Power-constrained aware and latency-aware microarchitectural optimizations in many-core processors

As the transistor budgets outpace the power envelope (the power-wall issue), new architectural and microarchitectural techniques are needed to improve, or at least maintain, the power efficiency of next-generation processors. Run-time adaptation, including core, cache and DVFS adaptations, has recently emerged as a promising area to keep the pace for acceptable power efficiency. However, none of the adaptation techniques proposed so far is able to provide good results when we consider the stringent power budgets that will be common in the next decades, so new techniques that attack the problem from several fronts using different specialized mechanisms are necessary. The combination of different power management mechanisms, however, bring extra levels of complexity, since other factors such as workload behavior and run-time conditions must also be considered to properly allocate power among cores and threads. To address the power issue, this thesis first proposes Chrysso, an integrated and scalable model-driven power management that quickly selects the best combination of adaptation methods out of different core and uncore micro-architecture adaptations, per-core DVFS, or any combination thereof. Chrysso can quickly search the adaptation space by making performance/power projections to identify Pareto-optimal configurations, effectively pruning the search space. Chrysso achieves 1.9x better chip performance over core-level gating for multi-programmed workloads, and 1.5x higher performance for multi-threaded workloads. Most existing power management schemes use a centralized approach to regulate power dissipation. Unfortunately, the complexity and overhead of centralized power management increases significantly with core count rendering it in-viable at fine-grain time slices. The work leverages a two-tier hierarchical power manager. This solution is highly scalable with low overhead on a tiled many-core architecture with shared LLC and per-tile DVFS at fine-grain time slices. The global power is first distributed across tiles using GPM and then within a tile (in parallel across all tiles). Additionally, this work also proposes DVFS and cache-aware thread migration (DCTM) to ensure optimum per-tile co-scheduling of compatible threads at runtime over the two-tier hierarchical power manager. DCTM outperforms existing solutions by up to 12% on adaptive many-core tile processor. With the advancements in the core micro-architectural techniques and technology scaling, the performance gap between the computational component and memory component is increasing significantly (the memory-wall issue). To bridge this gap, the architecture community is pushing forward towards multi-core architecture with on-die near-memory DRAM cache memory (faster than conventional DRAM). Gigascale DRAM Caches poses a problem of how to efficiently manage the tags. The Tags-in-DRAM designs aims at efficiently co-locate tags with data, but it still suffer from high latency especially in multi-way associativity. The thesis finally proposes Tag Cache mechanism, an on-chip distributed tag caching mechanism with limited space and latency overhead to bypass the tag read operation in multi-way DRAM Caches, thereby reducing hit latency. Each Tag Cache, stored in L2, stores tag information of the most recently used DRAM Cache ways. The Tag Cache is able to exploit temporal locality of the DRAM Cache, thereby contributing to on average 46% of the DRAM Cache hits.A mesura que el consum dels transistors supera el nivell de potència desitjable es necessiten noves tècniques arquitectòniques i microarquitectòniques per millorar, o almenys mantenir, l'eficiència energètica dels processadors de les pròximes generacions. L'adaptació en temps d'execució, tant de nuclis com de les cachés, així com també adaptacions DVFS són idees que han sorgit recentment que fan preveure que sigui un àrea prometedora per mantenir un ritme d'eficiència energètica acceptable. Tanmateix, cap de les tècniques d'adaptació proposades fins ara és capaç d'oferir bons resultats si tenim en compte les restriccions estrictes de potència que seran comuns a les pròximes dècades. És convenient definir noves tècniques que ataquin el problema des de diversos fronts utilitzant diferents mecanismes especialitzats. La combinació de diferents mecanismes de gestió d'energia porta aparellada nivells addicionals de complexitat, ja que altres factors com ara el comportament de la càrrega de treball així com condicions específiques de temps d'execució també han de ser considerats per assignar adequadament la potència entre els nuclis del sistema computador. Per tractar el tema de la potència, aquesta tesi proposa en primer lloc Chrysso, una administració d'energia integrada i escalable que selecciona ràpidament la millor combinació entre diferents adaptacions microarquitectòniques. Chrysso pot buscar ràpidament l'adaptació adequada al fer projeccions òptimes de rendiment i potència basades en configuracions de Pareto, permetent així reduir de manera efectiva l'espai de cerca. Chrysso arriba a un rendiment de 1,9 sobre tècniques convencionals d'inhibició de portes amb una càrrega d'aplicacions seqüencials; i un rendiment de 1,5 quan les aplicacions corresponen a programes parla·lels. La majoria dels sistemes de gestió d'energia existents utilitzen un enfocament centralitzat per regular la dissipació d'energia. Malauradament, la complexitat i el temps d'administració s'incrementen significativament amb una gran quantitat de nuclis. En aquest treball es defineix un gestor jeràrquic de potència basat en dos nivells. Aquesta solució és altament escalable amb baix cost operatiu en una arquitectura de múltiples nuclis integrats en clústers, amb memòria caché de darrer nivell compartida a nivell de cluster, i DVFS establert en intervals de temps de gra fi a nivell de clúster. La potència global es distribueix en primer lloc a través dels clústers utilitzant GPM i després es distribueix dins un clúster (en paral·lel si es consideren tots els clústers). A més, aquest treball també proposa DVFS i migració de fils conscient de la memòria caché (DCTM) que garanteix una òptima distribució de tasques entre els nuclis. DCTM supera les solucions existents fins a un 12%. Amb els avenços en la tecnologia i les tècniques de micro-arquitectura de nuclis, la diferència de rendiment entre el component computacional i la memòria està augmentant significativament. Per omplir aquest buit, s'està avançant cap a arquitectures de múltiples nuclis amb memòries caché integrades basades en DRAM. Aquestes memòries caché DRAM a gran escala plantegen el problema de com gestionar de forma eficaç les etiquetes. Els dissenys de cachés amb dades i etiquetes juntes són un primer pas, però encara pateixen per tenir una alta latència, especialment en cachés amb un grau alt d'associativitat. En aquesta tesi es proposa l'estudi d'una tècnica anomenada Tag Cache, un mecanisme distribuït d'emmagatzematge d'etiquetes, que redueix la latència de les operacions de lectura d'etiquetes en les memòries caché DRAM. Cada Tag Cache, que resideix a L2, emmagatzema la informació de les vies que s'han accedit recentment de les memòries caché DRAM. D'aquesta manera es pot aprofitar la localitat temporal d'una caché DRAM, fet que contribueix en promig en un 46% dels encerts en les caché DRAM

Modular Architectures And Optimization Techniques For Power And Reliability In Future Many Core Microprocessors

Power and reliability issues are expected to increase in future multicore systems with a higher degree of component integration. As the feature sizes of transistors continue to shrink, more resources can be incorporated in microprocessors to address a broader spectrum of different application requirements. However, power constraints will limit the amount of resources that can be powered on at any given time. Recent studies have shown that future multicore systems will be able to power on less than 80% of their transistors in the near future, and less than 50% in the long term. The most difficult challenge is deciding which transistors should be powered on at any given time to deliver high performance under strict power constraints. At the same time, device reliability issues - the proliferation of devices that will either be defective at manufacturing time or will fail in the field with usage - are projected to be exacerbated by the continued scaling of device sizes. We present a modular, dynamically reconfigurable architecture as a promising unified solution to the problems of dark silicon (the inability to power all available computing resources) and reliability. Our modular architecture implements deconfigurable lanes within the decoupled sections of a superscalar pipeline that can be easily powered on or off to isolate faults or create an energy-efficient hardware configuration tailored to the needs of the running software. At the system level, we propose a novel framework that uses surrogate response surfaces and heuristic global optimization algorithms to characterize the behavior of applications at runtime and dynamically redistribute the available chip-wide power to obtain hardware configurations customized for the software diversity and system goals. Our reconfigurable architecture is able to provide high performance under a strict power budget, maintain a certain performance level at a reduced power cost, and in the case of hard faults, restore the system's performance to pre-fault levels

3rd Many-core Applications Research Community (MARC) Symposium. (KIT Scientific Reports ; 7598)

This manuscript includes recent scientific work regarding the Intel Single Chip Cloud computer and describes approaches for novel approaches for programming and run-time organization

Coordinating Resource Use in Open Distributed Systems

In an open distributed system, computational resources are peer-owned, and distributed over time and space. The system is open to interactions with its environment, and the resources can dynamically join or leave the system, or can be discovered at runtime. This dynamicity leads to opportunities to carry out computations without statically owned resources, harnessing the collective compute power of the resources connected by the Internet. However, realizing this potential requires efficient and scalable resource discovery, coordination, and control, which present challenges in a dynamic, open environment. In this thesis, I present an approach to address these challenges by separating the functionality concerns of concurrent computations from those of coordinating their resource use, with the purpose of reducing programming complexity, and aiding development of correct, efficient, and resource-aware concurrent programs. As a first step towards effectively coordinating distributed resources, I developed DREAM, a Distributed Resource Estimation and Allocation Model, which enables computations to reason about future availability of resources. I then developed a fine-grained resource coordination scheme for distributed computations. The coordination scheme integrates DREAM-based resource reasoning into a distributed scheduler, for deciding and enforcing fine-grained resource-use schedules for distributed computations. To control the overhead caused by the coordination, a tuner is implemented which explicitly balances the overhead of the control mechanisms against the extent of control exercised. The effectiveness and performance of the resource coordination approach have been evaluated using a number of case studies. Experimental results show that the approach can effectively schedule computations for supporting various types of coordination objectives, such as ensuring Quality-of-Service, power-efficient execution, and dynamic load balancing. The overhead caused by the coordination mechanism is relatively modest, and adjustable through the tuner. In addition, the coordination mechanism does not add extra programming complexity to computations

Finding, Measuring, and Reducing Inefficiencies in Contemporary Computer Systems

Computer systems have become increasingly diverse and specialized in recent years. This complexity supports a wide range of new computing uses and users, but is not without cost: it has become difficult to maintain the efficiency of contemporary general purpose computing systems. Computing inefficiencies, which include nonoptimal runtimes, excessive energy use, and limits to scalability, are a serious problem that can result in an inability to apply computing to solve the world's most important problems. Beyond the complexity and vast diversity of modern computing platforms and applications, a number of factors make improving general purpose efficiency challenging, including the requirement that multiple levels of the computer system stack be examined, that legacy hardware devices and software may stand in the way of achieving efficiency, and the need to balance efficiency with reusability, programmability, security, and other goals. This dissertation presents five case studies, each demonstrating different ways in which the measurement of emerging systems can provide actionable advice to help keep general purpose computing efficient. The first of the five case studies is Parallel Block Vectors, a new profiling method for understanding parallel programs with a fine-grained, code-centric perspective aids in both future hardware design and in optimizing software to map better to existing hardware. Second is a project that defines a new way of measuring application interference on a datacenter's worth of chip-multiprocessors, leading to improved scheduling where applications can more effectively utilize available hardware resources. Next is a project that uses the GT-Pin tool to define a method for accelerating the simulation of GPGPUs, ultimately allowing for the development of future hardware with fewer inefficiencies. The fourth project is an experimental energy survey that compares and combines the latest energy efficiency solutions at different levels of the stack to properly evaluate the state of the art and to find paths forward for future energy efficiency research. The final project presented is NRG-Loops, a language extension that allows programs to measure and intelligently adapt their own power and energy use

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

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

Optimizing Resource Management in Cloud Analytics Services

The fundamental challenge in the cloud today is how to build and optimize machine learning and data analytical services. Machine learning and data analytical platforms are changing computing infrastructure from expensive private data centers to easily accessible online services. These services pack user requests as jobs and run them on thousands of machines in parallel in geo-distributed clusters. The scale and the complexity of emerging jobs lead to increasing challenges for the clusters at all levels, from power infrastructure to system architecture and corresponding software framework design. These challenges come in many forms. Today's clusters are built on commodity hardware and hardware failures are unavoidable. Resource competition, network congestion, and mixed generations of hardware make the hardware environment complex and hard to model and predict. Such heterogeneity becomes a crucial roadblock for efficient parallelization on both the task level and job level. Another challenge comes from the increasing complexity of the applications. For example, machine learning services run jobs made up of multiple tasks with complex dependency structures. This complexity leads to difficulties in framework designs. The scale, especially when services span geo-distributed clusters, leads to another important hurdle for cluster design. Challenges also come from the power infrastructure. Power infrastructure is very expensive and accounts for more than 20% of the total costs to build a cluster. Power sharing optimization to maximize the facility utilization and smooth peak hour usages is another roadblock for cluster design. In this thesis, we focus on solutions for these challenges at the task level, on the job level, with respect to the geo-distributed data cloud design and for power management in colocation data centers. At the task level, a crucial hurdle to achieving predictable performance is stragglers, i.e., tasks that take significantly longer than expected to run. At this point, speculative execution has been widely adopted to mitigate the impact of stragglers in simple workloads. We apply straggler mitigation for approximation jobs for the first time. We present GRASS, which carefully uses speculation to mitigate the impact of stragglers in approximation jobs. GRASS's design is based on the analysis of a model we develop to capture the optimal speculation levels for approximation jobs. Evaluations with production workloads from Facebook and Microsoft Bing in an EC2 cluster of 200 nodes show that GRASS increases accuracy of deadline-bound jobs by 47% and speeds up error-bound jobs by 38%. Moving from task level to job level, task level speculation mechanisms are designed and operated independently of job scheduling when, in fact, scheduling a speculative copy of a task has a direct impact on the resources available for other jobs. Thus, we present Hopper, a job-level speculation-aware scheduler that integrates the tradeoffs associated with speculation into job scheduling decisions based on a model generalized from the task-level speculation model. We implement both centralized and decentralized prototypes of the Hopper scheduler and show that 50% (66%) improvements over state-of-the-art centralized (decentralized) schedulers and speculation strategies can be achieved through the coordination of scheduling and speculation. As computing resources move from local clusters to geo-distributed cloud services, we are expecting the same transformation for data storage. We study two crucial pieces of a geo-distributed data cloud system: data acquisition and data placement. Starting from developing the optimal algorithm for the case of a data cloud made up of a single data center, we propose a near-optimal, polynomial-time algorithm for a geo-distributed data cloud in general. We show, via a case study, that the resulting design, Datum, is near-optimal (within 1.6%) in practical settings. Efficient power management is a fundamental challenge for data centers when providing reliable services. Power oversubscription in data centers is very common and may occasionally trigger an emergency when the aggregate power demand exceeds the capacity. We study power capping solutions for handling such emergencies in a colocation data center, where the operator supplies power to multiple tenants. We propose a novel market mechanism based on supply function bidding, called COOP, to financially incentivize and coordinate tenants' power reduction for minimizing total performance loss while satisfying multiple power capping constraints. We demonstrate that COOP is "win-win", increasing the operator's profit (through oversubscription) and reducing tenants' costs (through financial compensation for their power reduction during emergencies).</p

A Scalable and Adaptive Network on Chip for Many-Core Architectures

In this work, a scalable network on chip (NoC) for future many-core architectures is proposed and investigated. It supports different QoS mechanisms to ensure predictable communication. Self-optimization is introduced to adapt the energy footprint and the performance of the network to the communication requirements. A fault tolerance concept allows to deal with permanent errors. Moreover, a template-based automated evaluation and design methodology and a synthesis flow for NoCs is introduced