Polymorphic computing abstraction for heterogeneous architectures

Integration of multiple computing paradigms onto system on chip (SoC) has pushed the boundaries of design space exploration for hardware architectures and computing system software stack. The heterogeneity of computing styles in SoC has created a new class of architectures referred to as Heterogeneous Architectures. Novel applications developed to exploit the different computing styles are user centric for embedded SoC. Software and hardware designers are faced with several challenges to harness the full potential of heterogeneous architectures. Applications have to execute on more than one compute style to increase overall SoC resource utilization. The implication of such an abstraction is that application threads need to be polymorphic. Operating system layer is thus faced with the problem of scheduling polymorphic threads. Resource allocation is also an important problem to be dealt by the OS. Morphism evolution of application threads is constrained by the availability of heterogeneous computing resources. Traditional design optimization goals such as computational power and lower energy per computation are inadequate to satisfy user centric application resource needs. Resource allocation decisions at application layer need to permeate to the architectural layer to avoid conflicting demands which may affect energy-delay characteristics of application threads. We propose Polymorphic computing abstraction as a unified computing model for heterogeneous architectures to address the above issues. Simulation environment for polymorphic applications is developed and evaluated under various scheduling strategies to determine the effectiveness of polymorphism abstraction on resource allocation. User satisfaction model is also developed to complement polymorphism and used for optimization of resource utilization at application and network layer of embedded systems

Intelligent systems for efficiency and security

As computing becomes ubiquitous and personalized, resources like energy, storage and time are becoming increasingly scarce and, at the same time, computing systems must deliver in multiple dimensions, such as high performance, quality of service, reliability, security and low power. Building such computers is hard, particularly when the operating environment is becoming more dynamic, and systems are becoming heterogeneous and distributed. Unfortunately, computers today manage resources with many ad hoc heuristics that are suboptimal, unsafe, and cannot be composed across the computer’s subsystems. Continuing this approach has severe consequences: underperforming systems, resource waste, information loss, and even life endangerment. This dissertation research develops computing systems which, through intelligent adaptation, deliver efficiency along multiple dimensions. The key idea is to manage computers with principled methods from formal control. It is with these methods that the multiple subsystems of a computer sense their environment and configure themselves to meet system-wide goals. To achieve the goal of intelligent systems, this dissertation makes a series of contributions, each building on the previous. First, it introduces the use of formal MIMO (Multiple Input Multiple Output) control for processors, to simultaneously optimize many goals like performance, power, and temperature. Second, it develops the Yukta control system, which uses coordinated formal controllers in different layers of the stack (hardware and operating system). Third, it uses robust control to develop a fast, globally coordinated and decentralized control framework called Tangram, for heterogeneous computers. Finally, it presents Maya, a defense against power side-channel attacks that uses formal control to reshape the power dissipated by a computer, confusing the attacker. The ideas in the dissertation have been demonstrated successfully with several prototypes, including one built along with AMD (Advanced Micro Devices, Inc.) engineers. These designs significantly outperformed the state of the art. The research in this dissertation brought formal control closer to computer architecture and has been well-received in both domains. It has the first application of full-fledged MIMO control for processors, the first use of robust control in computer systems, and the first application of formal control for side-channel defense. It makes a significant stride towards intelligent systems that are efficient, secure and reliable

Zuverlässige und Energieeffiziente gemischt-kritische Echtzeit On-Chip Systeme

Multi- and many-core embedded systems are increasingly becoming the target for many applications that require high performance under varying conditions. A resulting challenge is the control, and reliable operation of such complex multiprocessing architectures under changes, e.g., high temperature and degradation. In mixed-criticality systems where many applications with varying criticalities are consolidated on the same execution platform, fundamental isolation requirements to guarantee non-interference of critical functions are crucially important. While Networks-on-Chip (NoCs) are the prevalent solution to provide scalable and efficient interconnects for the multiprocessing architectures, their associated energy consumption has immensely increased. Specifically, hard real-time NoCs must manifest limited energy consumption as thermal runaway in such a core shared resource jeopardizes the whole system guarantees. Thus, dynamic energy management of NoCs, as opposed to the related work static solutions, is highly necessary to save energy and decrease temperature, while preserving essential temporal requirements. In this thesis, we introduce a centralized management to provide energy-aware NoCs for hard real-time systems. The design relies on an energy control network, developed on top of an existing switch arbitration network to allow isolation between energy optimization and data transmission. The energy control layer includes local units called Power-Aware NoC controllers that dynamically optimize NoC energy depending on the global state and applications’ temporal requirements. Furthermore, to adapt to abnormal situations that might occur in the system due to degradation, we extend the concept of NoC energy control to include the entire system scope. That is, online resource management employing hierarchical control layers to treat system degradation (imminent core failures) is supported. The mechanism applies system reconfiguration that involves workload migration. For mixed-criticality systems, it allows flexible boundaries between safety-critical and non-critical subsystems to safely apply the reconfiguration, preserving fundamental safety requirements and temporal predictability. Simulation and formal analysis-based experiments on various realistic usecases and benchmarks are conducted showing significant improvements in NoC energy-savings and in treatment of system degradation for mixed-criticality systems improving dependability over the status quo.Eingebettete Many- und Multi-core-Systeme werden zunehmend das Ziel für Anwendungen, die hohe Anfordungen unter unterschiedlichen Bedinungen haben. Für solche hochkomplexed Multi-Prozessor-Systeme ist es eine grosse Herausforderung zuverlässigen Betrieb sicherzustellen, insbesondere wenn sich die Umgebungseinflüsse verändern. In Systeme mit gemischter Kritikalität, in denen viele Anwendungen mit unterschiedlicher Kritikalität auf derselben Ausführungsplattform bedient werden müssen, sind grundlegende Isolationsanforderungen zur Gewährleistung der Nichteinmischung kritischer Funktionen von entscheidender Bedeutung. Während On-Chip Netzwerke (NoCs) häufig als skalierbare Verbindung für die Multiprozessor-Architekturen eingesetzt werden, ist der damit verbundene Energieverbrauch immens gestiegen. Daher sind dynamische Plattformverwaltungen, im Gegensatz zu den statischen, zwingend notwendig, um ein System an die oben genannten Veränderungen anzupassen und gleichzeitig Timing zu gewährleisten. In dieser Arbeit entwickeln wir energieeffiziente NoCs für harte Echtzeitsysteme. Das Design basiert auf einem Energiekontrollnetzwerk, das auf einem bestehenden Switch-Arbitration-Netzwerk entwickelt wurde, um eine Isolierung zwischen Energieoptimierung und Datenübertragung zu ermöglichen. Die Energiesteuerungsschicht umfasst lokale Einheiten, die als Power-Aware NoC-Controllers bezeichnet werden und die die NoC-Energie in Abhängigkeit vom globalen Zustand und den zeitlichen Anforderungen der Anwendungen optimieren. Darüber hinaus wird das Konzept der NoC-Energiekontrolle zur Anpassung an Anomalien, die aufgrund von Abnutzung auftreten können, auf den gesamten Systemumfang ausgedehnt. Online- Ressourcenverwaltungen, die hierarchische Kontrollschichten zur Behandlung Abnutzung (drohender Kernausfälle) einsetzen, werden bereitgestellt. Bei Systemen mit gemischter Kritikalität erlaubt es flexible Grenzen zwischen sicherheitskritischen und unkritischen Subsystemen, um die Rekonfiguration sicher anzuwenden, wobei grundlegende Sicherheitsanforderungen erhalten bleiben und Timing Vorhersehbarkeit. Experimente werden auf der Basis von Simulationen und formalen Analysen zu verschiedenen realistischen Anwendungsfallen und Benchmarks durchgeführt, die signifikanten Verbesserungen bei On-Chip Netzwerke-Energieeinsparungen und bei der Behandlung von Abnutzung für Systeme mit gemischter Kritikalität zur Verbesserung die Systemstabilität gegenüber dem bisherigen Status quo zeigen

Learning-based run-time power and energy management of multi/many-core systems: current and future trends

Multi/Many-core systems are prevalent in several application domains targeting different scales of computing such as embedded and cloud computing. These systems are able to fulfil the everincreasing performance requirements by exploiting their parallel processing capabilities. However, effective power/energy management is required during system operations due to several reasons such as to increase the operational time of battery operated systems, reduce the energy cost of datacenters, and improve thermal efficiency and reliability. This article provides an extensive survey of learning-based run-time power/energy management approaches. The survey includes a taxonomy of the learning-based approaches. These approaches perform design-time and/or run-time power/energy management by employing some learning principles such as reinforcement learning. The survey also highlights the trends followed by the learning-based run-time power management approaches, their upcoming trends and open research challenges

Domain-specific Architectures for Data-intensive Applications

Graphs' versatile ability to represent diverse relationships, make them effective for a wide range of applications. For instance, search engines use graph-based applications to provide high-quality search results. Medical centers use them to aid in patient diagnosis. Most recently, graphs are also being employed to support the management of viral pandemics. Looking forward, they are showing promise of being critical in unlocking several other opportunities, including combating the spread of fake content in social networks, detecting and preventing fraudulent online transactions in a timely fashion, and in ensuring collision avoidance in autonomous vehicle navigation, to name a few. Unfortunately, all these applications require more computational power than what can be provided by conventional computing systems. The key reason is that graph applications present large working sets that fail to fit in the small on-chip storage of existing computing systems, while at the same time they access data in seemingly unpredictable patterns, thus cannot draw benefit from traditional on-chip storage. In this dissertation, we set out to address the performance limitations of existing computing systems so to enable emerging graph applications like those described above. To achieve this, we identified three key strategies: 1) specializing memory architecture, 2) processing data near its storage, and 3) message coalescing in the network. Based on these strategies, this dissertation develops several solutions: OMEGA, which employs specialized on-chip storage units, with co-located specialized compute engines to accelerate the computation; MessageFusion, which coalesces messages in the interconnect; and Centaur, providing an architecture that optimizes the processing of infrequently-accessed data. Overall, these solutions provide 2x in performance improvements, with negligible hardware overheads, across a wide range of applications. Finally, we demonstrate the applicability of our strategies to other data-intensive domains, by exploring an acceleration solution for MapReduce applications, which achieves a 4x performance speedup, also with negligible area and power overheads.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163186/1/abrahad_1.pd

Energy-efficient mobile Web computing

Next-generation Web services will be primarily accessed through mobile devices. However, mobile devices are low-performance and stringently energy-constrained. In my dissertation, I propose the design of a high-performance and energy-efficient mobile Web computing substrate. It is a hardware/software co-designed system that delivers satisfactory user quality-of-service (QoS) experience on a mobile energy budget. The key insight is that the traditional interfaces between different Web stacks need to be enhanced with new abstractions that express user QoS experience and that expose architectural-level complexities. On the basis of the enhanced interfaces, I propose synergistic cross-layer optimizations across the processor architecture, Web runtime, programming language, and application layers to maximize the whole system efficiency. The contributions made in this dissertation will likely have a long-term impact because the target application domain, the Web, is becoming a universal mobile development platform, and because our solutions target the fundamental computation layers of the Web domain.Electrical and Computer Engineerin

Toward Reliable, Secure, and Energy-Efficient Multi-Core System Design

Computer hardware researchers have perennially focussed on improving the performance of computers while stipulating the energy consumption under a strict budget. While several innovations over the years have led to high performance and energy efficient computers, more challenges have also emerged as a fallout. For example, smaller transistor devices in modern multi-core systems are afflicted with several reliability and security concerns, which were inconceivable even a decade ago. Tackling these bottlenecks happens to negatively impact the power and performance of the computers. This dissertation explores novel techniques to gracefully solve some of the pressing challenges of the modern computer design. Specifically, the proposed techniques improve the reliability of on-chip communication fabric under a high power supply noise, increase the energy-efficiency of low-power graphics processing units, and demonstrate an unprecedented security loophole of the low-power computing paradigm through rigorous hardware-based experiments

Methods for Robust and Energy-Efficient Microprocessor Architectures

Σήμερα, η εξέλιξη της τεχνολογίας επιτρέπει τη βελτίωση τριών βασικών στοιχείων της σχεδίασης των επεξεργαστών: αυξημένες επιδόσεις, χαμηλότερη κατανάλωση ισχύος και χαμηλότερο κόστος παραγωγής του τσιπ, ενώ οι σχεδιαστές επεξεργαστών έχουν επικεντρωθεί στην παραγωγή επεξεργαστών με περισσότερες λειτουργίες σε χαμηλότερο κόστος. Οι σημερινοί επεξεργαστές είναι πολύ ταχύτεροι και διαθέτουν εξελιγμένες λειτουργικές μονάδες συγκριτικά με τους προκατόχους τους, ωστόσο, καταναλώνουν αρκετά μεγάλη ενέργεια. Τα ποσά ηλεκτρικής ισχύος που καταναλώνονται, και η επακόλουθη έκλυση θερμότητας, αυξάνονται παρά τη μείωση του μεγέθους των τρανζίστορ. Αναπτύσσοντας όλο και πιο εξελιγμένους μηχανισμούς και λειτουργικές μονάδες για την αύξηση της απόδοσης και βελτίωση της ενέργειας, σε συνδυασμό με τη μείωση του μεγέθους των τρανζίστορ, οι επεξεργαστές έχουν γίνει εξαιρετικά πολύπλοκα συστήματα, καθιστώντας τη διαδικασία της επικύρωσής τους σημαντική πρόκληση για τη βιομηχανία ολοκληρωμένων κυκλωμάτων. Συνεπώς, οι κατασκευαστές επεξεργαστών αφιερώνουν επιπλέον χρόνο, προϋπολογισμό και χώρο στο τσιπ για να διασφαλίσουν ότι οι επεξεργαστές θα λειτουργούν σωστά κατά τη διάθεσή τους στη αγορά. Για τους λόγους αυτούς, η εργασία αυτή παρουσιάζει νέες μεθόδους για την επιτάχυνση και τη βελτίωση της φάσης της επικύρωσης, καθώς και για τη βελτίωση της ενεργειακής απόδοσης των σύγχρονων επεξεργαστών. Στο πρώτο μέρος της διατριβής προτείνονται δύο διαφορετικές μέθοδοι για την επικύρωση του επεξεργαστή, οι οποίες συμβάλλουν στην επιτάχυνση αυτής της διαδικασίας και στην αποκάλυψη σπάνιων σφαλμάτων στους μηχανισμούς μετάφρασης διευθύνσεων των σύγχρονων επεξεργαστών. Και οι δύο μέθοδοι καθιστούν ευκολότερη την ανίχνευση και τη διάγνωση σφαλμάτων, και επιταχύνουν την ανίχνευση του σφάλματος κατά τη φάση της επικύρωσης. Στο δεύτερο μέρος της διατριβής παρουσιάζεται μια λεπτομερής μελέτη χαρακτηρισμού των περιθωρίων τάσης σε επίπεδο συστήματος σε δύο σύγχρονους ARMv8 επεξεργαστές. Η μελέτη του χαρακτηρισμού προσδιορίζει τα αυξημένα περιθώρια τάσης που έχουν προκαθοριστεί κατά τη διάρκεια κατασκευής του κάθε μεμονωμένου πυρήνα του επεξεργαστή και αναλύει τυχόν απρόβλεπτες συμπεριφορές που μπορεί να προκύψουν σε συνθήκες μειωμένης τάσης. Για την μελέτη και καταγραφή της συμπεριφοράς του συστήματος υπό συνθήκες μειωμένης τάσης, παρουσιάζεται επίσης σε αυτή τη διατριβή μια απλή και ενοποιημένη συνάρτηση: η συνάρτηση πυκνότητας-σοβαρότητας. Στη συνέχεια, παρουσιάζεται αναλυτικά η ανάπτυξη ειδικά σχεδιασμένων προγραμμάτων (micro-viruses) τα οποία υποβάλουν της θεμελιώδεις δομές του επεξεργαστή σε μεγάλο φορτίο εργασίας. Αυτά τα προγράμματα στοχεύουν στην γρήγορη αναγνώριση των ασφαλών περιθωρίων τάσης. Τέλος, πραγματοποιείται ο χαρακτηρισμός των περιθωρίων τάσης σε εκτελέσεις πολλαπλών πυρήνων, καθώς επίσης και σε διαφορετικές συχνότητες, και προτείνεται ένα πρόγραμμα το οποίο εκμεταλλεύεται όλες τις διαφορετικές πτυχές του προβλήματος της κατανάλωσης ενέργειας και παρέχει μεγάλη εξοικονόμηση ενέργειας διατηρώντας παράλληλα υψηλά επίπεδα απόδοσης. Αυτή η μελέτη έχει ως στόχο τον εντοπισμό και την ανάλυση της σχέσης μεταξύ ενέργειας και απόδοσης σε διαφορετικούς συνδυασμούς τάσης και συχνότητας, καθώς και σε διαφορετικό αριθμό νημάτων/διεργασιών που εκτελούνται στο σύστημα, αλλά και κατανομής των προγραμμάτων στους διαθέσιμους πυρήνες.Technology scaling has enabled improvements in the three major design optimization objectives: increased performance, lower power consumption, and lower die cost, while system design has focused on bringing more functionality into products at lower cost. While today's microprocessors, are much faster and much more versatile than their predecessors, they also consume much power. As operating frequency and integration density increase, the total chip power dissipation increases. This is evident from the fact that due to the demand for increased functionality on a single chip, more and more transistors are being packed on a single die and hence, the switching frequency increases in every technology generation. However, by developing aggressive and sophisticated mechanisms to boost performance and to enhance the energy efficiency in conjunction with the decrease of the size of transistors, microprocessors have become extremely complex systems, making the microprocessor verification and manufacturing testing a major challenge for the semiconductor industry. Manufacturers, therefore, choose to spend extra effort, time, budget and chip area to ensure that the delivered products are operating correctly. To meet high-dependability requirements, manufacturers apply a sequence of verification tasks throughout the entire life-cycle of the microprocessor to ensure the correct functionality of the microprocessor chips from the various types of errors that may occur after the products are released to the market. To this end, this work presents novel methods for ensuring the correctness of the microprocessor during the post-silicon validation phase and for improving the energy efficiency requirements of modern microprocessors. These methods can be applied during the prototyping phase of the microprocessors or after their release to the market. More specifically, in the first part of the thesis, we present and describe two different ISA-independent software-based post-silicon validation methods, which contribute to formalization and modeling as well as the acceleration of the post-silicon validation process and expose difficult-to-find bugs in the address translation mechanisms (ATM) of modern microprocessors. Both methods improve the detection and diagnosis of a hardware design bug in the ATM structures and significantly accelerate the bug detection during the post-silicon validation phase. In the second part of the thesis we present a detailed system-level voltage scaling characterization study for two state-of-the-art ARMv8-based multicore CPUs. We present an extensive characterization study which identifies the pessimistic voltage guardbands (the increased voltage margins set by the manufacturer) of each individual microprocessor core and analyze any abnormal behavior that may occur in off-nominal voltage conditions. Towards the formalization of the any abnormal behavior we also present a simple consolidated function; the Severity function, which aggregates the effects of reduced voltage operation. We then introduce the development of dedicated programs (diagnostic micro-viruses) that aim to accelerate the time-consuming voltage margins characterization studies by stressing the fundamental hardware components. Finally, we present a comprehensive exploration of how two server-grade systems behave in different frequency and core allocation configurations beyond nominal voltage operation in multicore executions. This analysis aims (1) to identify the best performance per watt operation points, (2) to reveal how and why the different core allocation options affect the energy consumption, and (3) to enhance the default Linux scheduler to take task allocation decisions for balanced performance and energy efficiency

Scalable Emulation of Heterogeneous Systems

The breakdown of Dennard's transistor scaling has driven computing systems toward application-specific accelerators, which can provide orders-of-magnitude improvements in performance and energy efficiency over general-purpose processors. To enable the radical departures from conventional approaches that heterogeneous systems entail, research infrastructure must be able to model processors, memory and accelerators, as well as system-level changes---such as operating system or instruction set architecture (ISA) innovations---that might be needed to realize the accelerators' potential. Unfortunately, existing simulation tools that can support such system-level research are limited by the lack of fast, scalable machine emulators to drive execution. To fill this need, in this dissertation we first present a novel machine emulator design based on dynamic binary translation that makes the following improvements over the state of the art: it scales on multicore hosts while remaining memory efficient, correctly handles cross-ISA differences in atomic instruction semantics, leverages the host floating point (FP) unit to speed up FP emulation without sacrificing correctness, and can be efficiently instrumented to---among other possible uses---drive the execution of a full-system, cross-ISA simulator with support for accelerators. We then demonstrate the utility of machine emulation for studying heterogeneous systems by leveraging it to make two additional contributions. First, we quantify the trade-offs in different coupling models for on-chip accelerators. Second, we present a technique to reuse the private memories of on-chip accelerators when they are otherwise inactive to expand the system's last-level cache, thereby reducing the opportunity cost of the accelerators' integration