasks can cause privacy and security problems if proper isolation is not enforced. Computers need to rely on a trusted root to protect the data from malicious entities. Intel proposed the Software Guard eXtension (SGX) to create a trusted execution environment (TEE) within the processor. SGX allows developers to benefit from the hardware level isolation. SGX relies only on the hardware, and claims runtime protection even if the OS and other software components are malicious. However, SGX disregards any kind of side-channel attacks. Researchers have demonstrated that microarchitectural sidechannels are very effective in thwarting the hardware provided isolation. In scenarios that involve SGX as part of their defense mechanism, system adversaries become important threats, and they are capable of initiating these attacks. This work introduces a new and more powerful cache side-channel attack that provides system adversaries a high resolution channel. The developed attack is able to virtually track all memory accesses of SGX execution with temporal precision. As a proof of concept, we demonstrate our attack to recover cryptographic AES keys from the commonly used implementations including those that were believed to be resistant in previous attack scenarios. Our results show that SGX cannot protect critical data sensitive computations, and efficient AES key recovery is possible in a practical environment. In contrast to previous attacks which require hundreds of measurements, this is the first cache side-channel attack on a real system that can recover AES keys with a minimal number of measurements. We can successfully recover the AES key from T-Table based implementations in a known plaintext and ciphertext scenario with an average of 15 and 7 samples respectively

Hardware thread scheduling algorithms for single-ISA asymmetric CMPs

Through the past several decades, based on the Moore's law, the semiconductor industry was doubling the number of transistors on the single chip roughly every eighteen months. For a long time this continuous increase in transistor budget drove the increase in performance as the processors continued to exploit the instruction level parallelism (ILP) of the sequential programs. This pattern hit the wall in the early years of the twentieth century when designing larger and more complex cores became difficult because of the power and complexity reasons. Computer architects responded by integrating many cores on the same die thereby creating Chip Multicore Processors (CMP). In the last decade, the computing technology experienced tremendous developments, Chip Multiprocessors (CMP) expanded from the symmetric and homogeneous to the asymmetric or heterogeneous Multiprocessors. Having cores of different types in a single processor enables optimizing performance, power and energy efficiency for a wider range of workloads. It enables chip designers to employ specialization (that is, we can use each type of core for the type of computation where it delivers the best performance/energy trade-off). The benefits of Asymmetric Chip Multiprocessors (ACMP) are intuitive as it is well known that different workloads have different resource requirements. The CMPs improve the performance of applications by exploiting the Thread Level Parallelism (TLP). Parallel applications relying on multiple threads must be efficiently managed and dispatched for execution if the parallelism is to be properly exploited. Since more and more applications become multi-threaded we expect to find a growing number of threads executing on a machine. Consequently, the operating system will require increasingly larger amounts of CPU time to schedule these threads efficiently. Thus, dynamic thread scheduling techniques are of paramount importance in ACMP designs since they can make or break performance benefits derived from the asymmetric hardware or parallel software. Several thread scheduling methods have been proposed and applied to ACMPs. In this thesis, we first study the state of the art thread scheduling techniques and identify the main reasons limiting the thread level parallelism in an ACMP systems. We propose three novel approaches to schedule and manage threads and exploit thread level parallelism implemented in hardware, instead of perpetuating the trend of performing more complex thread scheduling in the operating system. Our first goal is to improve the performance of an ACMP systems by improving thread scheduling at the hardware level. We also show that the hardware thread scheduling reduces the energy consumption of an ACMP systems by allowing better utilization of the underlying hardware.A través de las últimas décadas, con base en la ley de Moore, la industria de semiconductores duplica el número de transistores en el chip alrededor de una vez cada dieciocho meses. Durante mucho tiempo, este aumento continuo en el número de transistores impulsó el aumento en el rendimiento de los procesadores solo explotando el paralelismo a nivel de instrucción (ILP) y el aumento de la frecuencia de los procesadores, permitiendo un aumento del rendimiento de los programas secuenciales. Este patrón llego a su limite en los primeros años del siglo XX, cuando el diseño de procesadores más grandes y complejos se convirtió en una tareá difícil debido a las debido al consumo requerido. La respuesta a este problema por parte de los arquitectos fue la integración de muchos núcleos en el mismo chip creando así chip multinúcleo Procesadores (CMP). En la última década, la tecnología de la computación experimentado enormes avances, sobre todo el en chip multiprocesadores (CMP) donde se ha pasado de diseños simetricos y homogeneous a sistemas asimétricos y heterogeneous. Tener núcleos de diferentes tipos en un solo procesador permite optimizar el rendimiento, la potencia y la eficiencia energética para una amplia gama de cargas de trabajo. Permite a los diseñadores de chips emplear especialización (es decir, podemos utilizar un tipo de núcleo diferente para distintos tipos de cálculo dependiendo del trade-off respecto del consumo y rendimiento). Los beneficios de la asimétrica chip multiprocesadores (ACMP) son intuitivos, ya que es bien sabido que diferentes cargas de trabajo tienen diferentes necesidades de recursos. Los CMP mejoran el rendimiento de las aplicaciones mediante la explotación del paralelismo a nivel de hilo (TLP). En las aplicaciones paralelas que dependen de múltiples hilos, estos deben ser manejados y enviados para su ejecución, y el paralelismo se debe explotar de manera eficiente. Cada día hay mas aplicaciones multi-hilo, por lo tanto encotraremos un numero mayor de hilos que se estaran ejecutando en la máquina. En consecuencia, el sistema operativo requerirá cantidades cada vez mayores de tiempo de CPU para organizar y ejecutar estos hilos de manera eficiente. Por lo tanto, las técnicas de optimizacion dinámica para la organizacion de la ejecucion de hilos son de suma importancia en los diseños ACMP ya que pueden incrementar o dsiminuir el rendimiento del hardware asimétrico o del software paralelo. Se han propuesto y aplicado a ACMPs varios métodos de organizar y ejecutar los hilos. En esta tesis, primero estudiamos el estado del arte en las técnicas para la gestionar la ejecucion de los hilos y hemos identificado las principales razones que limitan el paralelismo en sistemas ACMP. Proponemos tres nuevos enfoques para programar y gestionar los hilos y explotar el paralelismo a nivel de hardware, en lugar de perpetuar la tendencia actual de dejar esta gestion cada vez maas compleja al sistema operativo. Nuestro primer objetivo es mejorar el rendimiento de un sistema ACMP mediante la mejora en la gestion de los hilos a nivel de hardware. También mostramos que la gestion del los hilos a nivel de hardware reduce el consumo de energía de un sistemas de ACMP al permitir una mejor utilización del hardware subyacente

Model-driven dual caching For nomadic service-oriented architecture clients

Mobile devices have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. However, the most significant step in the evolution of mobile devices was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity such as email, web browsers and maybe most importantly smart/rich clients. Being able to host smart clients allows the users of mobile devices to seamlessly access the Information Technology (IT) resources of their organizations. One increasingly popular way of enabling access to IT resources is by using Web Services (WS). This trend has been aided by the rapid availability of WS packages/tools, most notably the efforts of the Apache group and Integrated Development Environment (IDE) vendors. But the widespread use of WS raises questions for users of mobile devices such as laptops or PDAs; how and if they can participate in WS. Unlike their “wired” counterparts (desktop computers and servers) they rely on a wireless network that is characterized by low bandwidth and unreliable connectivity.The aim of this thesis is to enable mobile devices to host Web Services consumers. It introduces a Model-Driven Dual Caching (MDDC) approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth

Mixed Speculative Multithreaded Execution Models

Institute for Computing Systems ArchitectureThe current trend toward chip multiprocessor architectures has placed great pressure on programmers and compilers to generate thread-parallel programs. Improved execution performance can no longer be obtained via traditional single-thread instruction level parallelism (ILP), but, instead, via multithreaded execution. One notable technique that facilitates the extraction of parallel threads from sequential applications is thread-level speculation (TLS). This technique allows programmers/compilers to generate threads without checking for inter-thread data and control dependences, which are then transparently enforced by the hardware. Most prior work on TLS has concentrated on thread selection and mechanisms to efficiently support the main TLS operations, such as squashes, data versioning, and commits. This thesis seeks to enhance TLS functionality by combining it with other speculative multithreaded execution models. The main idea is that TLS already requires extensive hardware support, which when slightly augmented can accommodate other speculative multithreaded techniques. Recognizing that for different applications, or even program phases, the application bottlenecks may be different, it is reasonable to assume that the more versatile a system is, the more efficiently it will be able to execute the given program. As mentioned above, generating thread-parallel programs is hard and TLS has been suggested as an execution model that can speculatively exploit thread-level parallelism (TLP) even when thread independence cannot be guaranteed by the programmer/ compiler. Alternatively, the helper threads (HT) execution model has been proposed where subordinate threads are executed in parallel with a main thread in order to improve the execution efficiency (i.e., ILP) of the latter. Yet another execution model, runahead execution (RA), has also been proposed where subordinate versions of the main thread are dynamically created especially to cope with long-latency operations, again with the aim of improving the execution efficiency of the main thread (ILP). Each one of these multithreaded execution models works best for different applications and application phases. We combine these three models into a single execution model and single hardware infrastructure such that the system can dynamically adapt to find the most appropriate multithreaded execution model. More specifically, TLS is favored whenever successful parallel execution of instructions in multiple threads (i.e., TLP) is possible and the system can seamlessly transition at run-time to the other models otherwise. In order to understand the tradeoffs involved, we also develop a performance model that allows one to quantitatively attribute overall performance gains to either TLP or ILP in such combined multithreaded execution model. Experimental results show that our combined execution model achieves speedups of up to 41.2%, with an average of 10.2%, over an existing state-of-the-art TLS system and speedups of up to 35.2%, with an average of 18.3%, over a flavor of runahead execution for a subset of the SPEC2000 Integer benchmark suite. We then investigate how a common ILP-enhancingmicroarchitectural feature, namely branch prediction, interacts with TLS.We show that branch prediction for TLS is even more important than it is for single core machines. Unfortunately, branch prediction for TLS systems is also inherently harder. Code partitioning and re-executions of squashed threads pollute the branch history making it harder for predictors to be accurate. We thus propose to augment the hardware, so as to accommodate Multi-Path (MP) execution within the existing TLS protocol. Under the MP execution model, all paths following a number of hard-to-predict conditional branches are followed. MP execution thus, removes branches that would have been otherwise mispredicted helping in this way the processor to exploit more ILP. We show that with only minimal hardware support, one can combine these two execution models into a unified one, which can achieve far better performance than both TLS and MP execution. Experimental results show that our combied execution model achieves speedups of up to 20.1%, with an average of 8.8%, over an existing state-of-the-art TLS system and speedups of up to 125%, with an average of 29.0%, when compared with multi-path execution for a subset of the SPEC2000 Integer benchmark suite. Finally, Since systems that support speculative multithreading usually treat all threads equally, they are energy-inefficient. This inefficiency stems from the fact that speculation occasionally fails and, thus, power is spent on threads that will have to be discarded. We propose a profitability-based power allocation scheme, where we “steal” power from non-profitable threads and use it to speed up more useful ones. We evaluate our techniques for a state-of-the-art TLS system and show that, with minimalhardware support, we achieve improvements in ED of up to 25.5% with an average of 18.9%, for a subset of the SPEC 2000 Integer benchmark suite

Smart memory management through locality analysis

Las memorias caché fueron incorporadas en los microprocesadores ya desde los primeros tiempos, y representan la solución más común para tratar la diferencia de velocidad entre el procesador y la memoria. Sin embargo, muchos estudios señalan que la capacidad de almacenamiento de la caché es malgastada muchas veces, lo cual tiene un impacto directo en el rendimiento del procesador. Aunque una caché está diseñada para explotar diferentes tipos de localidad, todas la referencias a memoria son tratadas de la misma forma, ignorando comportamientos particulares de localidad. El uso restringido de la información de localidad para cada acceso a memoria puede limitar la eficiencia de la cache. En esta tesis se demuestra como un análisis de localidad de datos puede ayudar al investigador a entender dónde y porqué ocurren los fallos de caché, y proponer entonces diferentes técnicas que hacen uso de esta información con el objetivo de mejorar el rendimiento de la memoria caché. Proponemos técnicas en las cuales la información de localidad obtenida por el analizador de localidad es pasada desde el compilador al hardware a través del ISA para guiar el manejo de los accesos a memoria.Hemos desarrollado un análisis estático de localidad de datos. Este análisis está basado en los vectores de reuso y contiene los tres típicos pasos: reuso, volumen y análisis de interferencias. Comparado con trabajos previos, tanto el análisis de volúmenes como el de interferencias ha sido mejorado utilizando información de profiling así como un análisis de interferencias más preciso. El analizador de localidad de datos propuesto ha sido incluido como un paso más en un compilador de investigación. Los resultados demuestran que, para aplicaciones numéricas, el análisis es muy preciso y el overhead de cálculo es bajo. Este análisis es la base para todas las otras partes de la tesis. Además, para algunas propuestas en la última parte de la tesis, hemos usado un análisis de localidad de datos basado en las ecuaciones de fallos de cache. Este análisis, aunque requiere más tiempo de cálculo, es más preciso y más apropiado para cachés asociativas por conjuntos. El uso de dos análisis de localidad diferentes también demuestra que las propuestas arquitectónicas de esta tesis son independientes del análisis de localidad particular utilizado.Después de mostrar la precisión del análisis, lo hemos utilizado para estudiar el comportamiento de localidad exhibido por los programas SPECfp95. Este tipo de análisis es necesario antes de proponer alguna nueva técnica ya que ayuda al investigador a entender porqué ocurren los fallos de caché. Se muestra que con el análisis propuesto se puede estudiar de forma muy precisa la localidad de un programa y detectar donde estan los "puntos negros" así como la razón de estos fallos en cache. Este estudio del comportamiento de localidad de diferentes programas es la base y motivación para las diferentes técnicas propuestas en esta tesis para mejorar el rendimiento de la memoria.Así, usando el análisis de localidad de datos y basándonos en los resultados obtenidos después de analizar el comportamiento de localidad de un conjunto de programas, proponemos utilizar este análisis con el objetivo de guiar tres técnicas diferentes: (i) manejo de caches multimódulo, (ii) prebúsqueda software para bucles con planificación módulo, y (iii) planificación de instrucciones de arquitecturas VLIW clusterizadas.El primer uso del análisis de localidad propuesto es el manejo de una novedosa organización de caché. Esta caché soporta bypass y/o está compuesta por diferentes módulos, cada uno orientado a explotar un tipo particular de localidad. La mayor diferencia de esta caché con respecto propuestas previas es que la decisión de "cachear" o no, o en qué módulo un nuevo bloque es almacenado, está controlado por algunos bits en las instrucciones de memoria ("pistas" de localidad). Estas "pistas" (hints) son fijadas en tiempo de compilación utilizando el análisis de localidad propuesto. Así, la complejidad del manejo de esta caché se mantiene bajo ya que no requiere ningún hardware adicional. Los resultados demuestran que cachés más pequeñas con un manejo más inteligente pueden funcionar tan bien (o mejor) que cachés convencionales más grandes.Hemos utilizado también el análisis de localidad para estudiar la interacción entre la segmentación software y la prebúsqueda software. La segmentación software es una técnica muy efectiva para la planificación de código en bucles (principalmente en aplicaciones numéricas en procesadores VLIW). El esquema más popular de prebúsqueda software se llama planificación módulo. Muchos trabajos sobre planificación módulo se pueden encontrar en la literatura, pero casi todos ellos consideran una suposición crítica: consideran un comportamiento optimista de la cache (en otras palabras, usan siempre la latencia de acierto cuando planifican instrucciones de memoria). Así, los resultados que presentan ignoran los efectos del bloqueo debido a dependencias con instrucciones de memoria. En esta parte de la tesis mostramos que esta suposición puede llevar a planificaciones cuyo rendimiento es bastante más bajo cuando se considera una memoria real. Nosotros proponemos un algoritmo para planificar instrucciones de memoria en bucles con planificación módulo. Hemos estudiado diferentes estrategias de prebúsqueda software y finalmente hemos propuesto un algoritmo que realiza prebúsqueda basándose en el análisis de localidad y en la forma del grafo de dependencias del bucle. Los resultados obtenidos demuestran que el esquema propuesto mejora el rendimiento de las otras heurísticas ya que obtiene un mejor compromiso entre tiempo de cálculo y de bloqueo.Finalmente, el último uso del análisis de localidad estudiado en esta tesis es para guiar un planificador de instrucciones para arquitecturas VLIW clusterizadas. Las arquitecturas clusterizadas están siendo una tendencia común en el diseño de procesadores empotrados/DSP. Típicamente, el núcleo de estos procesadores está basado en un diseño VLIW el cual particiona tanto el banco de registros como las unidades funcionales. En este trabajo vamos un paso más allá y también hacemos la partición de la memoria caché. En este caso, tanto las comunicaciones entre registros como entre memorias han de ser consideradas. Nosotros proponemos un algoritmo que realiza la partición del grafo así como la planificación de instrucciones en un único paso en lugar de hacerlo secuencialmente, lo cual se demuestra que es más efectivo. Este algoritmo es mejorado añadiendo una análisis basado en las ecuaciones de fallos de cache con el objetivo de guiar en la planificación de las instrucciones de memoria para reducir no solo comunicaciones entre registros, sino también fallos de cache.Cache memories were incorporated in microprocessors in the early times and represent the most common solution to deal with the gap between processor and memory speeds. However, many studies point out that the cache storage capacity is wasted many times, which means a direct impact in processor performance. Although a cache is designed to exploit different types of locality, all memory references are handled in the same way, ignoring particular locality behaviors. The restricted use of the locality information for each memory access can limit the effectivity of the cache. In this thesis we show how a data locality analysis can help the researcher to understand where and why cache misses occur, and then to propose different techniques that make use of this information in order to improve the performance of cache memory. We propose techniques in which locality information obtained by the locality analyzer is passed from the compiler to the hardware through the ISA to guide the management of memory accesses.We have developed a static data locality analysis. This analysis is based on reuse vectors and performs the three typical steps: reuse, volume and interfere analysis. Compared with previous works, both volume and interference analysis have been improved by using profile information as well as a more precise inter-ference analysis. The proposed data locality analyzer has been inserted as another pass in a research compiler. Results show that for numerical applications the analysis is very accurate and the computing overhead is low. This analysis is the base for all other parts of the thesis. In addition, for some proposals in the last part of the thesis we have used a data locality analysis based on cache miss equations. This analysis, although more time consuming, is more accurate and more appropriate for set-associative caches. The usage of two different locality analyzers also shows that the architectural proposals of this thesis are independent from the particular locality analysis.After showing the accuracy of the analysis, we have used it to study the locality behavior exhibited by the SPECfp95 programs. This kind of analysis is necessary before proposing any new technique since can help the researcher to understand why cache misses occur. We show that with the proposed analysis we can study very accurately the locality of a program and detect where the hot spots are as well as the reason for these misses. This study of the locality behavior of different programs is the base and motivation for the different techniques proposed in this thesis to improve the memory performance.Thus, using the data locality analysis and based on the results obtained after analyzing the locality behavior of a set of programs, we propose to use this analysis in order to guide three different techniques: (i) management of multi-module caches, (ii) software prefetching for modulo scheduled loops, and (iii) instruction scheduling for clustered VLIW architectures.The first use of the proposed data locality analysis is to manage a novel cache organization. This cache supports bypassing and/or is composed of different modules, each one oriented to exploit a particular type of locality. The main difference of this cache with respect to previous proposals is that the decision of caching or not, or in which module a new fetched block is allocated is managed by some bits in memory instructions (locality hints). These hints are set at compile time using the proposed locality analysis. Thus, the management complexity of this cache is kept low since no additional hardware is required. Results show that smaller caches with a smart management can perform as well as (or better than) bigger conventional caches.We have also used the locality analysis to study the interaction between software pipelining and software prefetching. Software pipelining has been shown to be a very effective scheduling technique for loops (mainly in numerical applications for VLIW processors). The most popular scheme for software pipelining is called modulo scheduling. Many works on modulo scheduling can be found in the literature, but almost all of them make a critical assumption: they consider an optimistic behavior of the cache (in other words, they use the hit latency when a memory instruction is scheduled). Thus, the results they present ignore the effect of stalls due to dependences with memory instructions. In this part of the thesis we show that this assumption can lead to schedules whose performance is rather low when a real memory is considered. Thus, we propose an algorithm to schedule memory instructions in modulo scheduled loops. We have studied different software prefetching strategies and finally proposed an algorithm that performs prefetching based on the locality analysis and the shape of the loop dependence graph. Results obtained shows that the proposed scheme outperforms other heuristic approaches since it achieves a better trade-off between compute and stall time than the others. Finally, the last use of the locality analysis studied in this thesis is to guide an instruction scheduler for a clustered VLIW architecture. Clustered architectures are becoming a common trend in the design of embedded/DSP processors. Typically, the core of these processors is based on a VLIW design which partitionates both register file and functional units. In this work we go a step beyond and also make a partition of the cache memory. Then, both inter-register and inter-memory communications have to be taken into account. We propose an algorithm that performs both graph partition and instruction scheduling in a single step instead of doing it sequentially, which is shown to be more effective. This algorithm is improved by adding an analysis based on the cache miss equations in order to guide the scheduling of memory instructions in clusters with the aim of reducing not only inter-register communications, but also cache misses

Enabling Hyperscale Web Services

Modern web services such as social media, online messaging, web search, video streaming, and online banking often support billions of users, requiring data centers that scale to hundreds of thousands of servers, i.e., hyperscale. In fact, the world continues to expect hyperscale computing to drive more futuristic applications such as virtual reality, self-driving cars, conversational AI, and the Internet of Things. This dissertation presents technologies that will enable tomorrow’s web services to meet the world’s expectations. The key challenge in enabling hyperscale web services arises from two important trends. First, over the past few years, there has been a radical shift in hyperscale computing due to an unprecedented growth in data, users, and web service software functionality. Second, modern hardware can no longer support this growth in hyperscale trends due to a decline in hardware performance scaling. To enable this new hyperscale era, hardware architects must become more aware of hyperscale software needs and software researchers can no longer expect unlimited hardware performance scaling. In short, systems researchers can no longer follow the traditional approach of building each layer of the systems stack separately. Instead, they must rethink the synergy between the software and hardware worlds from the ground up. This dissertation establishes such a synergy to enable futuristic hyperscale web services. This dissertation bridges the software and hardware worlds, demonstrating the importance of that bridge in realizing efficient hyperscale web services via solutions that span the systems stack. The specific goal is to design software that is aware of new hardware constraints and architect hardware that efficiently supports new hyperscale software requirements. This dissertation spans two broad thrusts: (1) a software and (2) a hardware thrust to analyze the complex hyperscale design space and use insights from these analyses to design efficient cross-stack solutions for hyperscale computation. In the software thrust, this dissertation contributes uSuite, the first open-source benchmark suite of web services built with a new hyperscale software paradigm, that is used in academia and industry to study hyperscale behaviors. Next, this dissertation uses uSuite to study software threading implications in light of today’s hardware reality, identifying new insights in the age-old research area of software threading. Driven by these insights, this dissertation demonstrates how threading models must be redesigned at hyperscale by presenting an automated approach and tool, uTune, that makes intelligent run-time threading decisions. In the hardware thrust, this dissertation architects both commodity and custom hardware to efficiently support hyperscale software requirements. First, this dissertation characterizes commodity hardware’s shortcomings, revealing insights that influenced commercial CPU designs. Based on these insights, this dissertation presents an approach and tool, SoftSKU, that enables cheap commodity hardware to efficiently support new hyperscale software paradigms, improving the efficiency of real-world web services that serve billions of users, saving millions of dollars, and meaningfully reducing the global carbon footprint. This dissertation also presents a hardware-software co-design, uNotify, that redesigns commodity hardware with minimal modifications by using existing hardware mechanisms more intelligently to overcome new hyperscale overheads. Next, this dissertation characterizes how custom hardware must be designed at hyperscale, resulting in industry-academia benchmarking efforts, commercial hardware changes, and improved software development. Based on this characterization’s insights, this dissertation presents Accelerometer, an analytical model that estimates gains from hardware customization. Multiple hyperscale enterprises and hardware vendors use Accelerometer to make well-informed hardware decisions.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169802/1/akshitha_1.pd