Measuring and Understanding Throughput of Network Topologies

High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available

FatPaths: Routing in Supercomputers and Data Centers when Shortest Paths Fall Short

We introduce FatPaths: a simple, generic, and robust routing architecture that enables state-of-the-art low-diameter topologies such as Slim Fly to achieve unprecedented performance. FatPaths targets Ethernet stacks in both HPC supercomputers as well as cloud data centers and clusters. FatPaths exposes and exploits the rich ("fat") diversity of both minimal and non-minimal paths for high-performance multi-pathing. Moreover, FatPaths uses a redesigned "purified" transport layer that removes virtually all TCP performance issues (e.g., the slow start), and incorporates flowlet switching, a technique used to prevent packet reordering in TCP networks, to enable very simple and effective load balancing. Our design enables recent low-diameter topologies to outperform powerful Clos designs, achieving 15% higher net throughput at 2x lower latency for comparable cost. FatPaths will significantly accelerate Ethernet clusters that form more than 50% of the Top500 list and it may become a standard routing scheme for modern topologies

Photonic Interconnection Networks for Exascale Computers

[ES] En los últimos años, distintos proyectos alrededor del mundo se han centrado en el diseño de supercomputadores capaces de alcanzar la meta de la computación a exascala, con el objetivo de soportar la ejecución de aplicaciones de gran importancia para la sociedad en diversos campos como el de la salud, la inteligencia artificial, etc. Teniendo en cuenta la creciente tendencia de la potencia computacional en cada generación de supercomputadores, este objetivo se prevee accesible en los próximos años. Alcanzar esta meta requiere abordar diversos retos en el diseño y desarrollo del sistema. Uno de los principales es conseguir unas comunicaciones rápidas y eficientes entre el inmenso número de nodos de computo y los sitemas de memoria. La tecnología fotónica proporciona ciertas ventajas frente a las redes eléctricas, como un mayor ancho de banda en los enlaces, un mayor paralelismo a nivel de comunicaciones gracias al DWDM o una mejor gestión del cableado gracias a su reducido tamaño. En la tesis se ha desarrollado un estudio de viabilidad y desarrollo de redes de interconexión haciendo uso de la tecnología fotónica para los futuros sistemas a exaescala dentro del proyecto europeo ExaNeSt. En primer lugar, se ha realizado un análisis y caracterización de aplicaciones exaescala. Este análisis se ha utilizado para conocer el comportamiento y requisitos de red que presentan las aplicaciones, y con ello guiarnos en el diseño de la red del sistema. El análisis considera tres parámetros: la distribución de mensajes en base a su tamaño y su tipo, el consumo de ancho de banda requerido a lo largo de la ejecución y la matriz de comunicación espacial entre los nodos. El estudio revela la necesidad de una red eficiente y rápida, debido a que la mayoría de las comunaciones se realizan en burst y con mensajes de un tamaño medio inferior a 50KB. A continuación, la tesis se centra en identificar los principales elementos que diferencian las redes fotónicas de las eléctricas. Identificamos una secuencia de pasos en el diseño de un simulador, ya sea haciéndolo desde cero con tecnología fotónica o adaptando un simulador de redes eléctricas existente para modelar la fotónica. Después se han realizado dos estudios de rendimiento y comparativas entre las actuales redes eléctricas y distintas configuraciones de redes fotónicas utilizando topologías clásicas. En el primer estudio, realizado tanto con tráfico sintético como con trazas de ExaNeSt en un toro, fat tree y dragonfly, se observa como la tecnología fotónica supone una clara mejora respecto a la eléctrica. Además, el estudio muestra que el parámetro que más afecta al rendimiento es el ancho de banda del canal fotónico. El segundo estudio muestra el comportamiento y rendimiento de aplicaciones reales en simulaciones a gran escala en una topología jellyfish. En este estudio se confirman las conclusiones obtenidas en el anterior, revelando además que la tecnología fotónica permite reducir la complejidad de algunas topologías, y por ende, el coste de la red. En los estudios realizados se ha observado una baja utilización de la red debido a que las topologías utilizadas para redes eléctricas no aprovechan las características que proporciona la tecnología fotónica. Por ello, se ha propuesto Segment Switching, una estrategia de conmutación orientada a reducir la longitud de las rutas mediante el uso de buffers intermedios. Los resultados experimentales muestran que cada topología tiene sus propios requerimientos. En el caso del toro, el mayor rendimiento se obtiene con un mayor número de buffers en la red. En el fat tree el parámetro más importante es el tamaño del buffer, obteniendo unas prestaciones similares una configuración con buffers en todos los switches que la que los ubica solo en el nivel superior. En resumen, esta tesis estudia el uso de la tecnología fotónica para las redes de sistemas a exascala y propone aprovechar[CA] Els darrers anys, múltiples projectes de recerca a tot el món s'han centrat en el disseny de superordinadors capaços d'assolir la barrera de computació exascala, amb l'objectiu de donar suport a l'execució d'aplicacions importants per a la nostra societat, com ara salut, intel·ligència artificial, meteorologia, etc. Segons la tendència creixent en la potència de càlcul en cada generació de superordinadors, es preveu assolir aquest objectiu en els propers anys. No obstant això, assolir aquest objectiu requereix abordar diferents reptes importants en el disseny i desenvolupament del sistema. Un dels principals és aconseguir comunicacions ràpides i eficients entre l'enorme nombre de nodes computacionals i els sistemes de memòria. La tecnologia fotònica proporciona diversos avantatges respecte a les xarxes elèctriques actuals, com ara un major ample de banda als enllaços, un major paral·lelisme de la xarxa gràcies a DWDM o una millor gestió del cable a causa de la seva mida molt més xicoteta. En la tesi, s'ha desenvolupat un estudi de viabilitat i desenvolupament de xarxes d'interconnexió mitjançant tecnologia fotònica per a futurs sistemes exascala dins del projecte europeu ExaNeSt. En primer lloc, s'ha dut a terme un estudi de caracterització d'aplicacions exascala dels requisits de xarxa. Els resultats de l'anàlisi ajuden a entendre els requisits de xarxa de les aplicacions exascale i, per tant, ens guien en el disseny de la xarxa del sistema. Aquesta anàlisi considera tres paràmetres principals: la distribució dels missatges en funció de la seva mida i tipus, el consum d'ample de banda requerit durant tota l'execució i els patrons de comunicació espacial entre els nodes. L'estudi revela la necessitat d'una xarxa d'interconnexió ràpida i eficient, ja que la majoria de comunicacions consisteixen en ràfegues de transmissions, cadascuna amb una mida mitjana de missatge de 50 KB. A continuació, la tesi se centra a identificar els principals elements que diferencien les xarxes fotòniques de les elèctriques. Identifiquem una seqüència de passos en el disseny i implementació d'un simulador: tractar la tecnologia fotònica des de zero o per ampliar un simulador de xarxa elèctrica existent per modelar la fotònica. Després, es presenten dos estudis principals de comparació de rendiment entre xarxes elèctriques i diferents configuracions de xarxes fotòniques mitjançant topologies clàssiques. En el primer estudi, realitzat tant amb trànsit sintètic com amb traces d'ExaNeSt en un toro, fat tree i dragonfly, vam trobar que la tecnologia fotònica representa una millora notable respecte a la tecnologia elèctrica. A més, l'estudi mostra que el paràmetre que més afecta el rendiment és l'amplada de banda del canal fotònic. Aquest darrer estudi analitza el rendiment d'aplicacions reals en simulacions a gran escala en una topologia jellyfish. Els resultats d'aquest estudi corroboren les conclusions obtingudes en l'anterior, revelant també que la tecnologia fotònica permet reduir la complexitat d'algunes topologies i, per tant, el cost de la xarxa. En els estudis anteriors ens adonem que la xarxa estava infrautilitzada principalment perquè les topologies estudiades per a xarxes elèctriques no aprofiten les característiques proporcionades per la tecnologia fotònica. Per aquest motiu, proposem Segment Switching, una estratègia de commutació destinada a reduir la longitud de les rutes mitjançant la implementació de memòries intermèdies en nodes intermedis al llarg de la ruta. Els resultats experimentals mostren que cadascuna de les topologies estudiades presenta diferents requisits de memòria intermèdia. Per al toro, com més gran siga el nombre de memòries intermèdies a la xarxa, major serà el rendiment. Per al fat tree, el paràmetre clau és la mida de la memòria intermèdia, aconseguint un rendiment similar tant amb una configuració amb memòria intermèdia en tots els co[EN] In the last recent years, multiple research projects around the world have focused on the design of supercomputers able to reach the exascale computing barrier, with the aim of supporting the execution of important applications for our society, such as health, artificial intelligence, meteorology, etc. According to the growing trend in the computational power in each supercomputer generation, this objective is expected to be reached in the coming years. However, achieving this goal requires addressing distinct major challenges in the design and development of the system. One of the main ones is to achieve fast and efficient communications between the huge number of computational nodes and the memory systems. Photonics technology provides several advantages over current electrical networks, such as higher bandwidth in the links, greater network parallelism thanks to DWDM, or better cable management due to its much smaller size. In this thesis, a feasibility study and development of interconnection networks have been developed using photonics technology for future exascale systems within the European project ExaNeSt. First, a characterization study of exascale applications from the network requirements has been carried out. The results of the analysis help understand the network requirements of exascale applications, and thereby guide us in the design of the system network. This analysis considers three main parameters: the distribution of the messages based on their size and type, the required bandwidth consumption throughout the execution, and the spatial communication patterns between the nodes. The study reveals the need for a fast and efficient interconnection network, since most communications consist of bursts of transmissions, each with an average message size of 50 KB. Next, this dissertation concentrates on identifying the main elements that differentiate photonic networks from electrical ones. We identify a sequence of steps in the design and implementation of a simulator either i) dealing with photonic technology from scratch or ii) to extend an existing electrical network simulator in order to model photonics. After that, two main performance comparison studies between electrical networks and different configurations of photonic networks are presented using classical topologies. In the former study, carried out with both synthetic traffic and traces of ExaNeSt in a torus, fat tree and dragonfly, we found that photonic technology represents a noticeable improvement over electrical technology. Furthermore, the study shows that the parameter that most affects the performance is the bandwidth of the photonic channel. The latter study analyzes performance of real applications in large-scale simulations in a jellyfish topology. The results of this study corroborates the conclusions obtained in the previous, also revealing that photonic technology allows reducing the complexity of some topologies, and therefore, the cost of the network. In the previous studies we realize that the network was underutilized mainly because the studied topologies for electrical networks do not take advantage of the features provided by photonic technology. For this reason, we propose Segment Switching, a switching strategy aimed at reducing the length of the routes by implementing buffers at intermediate nodes along the path. Experimental results show that each of the studied topologies presents different buffering requirements. For the torus, the higher the number of buffers in the network, the higher the performance. For the fat tree, the key parameter is the buffer size, achieving similar performance a configuration with buffers on all switches that locating buffers only at the top level. In summary, this thesis studies the use of photonic technology for networks of exascale systems, and proposes to take advantage of the characteristics of this technology in current electrical network topologies.This thesis has been conceived from the work carried out by Polytechnic University of Valencia in the ExaNeSt European projectDuro Gómez, J. (2021). Photonic Interconnection Networks for Exascale Computers [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/166796TESI

Efficient All-to-All Collective Communication Schedules for Direct-Connect Topologies

The all-to-all collective communications primitive is widely used in machine learning (ML) and high performance computing (HPC) workloads, and optimizing its performance is of interest to both ML and HPC communities. All-to-all is a particularly challenging workload that can severely strain the underlying interconnect bandwidth at scale. This is mainly because of the quadratic scaling in the number of messages that must be simultaneously serviced combined with large message sizes. This paper takes a holistic approach to optimize the performance of all-to-all collective communications on supercomputer-scale direct-connect interconnects. We address several algorithmic and practical challenges in developing efficient and bandwidth-optimal all-to-all schedules for any topology, lowering the schedules to various backends and fabrics that may or may not expose additional forwarding bandwidth, establishing an upper bound on all-to-all throughput, and exploring novel topologies that deliver near-optimal all-to-all performance

A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network

Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption of low-diameter networks, we design, implement, deploy, and evaluate the first real-world SF installation. We focus on deployment, management, and operational aspects of our test cluster with 200 servers and carefully analyze performance. We demonstrate techniques for simple cabling and cabling validation as well as a novel high-performance routing architecture for InfiniBand-based low-diameter topologies. Our real-world benchmarks show SF's strong performance for many modern workloads such as deep neural network training, graph analytics, or linear algebra kernels. SF outperforms non-blocking Fat Trees in scalability while offering comparable or better performance and lower cost for large network sizes. Our work can facilitate deploying SF while the associated (open-source) routing architecture is fully portable and applicable to accelerate any low-diameter interconnect

Designing data center networks for high throughput

Data centers with tens of thousands of servers now support popular Internet services, scientific research, as well as industrial applications. The network is the foundation of such facilities, giving the large server pool the ability to work together on these applications. The network needs to provide high throughput between servers to ensure that computations are not slowed down by network bottlenecks, with servers waiting on data from other servers. This work address two broad, related questions about high-throughput data center network design: (a) how do we measure and benchmark various network designs for throughput? and (b) how do we design such networks for near-optimal throughput? The problem of designing high-throughput networks has received a lot of attention, with multiple interesting architectures being proposed every year. However, there is no clarity on how one should benchmark these networks and how they compare to each other. In fact, this work shows that commonly used measurement approaches, in particular, cut-metrics like bisection bandwidth, do not predict throughput accurately. In contrast, we directly evaluate the throughput of networks on both uniform and (heretofore unknown) nearly-worst-case traffic matrices, and include here a comparison of 10 networks using this approach. Further, prior work has not addressed a fundamental question: how far are we from throughput-optimal design? In this work, we propose the first upper bound on network throughput for any topology with identical switches. Although designing optimal topologies is infeasible, we demonstrate that random graphs achieve throughput surprisingly close to this bound -- within a few percent at the scale of a few thousand servers for uniform traffic. Our approach also addresses important practical concerns in the design of data center networks, such as incremental expansion and heterogeneous design – as more and varied equipment is added to a data center over the years in response to evolving needs, how do we best accommodate such equipment? Our networks can achieve the same incremental growth at 40% of the expense such growth would incur with past techniques for Clos networks. Further, our approach to designing heterogeneous topologies (i.e., where all the network switches are not identical) achieves 43% higher throughput than a comparable VL2 topology, a heterogeneous network already deployed in Microsoft’s data centers. We acknowledge that the use of random graphs also poses challenges, particularly with regards to efficient routing and physical cabling. We thus present here high-efficiency routing and cabling schemes for such networks as well