A High Speed Hardware Scheduler for 1000-port Optical Packet Switches to Enable Scalable Data Centers

Meeting the exponential increase in the global demand for bandwidth has become a major concern for today's data centers. The scalability of any data center is defined by the maximum capacity and port count of the switching devices it employs, limited by total pin bandwidth on current electronic switch ASICs. Optical switches can provide higher capacity and port counts, and hence, can be used to transform data center scalability. We have recently demonstrated a 1000-port star-coupler based wavelength division multiplexed (WDM) and time division multiplexed (TDM) optical switch architecture offering a bandwidth of 32 Tbit/s with the use of fast wavelength-tunable transmitters and high-sensitivity coherent receivers. However, the major challenge in deploying such an optical switch to replace current electronic switches lies in designing and implementing a scalable scheduler capable of operating on packet timescales. In this paper, we present a pipelined and highly parallel electronic scheduler that configures the high-radix (1000-port) optical packet switch. The scheduler can process requests from 1000 nodes and allocate timeslots across 320 wavelength channels and 4000 wavelength-tunable transceivers within a time constraint of 1μs. Using the Opencell NanGate 45nm standard cell library, we show that the complete 1000-port parallel scheduler algorithm occupies a circuit area of 52.7mm2, 4-8x smaller than that of a high-performance switch ASIC, with a clock period of less than 8ns, enabling 138 scheduling iterations to be performed in 1μs. The performance of the scheduling algorithm is evaluated in comparison to maximal matching from graph theory and conventional software-based wavelength allocation heuristics. The parallel hardware scheduler is shown to achieve similar matching performance and network throughput while being orders of magnitude faster

Parallel Modular Scheduler Design for Clos Switches in Optical Data Center Networks

As data centers enter the exascale computing era, the traffic exchanged between internal network nodes, increases exponentially. Optical networking is an attractive solution to deliver the high capacity, low latency, and scalable interconnection needed. Among other switching methods, packet switching is particularly interesting as it can be widely deployed in the network to handle rapidly-changing traffic of arbitrary size. Nanosecond-reconfigurable photonic integrated switch fabrics, built as multi-stage architectures such as the Clos network, are key enablers to scalable packet switching. However, the accompanying control plane needs to also operate on packet timescales. Designing a central scheduler, to control an optical packet switch in nanoseconds, presents a challenge especially as the switch size increases. To this end, we present a highly-parallel, modular scheduler design for Clos switches along with a proposed routing scheme to enable nanosecond scalable scheduling. We synthesize our scheduler as an application-specific integrated circuit (ASIC) and demonstrate scaling to a 256 × 256 size with an ultra-low scheduling delay of only 6.0 ns. In a cycle-accurate rack-scale network emulation, for this switch size, we show a minimum end-to-end latency of 30.8 ns and maintain nanosecond average latency up to 80% of input traffic load. We achieve zero packet loss and short-tailed packet latency distributions for all traffic loads and switch sizes. Our work is compared to state-of-the-art optical switches, in terms of scheduling delay, packet latency, and switch throughput

Control Plane Hardware Design for Optical Packet Switched Data Centre Networks

Optical packet switching for intra-data centre networks is key to addressing traffic requirements. Photonic integration and wavelength division multiplexing (WDM) can overcome bandwidth limits in switching systems. A promising technology to build a nanosecond-reconfigurable photonic-integrated switch, compatible with WDM, is the semiconductor optical amplifier (SOA). SOAs are typically used as gating elements in a broadcast-and-select (B\&S) configuration, to build an optical crossbar switch. For larger-size switching, a three-stage Clos network, based on crossbar nodes, is a viable architecture. However, the design of the switch control plane, is one of the barriers to packet switching; it should run on packet timescales, which becomes increasingly challenging as line rates get higher. The scheduler, used for the allocation of switch paths, limits control clock speed. To this end, the research contribution was the design of highly parallel hardware schedulers for crossbar and Clos network switches. On a field-programmable gate array (FPGA), the minimum scheduler clock period achieved was 5.0~ns and 5.4~ns, for a 32-port crossbar and Clos switch, respectively. By using parallel path allocation modules, one per Clos node, a minimum clock period of 7.0~ns was achieved, for a 256-port switch. For scheduler application-specific integrated circuit (ASIC) synthesis, this reduces to 2.0~ns; a record result enabling scalable packet switching. Furthermore, the control plane was demonstrated experimentally. Moreover, a cycle-accurate network emulator was developed to evaluate switch performance. Results showed a switch saturation throughput at a traffic load 60\% of capacity, with sub-microsecond packet latency, for a 256-port Clos switch, outperforming state-of-the-art optical packet switches

Parallel Star-coupler OCS Architectures using Distributed Hardware Schedulers

WDM/TDM star-coupler architectures have been proposed for building high-radix optical switches to enhance data centre network scalability. Here we propose a 1000-server star coupler network, which uses parallel OCS sub-stars to scale the network capacity to 256 Tbps. The harmony of distributed ns-timescale hardware schedulers and parallel OCS resource management achieves a throughput of 82.5% (200 Tbps) while incurring an average latency of 9.6 µs at 100% network load

dReDBox: A Disaggregated Architectural Perspective for Data Centers

Data centers are currently constructed with fixed blocks (blades); the hard boundaries of this approach lead to suboptimal utilization of resources and increased energy requirements. The dReDBox (disaggregated Recursive Datacenter in a Box) project addresses the problem of fixed resource proportionality in next-generation, low-power data centers by proposing a paradigm shift toward finer resource allocation granularity, where the unit is the function block rather than the mainboard tray. This introduces various challenges at the system design level, requiring elastic hardware architectures, efficient software support and management, and programmable interconnect. Memory and hardware accelerators can be dynamically assigned to processing units to boost application performance, while high-speed, low-latency electrical and optical interconnect is a prerequisite for realizing the concept of data center disaggregation. This chapter presents the dReDBox hardware architecture and discusses design aspects of the software infrastructure for resource allocation and management. Furthermore, initial simulation and evaluation results for accessing remote, disaggregated memory are presented, employing benchmarks from the Splash-3 and the CloudSuite benchmark suites.This work was supported in part by EU H2020 ICT project dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Reconfigurable network systems and software-defined networking

Modern high-speed networks have evolved from relatively static networks to highly adaptive networks facilitating dynamic reconfiguration. This evolution has influenced all levels of network design and management, introducing increased programmability and configuration flexibility. This influence has extended from the lowest level of physical hardware interfaces to the highest level of network management by software. A key representative of this evolution is the emergence of softwaredefined networking (SDN). In this paper, we review the current state of the art in reconfigurable network systems, covering hardware reconfiguration, SDN, and the interplay between them. We take a top-down approach, starting with a tutorial on software-defined networks. We then continue to discuss programming languages as the linking element between different levels of software and hardware in the network. We review electronic switching systems, highlighting programmability and reconfiguration aspects, and describe the trends in reconfigurable network elements. Finally, we describe the state of the art in the integration of photonic transceiver and switching elements with electronic technologies, and consider the implications for SDN and reconfigurable network systems.This work was jointly supported by the UKs Engineering and Physical Sciences Research Council (EPSRC) Internet Project EP/H040536/1, an EPSRC Research Fellowship grant to Philip Watts (EP/I004157/2), and DARPA and AFRL under contract FA8750-11-C-0249.This is the final version of the article. It first appeared from IEEE via http://dx.doi.org/10.1109/JPROC.2015.243573

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

Reconfigurable optical star network architecture for multicast media production data centres

Passive optical star networks have attractive properties for multicast traffic in data centres, but are limited in transmission bandwidth per node due to sharing a finite total throughput capacity. By adding reconfigurable switching elements to the core of an optical star topology, simulations show that the expected transmission rate per node can be increased by 26–40% (at 90% and 70% network load respectively). The proposed architecture shows no loss of multicast functionality compared to a single passive optical star, and only 7.1% increase in power consumption. Network throughput is shown to be highly dependent on the network traffic pattern, with simulations of multicast zonal media production traffic showing 6 times greater throughput than random or hotspot traffic models

Energy Demand Response for High-Performance Computing Systems

The growing computational demand of scientific applications has greatly motivated the development of large-scale high-performance computing (HPC) systems in the past decade. To accommodate the increasing demand of applications, HPC systems have been going through dramatic architectural changes (e.g., introduction of many-core and multi-core systems, rapid growth of complex interconnection network for efficient communication between thousands of nodes), as well as significant increase in size (e.g., modern supercomputers consist of hundreds of thousands of nodes). With such changes in architecture and size, the energy consumption by these systems has increased significantly. With the advent of exascale supercomputers in the next few years, power consumption of the HPC systems will surely increase; some systems may even consume hundreds of megawatts of electricity. Demand response programs are designed to help the energy service providers to stabilize the power system by reducing the energy consumption of participating systems during the time periods of high demand power usage or temporary shortage in power supply. This dissertation focuses on developing energy-efficient demand-response models and algorithms to enable HPC system\u27s demand response participation. In the first part, we present interconnection network models for performance prediction of large-scale HPC applications. They are based on interconnected topologies widely used in HPC systems: dragonfly, torus, and fat-tree. Our interconnect models are fully integrated with an implementation of message-passing interface (MPI) that can mimic most of its functions with packet-level accuracy. Extensive experiments show that our integrated models provide good accuracy for predicting the network behavior, while at the same time allowing for good parallel scaling performance. In the second part, we present an energy-efficient demand-response model to reduce HPC systems\u27 energy consumption during demand response periods. We propose HPC job scheduling and resource provisioning schemes to enable HPC system\u27s emergency demand response participation. In the final part, we propose an economic demand-response model to allow both HPC operator and HPC users to jointly reduce HPC system\u27s energy cost. Our proposed model allows the participation of HPC systems in economic demand-response programs through a contract-based rewarding scheme that can incentivize HPC users to participate in demand response