Energy-efficient electrical and silicon-photonic networks in many core systems

Thesis (Ph.D.)--Boston UniversityDuring the past decade, the very large scale integration (VLSI) community has migrated towards incorporating multiple cores on a single chip to sustain the historic performance improvement in computing systems. As the core count continuously increases, the performance of network-on-chip (NoC), which is responsible for the communication between cores, caches and memory controllers, is increasingly becoming critical for sustaining the performance improvement. In this dissertation, we propose several methods to improve the energy efficiency of both electrical and silicon-photonic NoCs. Firstly, for electrical NoC, we propose a flow control technique, Express Virtual Channel with Taps (EVC-T), to transmit both broadcast and data packets efficiently in a mesh network. A low-latency notification tree network is included to maintain t he order of broadcast packets. The EVC-T technique improves the NoC latency by 24% and the system energy efficiency in terms of energy-delay product (EDP) by 13%. In the near future, the silicon-photonic links are projected to replace the electrical links for global on-chip communication due to their lower data-dependent power and higher bandwidth density, but the high laser power can more than offset these advantages. Therefore, we propose a silicon-photonic multi-bus NoC architecture and a methodology that can reduce the laser power by 49% on average through bandwidth reconfiguration at runtime based on the variations in bandwidth requirements of applications. We also propose a technique to reduce the laser power by dynamically activating/deactivating the 12 cache banks and switching ON/ OFF the corresponding silicon-photonic links in a crossbar NoC. This cache-reconfiguration based technique can save laser power by 23.8% and improves system EDP by 5.52% on average. In addition, we propose a methodology for placing and sharing on-chip laser sources by jointly considering the bandwidth requirements, thermal constraints and physical layout constraints. Our proposed methodology for placing and sharing of on-chip laser sources reduces laser power. In addition to reducing the laser power to improve the energy efficiency of silicon-photonic NoCs, we propose to leverage the large bandwidth provided by silicon-photonic NoC to share computing resources. The global sharing of floating-point units can save system area by 13.75% and system power by 10%

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

Parallel architectures and runtime systems co-design for task-based programming models

The increasing parallelism levels in modern computing systems has extolled the need for a holistic vision when designing multiprocessor architectures taking in account the needs of the programming models and applications. Nowadays, system design consists of several layers on top of each other from the architecture up to the application software. Although this design allows to do a separation of concerns where it is possible to independently change layers due to a well-known interface between them, it is hampering future systems design as the Law of Moore reaches to an end. Current performance improvements on computer architecture are driven by the shrinkage of the transistor channel width, allowing faster and more power efficient chips to be made. However, technology is reaching physical limitations were the transistor size will not be able to be reduced furthermore and requires a change of paradigm in systems design. This thesis proposes to break this layered design, and advocates for a system where the architecture and the programming model runtime system are able to exchange information towards a common goal, improve performance and reduce power consumption. By making the architecture aware of runtime information such as a Task Dependency Graph (TDG) in the case of dataflow task-based programming models, it is possible to improve power consumption by exploiting the critical path of the graph. Moreover, the architecture can provide hardware support to create such a graph in order to reduce the runtime overheads and making possible the execution of fine-grained tasks to increase the available parallelism. Finally, the current status of inter-node communication primitives can be exposed to the runtime system in order to perform a more efficient communication scheduling, and also creates new opportunities of computation and communication overlap that were not possible before. An evaluation of the proposals introduced in this thesis is provided and a methodology to simulate and characterize the application behavior is also presented.El aumento del paralelismo proporcionado por los sistemas de cómputo modernos ha provocado la necesidad de una visión holística en el diseño de arquitecturas multiprocesador que tome en cuenta las necesidades de los modelos de programación y las aplicaciones. Hoy en día el diseño de los computadores consiste en diferentes capas de abstracción con una interfaz bien definida entre ellas. Las limitaciones de esta aproximación junto con el fin de la ley de Moore limitan el potencial de los futuros computadores. La mayoría de las mejoras actuales en el diseño de los computadores provienen fundamentalmente de la reducción del tamaño del canal del transistor, lo cual permite chips más rápidos y con un consumo eficiente sin apenas cambios fundamentales en el diseño de la arquitectura. Sin embargo, la tecnología actual está alcanzando limitaciones físicas donde no será posible reducir el tamaño de los transistores motivando así un cambio de paradigma en la construcción de los computadores. Esta tesis propone romper este diseño en capas y abogar por un sistema donde la arquitectura y el sistema de tiempo de ejecución del modelo de programación sean capaces de intercambiar información para alcanzar una meta común: La mejora del rendimiento y la reducción del consumo energético. Haciendo que la arquitectura sea consciente de la información disponible en el modelo de programación, como puede ser el grafo de dependencias entre tareas en los modelos de programación dataflow, es posible reducir el consumo energético explotando el camino critico del grafo. Además, la arquitectura puede proveer de soporte hardware para crear este grafo con el objetivo de reducir el overhead de construir este grado cuando la granularidad de las tareas es demasiado fina. Finalmente, el estado de las comunicaciones entre nodos puede ser expuesto al sistema de tiempo de ejecución para realizar una mejor planificación de las comunicaciones y creando nuevas oportunidades de solapamiento entre cómputo y comunicación que no eran posibles anteriormente. Esta tesis aporta una evaluación de todas estas propuestas, así como una metodología para simular y caracterizar el comportamiento de las aplicacionesPostprint (published version

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.Siirretty Doriast

Resource Management Algorithms for Computing Hardware Design and Operations: From Circuits to Systems

The complexity of computation hardware has increased at an unprecedented rate for the last few decades. On the computer chip level, we have entered the era of multi/many-core processors made of billions of transistors. With transistor budget of this scale, many functions are integrated into a single chip. As such, chips today consist of many heterogeneous cores with intensive interaction among these cores. On the circuit level, with the end of Dennard scaling, continuously shrinking process technology has imposed a grand challenge on power density. The variation of circuit further exacerbated the problem by consuming a substantial time margin. On the system level, the rise of Warehouse Scale Computers and Data Centers have put resource management into new perspective. The ability of dynamically provision computation resource in these gigantic systems is crucial to their performance. In this thesis, three different resource management algorithms are discussed. The first algorithm assigns adaptivity resource to circuit blocks with a constraint on the overhead. The adaptivity improves resilience of the circuit to variation in a cost-effective way. The second algorithm manages the link bandwidth resource in application specific Networks-on-Chip. Quality-of-Service is guaranteed for time-critical traffic in the algorithm with an emphasis on power. The third algorithm manages the computation resource of the data center with precaution on the ill states of the system. Q-learning is employed to meet the dynamic nature of the system and Linear Temporal Logic is leveraged as a tool to describe temporal constraints. All three algorithms are evaluated by various experiments. The experimental results are compared to several previous work and show the advantage of our methods

Efficient Connection Allocator in Network-on-Chip

As semiconductor technologies develop, a System-on-Chip (SoC) that integrates all semiconductor intellectual property (IP) cores is suggested and widely used for various applications. A traditional bus interconnection does not support transmitting data between IP cores for high performance. Because of this reason, a Network-on-Chip (NoC) has been suggested to provide an efficient and scalable solution to interconnect among all IP cores. High throughput and low latency have recently become the main important factors of NoC for achieving hard guaranteed real-time systems. In order to guarantee these factors and provide real-time service (i.e., Guaranteed Service, GS), the circuit switching (CS) approach has been widely utilized. The CS approach allocates mutually exclusive paths to transmitting data between different sources and destinations using dedicated NoC resources. However, the exclusive occupancy of the allocated path reduces the efficiency of the overall use of NoC resources. In order to solve this problem, Space-Division-Multiplexing (SDM) and Time-Division-Multiplexing (TDM) techniques have been suggested. SDM implements a circuit switching technique by assigning physically different NoC-links between different connections. Path connections of the SDM technique based on spatial resources assignment do not provide high scalability. In contrast to this, using virtual time slots for a path connection, the TDM technique can share physical links between exclusively established connections, thereby improving NoC path diversity. For all of these mentioned techniques, the factor that significantly impacts the system efficiency or performance scaling is how the path is allocated. In recent years, a dynamic connection allocation approach that can cope with highly dynamic workloads has been gaining attention due to the sudden and diverse demands of applications in real-time systems. There are two groups in the dynamic connection allocation approach. One is a distributed allocation technique, and the other is a centralized allocation technique. While distributed allocation exploits additional logic integrated into the NoC-routers for path search and allocation, the centralized approach makes use of a central unit to manage the path allocation problem. There are several algorithms for the centralized allocation technique. Trellis search-based allocation approach shows the best performance among them. Many algorithms related to centralized connection allocators have been studied extensively during the past decade. However, relatively little attention was paid to methodology in analyzing and evaluating the centralized connection allocation algorithms. In order to further develop the algorithms, it is necessary to understand and evaluate the centralized connection allocator by establishing a new analysis methodology. Thus, this thesis presents a performance analysis methodology for the trellis search-based allocation approach. Firstly, this thesis proposes a system model for analysis. Secondly, performance metrics are defined. Finally, the analysis results of each performance metric related to the trellis search-based allocation approach are presented. Through this analysis, the performance of the trellis search-based allocation approach can be accurately analyzed. Although a simulation is not performed, the upper limit of performance of the trellis search-based allocation approach can also be predicted through the analysis metrics. Additionally, we introduce the general formulation of the trellis search-based path allocation algorithm. The weight values among available paths through the branch metric and path metric are proposed to enable higher performance path connection. Furthermore, according to network size, topology, TDM, interface load delivery, and router internal storage, the performance of trellis search-based path allocation algorithms is also described. In the end, the Application Specific Instruction Processor (ASIP) hardware platform customized for the trellis search-based path allocation algorithm is presented. The shortest available and lowest-cost (SALC) path search algorithm is proposed to improve the success rate of path connection in the ASIP hardware platform. We evaluate the algorithm performance and implementation synthesis results. In order to realize the dynamic connection approach, a short execution cycle of ASIP time is essential. We develop several algorithms to achieve this short execution cycle. The first one is a rectangular region of search algorithm that allows adapting the size and form of path search region according to the particular source-destination positions and considers actual operational constraints. The average execution cycles for searching an optimum path are decreased because the unnecessary region for path-search is excluded. The second one is a path-spreading search algorithm that separates between involved routers and uninvolved routers in path search. The involved routers are selected and spread out from source to destination at each intermediate trellis-search process. The path-search overhead is considerably reduced due to the router involvements. The third one is a three-directional path-spreading search algorithm that eliminates one direction movement among four spreading movements. Because of this reason, the trellis search-based path connection algorithm, which omits the back-tracing process, can be implemented in the ASIP platform. Thus, the whole algorithm execution time can be halved. The last one is a moving regional path search algorithm that significantly reduces computation complexity by selecting a constant dimensional path-search region that affects performance and moving the region from source to destination. The moving regional path search algorithm achieves a considerable decrement of computational complexity.:1 Introduction 1 1.1 NoC-interconnect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Connection allocation in a Network-on-Chip 7 2.1 Circuit Switching NoCs . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Guaranteed Service in NoCs . . . . . . . . . . . . . . . . . . . 7 2.1.2 Spatial-Division-Multiplexing technique . . . . . . . . . . . . 8 2.1.3 Time-Division-Multiplexing technique . . . . . . . . . . . . . 10 2.2 System architectures employing circuit switching NoCs . . . . . . . . 11 2.2.1 Static and dynamic connection allocation . . . . . . . . . . . 12 2.2.2 Distributed connection allocation technique . . . . . . . . . . 14 2.2.3 Centralized connection allocation technique . . . . . . . . . . 16 2.2.4 Algorithms for centralized connection allocation . . . . . . . . 17 2.2.4.1 Software based run-time path allocation approach . 18 2.2.4.2 Trellis search-based allocation approach . . . . . . . 19 3 Performance analysis methodology for a centralized connection allocator 23 3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2 Performance metrics and analysis methodology . . . . . . . . . . . . 25 3.3 System simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4 Trellis search-based path allocation algorithm 45 4.1 General formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.1.1 Trellis graph structure . . . . . . . . . . . . . . . . . . . . . . 45 4.1.2 Survivor path selection criterion . . . . . . . . . . . . . . . . . 52 ix 4.1.2.1 Branch metric and path metric . . . . . . . . . . . . 52 4.1.2.2 The shortest-available and lowest-cost path selection criterion . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.2 Algorithm Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2.1 Network topology . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2.2 Network size . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.2.3 Time-Division-Multiplexing . . . . . . . . . . . . . . . . . . . 61 4.2.4 NoC interface load diversity . . . . . . . . . . . . . . . . . . . 63 4.2.5 The internal storage of the router . . . . . . . . . . . . . . . . 66 5 ASIP approach for Trellis search-based connection allocation 73 5.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.1.1 Trellis search-based ASIP platform architecture . . . . . . . . 74 5.2 Algorithm for improving success rates of path connection . . . . . . . 81 5.2.1 SALC algorithm for Trellis search-based ASIP platform . . . . 81 5.2.2 Performance evaluation of the SALC algorithm . . . . . . . . 88 5.2.2.1 Simulation results . . . . . . . . . . . . . . . . . . . 88 5.2.2.2 Synthesis results . . . . . . . . . . . . . . . . . . . . 91 5.3 Algorithm for reducing path-search time . . . . . . . . . . . . . . . . 93 5.3.1 Rectangular regional path search algorithm . . . . . . . . . . 93 5.3.2 Path-spreading search algorithm . . . . . . . . . . . . . . . . 99 5.3.3 Three directional path-spreading search algorithm . . . . . . 108 5.3.4 Moving regional path search algorithm . . . . . . . . . . . . . 114 5.3.5 Performance evaluation . . . . . . . . . . . . . . . . . . . . . 123 5.3.5.1 Simulation results . . . . . . . . . . . . . . . . . . . 123 5.3.5.2 Synthesis results . . . . . . . . . . . . . . . . . . . . 126 6 Conclusion and Future work 131 6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 6.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Bibliography 13