Automatic synthesis and optimization of chip multiprocessors

The microprocessor technology has experienced an enormous growth during the last decades. Rapid downscale of the CMOS technology has led to higher operating frequencies and performance densities, facing the fundamental issue of power dissipation. Chip Multiprocessors (CMPs) have become the latest paradigm to improve the power-performance efficiency of computing systems by exploiting the parallelism inherent in applications. Industrial and prototype implementations have already demonstrated the benefits achieved by CMPs with hundreds of cores.CMP architects are challenged to take many complex design decisions. Only a few of them are:- What should be the ratio between the core and cache areas on a chip?- Which core architectures to select?- How many cache levels should the memory subsystem have?- Which interconnect topologies provide efficient on-chip communication?These and many other aspects create a complex multidimensional space for architectural exploration. Design Automation tools become essential to make the architectural exploration feasible under the hard time-to-market constraints. The exploration methods have to be efficient and scalable to handle future generation on-chip architectures with hundreds or thousands of cores.Furthermore, once a CMP has been fabricated, the need for efficient deployment of the many-core processor arises. Intelligent techniques for task mapping and scheduling onto CMPs are necessary to guarantee the full usage of the benefits brought by the many-core technology. These techniques have to consider the peculiarities of the modern architectures, such as availability of enhanced power saving techniques and presence of complex memory hierarchies.This thesis has several objectives. The first objective is to elaborate the methods for efficient analytical modeling and architectural design space exploration of CMPs. The efficiency is achieved by using analytical models instead of simulation, and replacing the exhaustive exploration with an intelligent search strategy. Additionally, these methods incorporate high-level models for physical planning. The related contributions are described in Chapters 3, 4 and 5 of the document.The second objective of this work is to propose a scalable task mapping algorithm onto general-purpose CMPs with power management techniques, for efficient deployment of many-core systems. This contribution is explained in Chapter 6 of this document.Finally, the third objective of this thesis is to address the issues of the on-chip interconnect design and exploration, by developing a model for simultaneous topology customization and deadlock-free routing in Networks-on-Chip. The developed methodology can be applied to various classes of the on-chip systems, ranging from general-purpose chip multiprocessors to application-specific solutions. Chapter 7 describes the proposed model.The presented methods have been thoroughly tested experimentally and the results are described in this dissertation. At the end of the document several possible directions for the future research are proposed

Floorplan-Aware High Performance NoC Design

Las actuales arquitecturas de m�ltiples n�cleos como los chip multiprocesadores (CMP) y soluciones multiprocesador para sistemas dentro del chip (MPSoCs) han adoptado a las redes dentro del chip (NoC) como elemento -ptimo para la inter-conexi-n de los diversos elementos de dichos sistemas. En este sentido, fabricantes de CMPs y MPSoCs han adoptado NoCs sencillas, generalmente con una topolog'a en malla o anillo, ya que son suficientes para satisfacer las necesidades de los sistemas actuales. Sin embargo a medida que los requerimientos del sistema -- baja latencia y alto rendimiento -- se hacen m�s exigentes, estas redes tan simples dejan de ser una soluci-n real. As', la comunidad investigadora ha propuesto y analizado NoCs m�s complejas. No obstante, estas soluciones son m�s dif'ciles de implementar -- especialmente los enlaces largos -- haciendo que este tipo de topolog'as complejas sean demasiado costosas o incluso inviables. En esta tesis, presentamos una metodolog'a de dise-o que minimiza la p�rdida de prestaciones de la red debido a su implementaci-n real. Los principales problemas que se encuentran al implementar una NoC son los conmutadores y los enlaces largos. En esta tesis, el conmutador se ha hecho modular, es decir, formado como uni-n de m-dulos m�s peque-os. En nuestro caso, los m-dulos son id�nticos, donde cada m-dulo es capaz de arbitrar, conmutar, y almacenar los mensajes que le llegan. Posteriormente, flexibilizamos la colocaci-n de estos m-dulos en el chip, permitiendo que m-dulos de un mismo conmutador est�n distribuidos por el chip. Esta metodolog'a de dise-o la hemos aplicado a diferentes escenarios. Primeramente, hemos introducido nuestro conmutador modular en NoCs con topolog'as conocidas como la malla 2D. Los resultados muestran como la modularidad y la distribuci-n del conmutador reducen la latencia y el consumo de potencia de la red. En segundo lugar, hemos utilizado nuestra metodolog'a de dise-o para implementar un crossbar distribuidRoca Pérez, A. (2012). Floorplan-Aware High Performance NoC Design [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17844Palanci

Energy consumption in networks on chip : efficiency and scaling

Computer architecture design is in a new era where performance is increased by replicating processing cores on a chip rather than making CPUs larger and faster. This design strategy is motivated by the superior energy efficiency of the multi-core architecture compared to the traditional monolithic CPU. If the trend continues as expected, the number of cores on a chip is predicted to grow exponentially over time as the density of transistors on a die increases. A major challenge to the efficiency of multi-core chips is the energy used for communication among cores over a Network on Chip (NoC). As the number of cores increases, this energy also increases, imposing serious constraints on design and performance of both applications and architectures. Therefore, understanding the impact of different design choices on NoC power and energy consumption is crucial to the success of the multi- and many-core designs. This dissertation proposes methods for modeling and optimizing energy consumption in multi- and many-core chips, with special focus on the energy used for communication on the NoC. We present a number of tools and models to optimize energy consumption and model its scaling behavior as the number of cores increases. We use synthetic traffic patterns and full system simulations to test and validate our methods. Finally, we take a step back and look at the evolution of computer hardware in the last 40 years and, using a scaling theory from biology, present a predictive theory for power-performance scaling in microprocessor systems

RAMP: A Flat Nanosecond Optical Network and MPI Operations for Distributed Deep Learning Systems

Distributed deep learning (DDL) systems strongly depend on network performance. Current electronic packet switched (EPS) network architectures and technologies suffer from variable diameter topologies, low-bisection bandwidth and over-subscription affecting completion time of communication and collective operations. We introduce a near-exascale, full-bisection bandwidth, all-to-all, single-hop, all-optical network architecture with nanosecond reconfiguration called RAMP, which supports large-scale distributed and parallel computing systems (12.8~Tbps per node for up to 65,536 nodes). For the first time, a custom RAMP-x MPI strategy and a network transcoder is proposed to run MPI collective operations across the optical circuit switched (OCS) network in a schedule-less and contention-less manner. RAMP achieves 7.6-171$\times$ speed-up in completion time across all MPI operations compared to realistic EPS and OCS counterparts. It can also deliver a 1.3-16$\times$ and 7.8-58$\times$ reduction in Megatron and DLRM training time respectively} while offering 42-53$\times$ and 3.3-12.4$\times$ improvement in energy consumption and cost respectively

The k-ary n-direct s-indirect family of topologies for large-scale interconnection networks

The final publication is available at Springer via http://dx.doi.org/10.1007/s11227-016-1640-zIn large-scale supercomputers, the interconnection network plays a key role in system performance. Network topology highly defines the performance and cost of the interconnection network. Direct topologies are sometimes used due to its reduced hardware cost, but the number of network dimensions is limited by the physical 3D space, which leads to an increase of the communication latency and a reduction of network throughput for large machines. Indirect topologies can provide better performance for large machines, but at higher hardware cost. In this paper, we propose a new family of hybrid topologies, the k-ary n-direct s-indirect, that combines the best features from both direct and indirect topologies to efficiently connect an extremely high number of processing nodes. The proposed network is an n-dimensional topology where the k nodes of each dimension are connected through a small indirect topology of s stages. This combination results in a family of topologies that provides high performance, with latency and throughput figures of merit close to indirect topologies, but at a lower hardware cost. In particular, it doubles the throughput obtained per cost unit compared with indirect topologies in most of the cases. Moreover, their fault-tolerance degree is similar to the one achieved by direct topologies built with switches with the same number of ports.This work was supported by the Spanish Ministerio de Economa y Competitividad (MINECO) and by FEDER funds under Grant TIN2012-38341-C04-01 and by Programa de Ayudas de Investigacion y Desarrollo (PAID) from Universitat Politecnica de Valencia.Peñaranda Cebrián, R.; Gómez Requena, C.; Gómez Requena, ME.; López Rodríguez, PJ.; Duato Marín, JF. (2016). 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An In-Depth Analysis of the Slingshot Interconnect

The interconnect is one of the most critical components in large scale computing systems, and its impact on the performance of applications is going to increase with the system size. In this paper, we will describe Slingshot, an interconnection network for large scale computing systems. Slingshot is based on high-radix switches, which allow building exascale and hyperscale datacenters networks with at most three switch-to-switch hops. Moreover, Slingshot provides efficient adaptive routing and congestion control algorithms, and highly tunable traffic classes. Slingshot uses an optimized Ethernet protocol, which allows it to be interoperable with standard Ethernet devices while providing high performance to HPC applications. We analyze the extent to which Slingshot provides these features, evaluating it on microbenchmarks and on several applications from the datacenter and AI worlds, as well as on HPC applications. We find that applications running on Slingshot are less affected by congestion compared to previous generation networks.Comment: To be published in Proceedings of The International Conference for High Performance Computing Networking, Storage, and Analysis (SC '20) (2020

Dynamic Optical Networks for Data Centres and Media Production

This thesis explores all-optical networks for data centres, with a particular focus on network designs for live media production. A design for an all-optical data centre network is presented, with experimental verification of the feasibility of the network data plane. The design uses fast tunable (< 200 ns) lasers and coherent receivers across a passive optical star coupler core, forming a network capable of reaching over 1000 nodes. Experimental transmission of 25 Gb/s data across the network core, with combined wavelength switching and time division multiplexing (WS-TDM), is demonstrated. Enhancements to laser tuning time via current pre-emphasis are discussed, including experimental demonstration of fast wavelength switching (< 35 ns) of a single laser between all combinations of 96 wavelengths spaced at 50 GHz over a range wider than the optical C-band. Methods of increasing the overall network throughput by using a higher complexity modulation format are also described, along with designs for line codes to enable pulse amplitude modulation across the WS-TDM network core. The construction of an optical star coupler network core is investigated, by evaluating methods of constructing large star couplers from smaller optical coupler components. By using optical circuit switches to rearrange star coupler connectivity, the network can be partitioned, creating independent reserves of bandwidth and resulting in increased overall network throughput. Several topologies for constructing a star from optical couplers are compared, and algorithms for optimum construction methods are presented. All of the designs target strict criteria for the flexible and dynamic creation of multicast groups, which will enable future live media production workflows in data centres. The data throughput performance of the network designs is simulated under synthetic and practical media production traffic scenarios, showing improved throughput when reconfigurable star couplers are used compared to a single large star. An energy consumption evaluation shows reduced network power consumption compared to incumbent and other proposed data centre network technologies

Network-on-Chip

Limitations of bus-based interconnections related to scalability, latency, bandwidth, and power consumption for supporting the related huge number of on-chip resources result in a communication bottleneck. These challenges can be efficiently addressed with the implementation of a network-on-chip (NoC) system. This book gives a detailed analysis of various on-chip communication architectures and covers different areas of NoCs such as potentials, architecture, technical challenges, optimization, design explorations, and research directions. In addition, it discusses current and future trends that could make an impactful and meaningful contribution to the research and design of on-chip communications and NoC systems

Doctor of Philosophy

dissertationPortable electronic devices will be limited to available energy of existing battery chemistries for the foreseeable future. However, system-on-chips (SoCs) used in these devices are under a demand to offer more functionality and increased battery life. A difficult problem in SoC design is providing energy-efficient communication between its components while maintaining the required performance. This dissertation introduces a novel energy-efficient network-on-chip (NoC) communication architecture. A NoC is used within complex SoCs due it its superior performance, energy usage, modularity, and scalability over traditional bus and point-to-point methods of connecting SoC components. This is the first academic research that combines asynchronous NoC circuits, a focus on energy-efficient design, and a software framework to customize a NoC for a particular SoC. Its key contribution is demonstrating that a simple, asynchronous NoC concept is a good match for low-power devices, and is a fruitful area for additional investigation. The proposed NoC is energy-efficient in several ways: simple switch and arbitration logic, low port radix, latch-based router buffering, a topology with the minimum number of 3-port routers, and the asynchronous advantages of zero dynamic power consumption while idle and the lack of a clock tree. The tool framework developed for this work uses novel methods to optimize the topology and router oorplan based on simulated annealing and force-directed movement. It studies link pipelining techniques that yield improved throughput in an energy-efficient manner. A simulator is automatically generated for each customized NoC, and its traffic generators use a self-similar message distribution, as opposed to Poisson, to better match application behavior. Compared to a conventional synchronous NoC, this design is superior by achieving comparable message latency with half the energy