Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

Conflict-Free Networks on Chip for Real Time Systems

[ES] La constante necesidad de un mayor rendimiento para cumplir con la gran demanda de potencia de cómputo de las nuevas aplicaciones, (ej. sistemas de conducción autónoma), obliga a la industria a apostar por la tecnología basada en Sistemas en Chip con Procesadores Multinúcleo (MPSoCs) en sus sistemas embebidos de seguridad-crítica. Los sistemas MPSoCs generalmente incluyen una red en el chip (NoC) para interconectar los núcleos de procesamiento entre ellos, con la memoria y con el resto de recursos compartidos. Desafortunadamente, el uso de las NoCs dificulta alcanzar la predecibilidad en el tiempo, ya que pueden aparecer conflictos en muchos puntos y de forma distribuida a nivel de red. Para afrontar este problema, en esta tesis se propone un nuevo paradigma de diseño para NoCs de tiempo real donde los conflictos en la red son eliminados por diseño. Este nuevo paradigma parte del Grafo de Dependencia de Canales (CDG) para evitar los conflictos de red de forma determinista. Nuestra solución es capaz de inyectar mensajes de forma natural usando un periodo TDM igual al límite teórico óptimo sin la necesidad de usar un proceso offline exigente computacionalmente. La red se ha integrado en un sistema multinúcleo basado en tiles y adaptado a su jerarquía de memoria. Como segunda contribución principal, proponemos un nuevo planificador dinámico y distribuido capaz de alcanzar un rendimiento pico muy cercanos a las NoC basadas en un diseño wormhole sin comprometer sus garantías de tiempo real. El planificador se basa en nuestro diseño de red para explotar sus propiedades clave. Los resultados de nuestra NoC muestran que nuestro diseño garantiza la predecibilidad en el tiempo evitando interferencias en la red entre múltiples aplicaciones ejecutándose concurrentemente. La red siempre garantiza el rendimiento y también mejora el rendimiento respecto al de las redes wormhole en una red 4 x 4 en un factor de 3,7x cuando se inyecta trafico para generar interferencias. En una red 8 x 8 las diferencias son incluso mayores. Además, la red obtiene un ahorro de área total del 10,79% frente a una implementación básica de una red wormhole. El planificador propuesto alcanza una mejora de rendimiento de 6,9x y 14,4x frente la versión básica de la red DCFNoC para redes en forma de malla de 16 y 64 nodos, respectivamente. Cuando lo comparamos frente a un conmutador estándar wormhole se preserva un rendimiento de red del 95% al mismo tiempo que preserva la estricta predecibilidad en el tiempo. Este logro abre la puerta a nuevos diseños de NoCs de alto rendimiento con predecibilidad en el tiempo. Como contribución final, construimos una taxonomía de NoCs basadas en TDM con propiedades de tiempo real. Con esta taxonomía realizamos un análisis exhaustivo para estudiar y comparar desde tiempos de respuesta, a implementaciones con bajo coste, pasando por soluciones de compromiso para diseños de NoCs de tiempo real. Como resultado, obtenemos nuevos diseños de NoCs basadas en TDM.[CA] La constant necessitat d'un major rendiment per a complir amb la gran demanda de potència de còmput de les noves aplicacions, (ex. sistemes de conducció autònoma), obliga la indústria a apostar per la tecnologia basada en Sistemes en Xip amb Processadors Multinucli (MPSoCs) en els seus sistemes embeguts de seguretat-crítica. Els sistemes MPSoCs generalment inclouen una xarxa en el xip (NoC) per a interconnectar els nuclis de processament entre ells, amb la memòria i amb la resta de recursos compartits. Desafortunadament, l'ús de les NoCs dificulta aconseguir la predictibilitat en el temps, ja que poden aparéixer conflictes en molts punts i de forma distribuïda a nivell de xarxa. Per a afrontar aquest problema, en aquesta tesi es proposa un nou paradigma de disseny per a NoCs de temps real on els conflictes en la xarxa són eliminats per disseny. Aquest nou paradigma parteix del Graf de Dependència de Canals (CDG) per a evitar els conflictes de xarxa de manera determinista. La nostra solució és capaç d'injectar missatges de mra natural fent ús d'un període TDM igual al límit teòric òptim sense la necessitat de fer ús d'un procés offline exigent computacionalment. La xarxa s'ha integrat en un sistema multinucli basat en tiles i adaptat a la seua jerarquia de memòria. Com a segona contribució principal, proposem un nou planificador dinàmic i distribuït capaç d'aconseguir un rendiment pic molt pròxims a les NoC basades en un disseny wormhole sense comprometre les seues garanties de temps real. El planificador es basa en el nostre disseny de xarxa per a explotar les seues propietats clau. Els resultats de la nostra NoC mostren que el nostre disseny garanteix la predictibilitat en el temps evitant interferències en la xarxa entre múltiples aplicacions executant-se concurrentment. La xarxa sempre garanteix el rendiment i també millora el rendiment respecte al de les xarxes wormhole en una xarxa 4 x 4 en un factor de 3,7x quan s'injecta trafic per a generar interferències. En una xarxa 8 x 8 les diferències són fins i tot majors. A més, la xarxa obté un estalvi d'àrea total del 10,79% front una implementació bàsica d'una xarxa wormhole. El planificador proposat aconsegueix una millora de rendiment de 6,9x i 14,4x front la versió bàsica de la xarxa DCFNoC per a xarxes en forma de malla de 16 i 64 nodes, respectivament. Quan ho comparem amb un commutador estàndard wormhole es preserva un rendiment de xarxa del 95% al mateix temps que preserva la estricta predictibilitat en el temps. Aquest assoliment obri la porta a nous dissenys de NoCs d'alt rendiment amb predictibilitat en el temps. Com a contribució final, construïm una taxonomia de NoCs basades en TDM amb propietats de temps real. Amb aquesta taxonomia realitzem una anàlisi exhaustiu per a estudiar i comparar des de temps de resposta, a implementacions amb baix cost, passant per solucions de compromís per a dissenys de NoCs de temps real. Com a resultat, obtenim nous dissenys de NoCs basades en TDM.[EN] The ever need for higher performance to cope with the high computational power demands of new applications (e.g autonomous driving systems), forces industry to support technology based on multi-processors system on chip (MPSoCs) in their safety-critical embedded systems. MPSoCs usually include a network-on-chip (NoC) to interconnect the cores between them and, with memory and the rest of shared resources. Unfortunately, the inclusion of NoCs difficults achieving time predictability as network-level conflicts may occur in many points in a distributed manner. To overcome this problem, this thesis proposes a new time-predictable NoC design paradigm where conflicts within the network are eliminated by design. This new paradigm builds on top of the Channel Dependency Graph (CDG) in order to deterministically avoid network conflicts. Our solution is able to naturally inject messages using a TDM period equal to the optimal theoretical bound without the need of using a computationally demanding offline process. The network is integrated in a tile-based manycore system and adapted to its memory hierarchy. As a second main contribution, we propose a novel distributed dynamic scheduler that is able to achieve peak performance close to a wormhole-based NoC design without compromising its real-time guarantees. The scheduler builds on top of our NoC design to exploit its key properties. The results of our NoC show that our design guarantees time predictability avoiding network interference among multiple running applications. The network always guarantees performance and also improves wormhole performance in a 4 x 4 setting by a factor of 3.7x when interference traffic is injected. For a 8 x 8 network differences are even larger. In addition, the network obtains a total area saving of 10.79% over a standard wormhole implementation. The proposed scheduler achieves an overall throughput improvement of 6.9x and 14.4x over a baseline conflict-free NoC for 16 and 64-node meshes, respectively. When compared against a standard wormhole router 95% of its network throughput is preserved while strict timing predictability is kept. This achievement opens the door to new high performance time predictable NoC designs. As a final contribution, we build a taxonomy of TDM-based NoCs with real-time properties. With this taxonomy we perform a comprehensive analysis to study and compare from response time specific, to low resource implementation cost, through trade-off solutions for real-time NoCs designs. As a result, we derive new TDM-based NoC designs.Picornell Sanjuan, T. (2021). Conflict-Free Networks on Chip for Real Time Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/177347TESI

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%

Efficient Interconnection Network Design for Heterogeneous Architectures

The onset of big data and deep learning applications, mixed with conventional general-purpose programs, have driven computer architecture to embrace heterogeneity with specialization. With the ever-increasing interconnected chip components, future architectures are required to operate under a stricter power budget and process emerging big data applications efficiently. Interconnection network as the communication backbone thus is facing the grand challenges of limited power envelope, data movement and performance scaling. This dissertation provides interconnect solutions that are specialized to application requirements towards power-/energy-efficient and high-performance computing for heterogeneous architectures. This dissertation examines the challenges of network-on-chip router power-gating techniques for general-purpose workloads to save static power. A voting approach is proposed as an adaptive power-gating policy that considers both local and global traffic status through router voting. In addition, low-latency routing algorithms are designed to guarantee performance in irregular power-gating networks. This holistic solution not only saves power but also avoids performance overhead. This research also introduces emerging computation paradigms to interconnects for big data applications to mitigate the pressure of data movement. Approximate network-on-chip is proposed to achieve high-throughput communication by means of lossy compression. Then, near-data processing is combined with in-network computing to further improve performance while reducing data movement. The two schemes are general to play as plug-ins for different network topologies and routing algorithms. To tackle the challenging computational requirements of deep learning workloads, this dissertation investigates the compelling opportunities of communication algorithm-architecture co-design to accelerate distributed deep learning. MultiTree allreduce algorithm is proposed to bond with message scheduling with network topology to achieve faster and contention-free communication. In addition, the interconnect hardware and flow control are also specialized to exploit deep learning communication characteristics and fulfill the algorithm needs, thereby effectively improving the performance and scalability. By considering application and algorithm characteristics, this research shows that interconnection network can be tailored accordingly to improve the power-/energy-efficiency and performance to satisfy heterogeneous computation and communication requirements

High performance communication on reconfigurable clusters

High Performance Computing (HPC) has matured to where it is an essential third pillar, along with theory and experiment, in most domains of science and engineering. Communication latency is a key factor that is limiting the performance of HPC, but can be addressed by integrating communication into accelerators. This integration allows accelerators to communicate with each other without CPU interactions, and even bypassing the network stack. Field Programmable Gate Arrays (FPGAs) are the accelerators that currently best integrate communication with computation. The large number of Multi-gigabit Transceivers (MGTs) on most high-end FPGAs can provide high-bandwidth and low-latency inter-FPGA connections. Additionally, the reconfigurable FPGA fabric enables tight coupling between computation kernel and network interface. Our thesis is that an application-aware communication infrastructure for a multi-FPGA system makes substantial progress in solving the HPC communication bottleneck. This dissertation aims to provide an application-aware solution for communication infrastructure for FPGA-centric clusters. Specifically, our solution demonstrates application-awareness across multiple levels in the network stack, including low-level link protocols, router microarchitectures, routing algorithms, and applications. We start by investigating the low-level link protocol and the impact of its latency variance on performance. Our results demonstrate that, although some link jitter is always present, we can still assume near-synchronous communication on an FPGA-cluster. This provides the necessary condition for statically-scheduled routing. We then propose two novel router microarchitectures for two different kinds of workloads: a wormhole Virtual Channel (VC)-based router for workloads with dynamic communication, and a statically-scheduled Virtual Output Queueing (VOQ)-based router for workloads with static communication. For the first (VC-based) router, we propose a framework that generates application-aware router configurations. Our results show that, by adding application-awareness into router configuration, the network performance of FPGA clusters can be substantially improved. For the second (VOQ-based) router, we propose a novel offline collective routing algorithm. This shows a significant advantage over a state-of-the-art collective routing algorithm. We apply our communication infrastructure to a critical strong-scaling HPC kernel, the 3D FFT. The experimental results demonstrate that the performance of our design is faster than that on CPUs and GPUs by at least one order of magnitude (achieving strong scaling for the target applications). Surprisingly, the FPGA cluster performance is similar to that of an ASIC-cluster. We also implement the 3D FFT on another multi-FPGA platform: the Microsoft Catapult II cloud. Its performance is also comparable or superior to CPU and GPU HPC clusters. The second application we investigate is Molecular Dynamics Simulation (MD). We model MD on both FPGA clouds and clusters. We find that combining processing and general communication in the same device leads to extremely promising performance and the prospect of MD simulations well into the us/day range with a commodity cloud

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.Siirretty Doriast

An Efficient NoC-based Framework To Improve Dataflow Thread Management At Runtime

This doctoral thesis focuses on how the application threads that are based on dataflow execution model can be managed at Network-on-Chip (NoC) level. The roots of the dataflow execution model date back to the early 1970’s. Applications adhering to such program execution model follow a simple producer-consumer communication scheme for synchronising parallel thread related activities. In dataflow execution environment, a thread can run if and only if all its required inputs are available. Applications running on a large and complex computing environment can significantly benefit from the adoption of dataflow model. In the first part of the thesis, the work is focused on the thread distribution mechanism. It has been shown that how a scalable hash-based thread distribution mechanism can be implemented at the router level with low overheads. To enhance the support further, a tool to monitor the dataflow threads’ status and a simple, functional model is also incorporated into the design. Next, a software defined NoC has been proposed to manage the distribution of dataflow threads by exploiting its reconfigurability. The second part of this work is focused more on NoC microarchitecture level. Traditional 2D-mesh topology is combined with a standard ring, to understand how such hybrid network topology can outperform the traditional topology (such as 2D-mesh). Finally, a mixed-integer linear programming based analytical model has been proposed to verify if the application threads mapped on to the free cores is optimal or not. The proposed mathematical model can be used as a yardstick to verify the solution quality of the newly developed mapping policy. It is not trivial to provide a complete low-level framework for dataflow thread execution for better resource and power management. However, this work could be considered as a primary framework to which improvements could be carried out

Efficient Intra-Rack Resource Disaggregation for HPC Using Co-Packaged DWDM Photonics

The diversity of workload requirements and increasing hardware heterogeneity in emerging high performance computing (HPC) systems motivate resource disaggregation. Resource disaggregation allows compute and memory resources to be allocated individually as required to each workload. However, it is unclear how to efficiently realize this capability and cost-effectively meet the stringent bandwidth and latency requirements of HPC applications. To that end, we describe how modern photonics can be co-designed with modern HPC racks to implement flexible intra-rack resource disaggregation and fully meet the bit error rate (BER) and high escape bandwidth of all chip types in modern HPC racks. Our photonic-based disaggregated rack provides an average application speedup of 11% (46% maximum) for 25 CPU and 61% for 24 GPU benchmarks compared to a similar system that instead uses modern electronic switches for disaggregation. Using observed resource usage from a production system, we estimate that an iso-performance intra-rack disaggregated HPC system using photonics would require 4x fewer memory modules and 2x fewer NICs than a non-disaggregated baseline.Comment: 15 pages, 12 figures, 4 tables. Published in IEEE Cluster 202