Power-performance assessment of different DVFS control policies in NoCs

We analyze the power-delay trade-off in a Network-on-Chip (NoC) under three Dynamic Voltage and Frequency Scaling (DVFS) policies. The first rate-based policy sets frequency and voltage of the NoC to the minimum value that allows to sustain the injection rate without reaching saturation. The second queue-based policy uses a feedback-loop approach to throttle the NoC frequency and voltage such that the average backlog of the injection queues tracks a target value. The third delay-based policy uses a closed- loop strategy that targets a given NoC end-to-end average delay. We first show that, despite the different mechanism and implementation, both rate-based and queue-based policies obtain very similar results in terms of power and delay, and we propose a theoretical interpretation of this similarity. Then, we show that delay-based policy generally offers a better power-delay trade-off. We obtained our results with an extensive set of experiments on synthetic traffic, as well as multimedia, communications and PARSEC benchmarks. For all the experiments, we report both cycle-accurate simulation results for the analysis of NoC delay and accurate power results obtained targeting a standard-cell library in an advanced 28-nm FDSOI CMOS technology

A Control-based Methodology for Power-performance Optimization in NoCs Exploiting DVFS

Networks-on-Chip (NoCs) are considered a viable solution to fully exploit the computational power of multi- and many-cores, but their non negligible power consumption requires ad hoc power-performance design methodologies. In this perspective, several proposals exploited the possibility to dynamically tune voltage and frequency for the interconnect, taking steps from traditional CPU-based power management solutions. However, the impact of the actuators, i.e. the limited range of frequencies for a PLL (Phase Locked Loop) or the time to increase voltage and frequency for a Dynamic Voltage and Frequency Scaling (DVFS) modules, are often not carefully accounted for, thus overestimating the benefits. This paper presents a control-based methodology for the NoC power-performance optimization exploiting the Dynamic Frequency Scaling (DFS). Both timing and power overheads of the actuators are considered, thanks to an ad hoc simulation framework. Moreover the proposed methodology eventually allows for user and/or OS interactions to change between different high level power-performance modes, i.e. to trigger performance oriented or power saving system behaviors. Experimental validation considered a 16-core architecture comparing our proposal with different settings of threshold-based policies. We achieved a speedup up to 3 for the timing and a reduction up to 33.17% of the power ∗ time product against the best threshold-based policy. Moreover, our best control-based scheme provides an averaged power-performance product improvement of 16.50% and 34.79% against the best and the second considered threshold-based policy setting

Modeling DVFS and Power-Gating Actuators for Cycle-Accurate NoC-Based Simulators

Networks-on-chip (NoCs) are a widely recognized viable interconnection paradigm to support the multi-core revolution. One of the major design issues of multicore architectures is still the power, which can no longer be considered mainly due to the cores, since the NoC contribution to the overall energy budget is relevant. To face both static and dynamic power while balancing NoC performance, different actuators have been exploited in literature, mainly dynamic voltage frequency scaling (DVFS) and power gating. Typically, simulation-based tools are employed to explore the huge design space by adopting simplified models of the components. As a consequence, the majority of state-of-the-art on NoC power-performance optimization do not accurately consider timing and power overheads of actuators, or (even worse) do not consider them at all, with the risk of overestimating the benefits of the proposed methodologies. This article presents a simulation framework for power-performance analysis of multicore architectures with specific focus on the NoC. It integrates accurate power gating and DVFS models encompassing also their timing and power overheads. The value added of our proposal is manyfold: (i) DVFS and power gating actuators are modeled starting from SPICE-level simulations; (ii) such models have been integrated in the simulation environment; (iii) policy analysis support is plugged into the framework to enable assessment of different policies; (iv) a flexible GALS (globally asynchronous locally synchronous) support is provided, covering both handshake and FIFO re-synchronization schemas. To demonstrate both the flexibility and extensibility of our proposal, two simple policies exploiting the modeled actuators are discussed in the article

A DVFS Cycle Accurate Simulation Framework with Asynchronous NoC Design for Power-Performance Optimizations

Network-on-Chip (NoC) is a flexible and scalable solution to interconnect multi-cores, with a strong influence on the performance of the whole chip. On-chip network affects also the overall power consumption, thus requiring accurate early-stage estimation and optimization methodologies. In this scenario, the Dynamic Voltage Frequency Scaling (DVFS) technique have been proposed both for CPUs and NoCs. The promise is to be a flexible and scalable way to jointly optimize power-performance, addressing both static and dynamic power sources. Being simulation a de-facto prime solution to explore novel multi-core architectures, a reliable full system analysis requires to integrate in the toolchain accurate timing and power models for the DVFS block and for the resynchronization logic between different Voltage and Frequency Islands (VFIs). In such a way, a more accurate validation of novel optimization methodologies which exploit such actuator is possible, since both architectural and actuator overheads are considered at the same time. This work proposes a complete cycle accurate framework for multi-core design supporting Global Asynchronous Local Synchronous (GALS) NoC design and DVFS actuators for the NoC. Furthermore, static and dynamic frequency assignment is possible with or without the use of the voltage regulator. The proposed framework sits on accurate analytical timing model and SPICE-based power measures, providing accurate estimates of both timing and power overheads of the power control mechanisms

Head-of-Line Blocking Reduction in Power-Efficient Networks-on-Chip

Tesis por compendioNowadays, thanks to the continuous improvements in the integration scale, more and more cores are added on the same chip, leading to higher system performance. In order to interconnect all nodes, a network-on-chip (NoC) is used, which is in charge of delivering data between cores. However, increasing the number of cores leads to a significant power consumption increase, leading the NoC to be one of the most expensive components in terms of power. Because of this, during the last years, several mechanisms have been proposed to address the NoC power consumption by means of DVFS (Dynamic Voltage and Frequency Scaling) and power-gating strategies. Nevertheless, improvements achieved by these mechanisms are achieved, to a greater or lesser extent, at the cost of system performance, potentially increasing the risk of saturating the network by forming congested points which, in turn, compromise the rest of the system functionality. One side effect is the creation of the "Head-of-Line blocking" effect where congested packets at the head of queues prevent other non-blocked packets from advancing. To address this issue, in this thesis, on one hand, we propose novel congestion control techniques in order to improve system performance by removing the "Head-of-Line" blocking effect. On the other hand, we propose combined solutions adapted to DVFS in order to achieve improvements in terms of performance and power. In addition to this, we propose a path-aware power-gating-based mechanism, which is capable of detecting the flows sharing buffer resources along data paths and perform to switch them off when not needed. With all these combined solutions we can significantly reduce the power consumption of the NoC when compared with state-of-the-art proposals.Hoy en día, gracias a las mejoras en la escala de integración cada vez se integran más y más núcleos en un mismo chip, mejorando así sus prestaciones. Para interconectar todos los nodos dentro del chip se emplea una red en chip (NoC, Network-on-Chip), la cual es la encargada de intercambiar información entre núcleos. No obstante, aumentar el número de núcleos en el chip también conlleva a su vez un importante incremento en el consumo de la NoC, haciendo que ésta se convierta en una de las partes más caras del chip en términos de consumo. Por ello, en los últimos años se han propuesto diversas técnicas de ahorro de energía orientadas a reducir el consumo de la NoC mediante el uso de DVFS (Dynamic Voltage and Frequency Scaling) o estrategias basadas en "power-gating". Sin embargo, éstas mejoras de consumo normalmente se obtienen a costa de sacrificar, en mayor o menor medida, las prestaciones del sistema, aumentado potencialmente así el riesgo de saturar la red, generando puntos de congestión que, a su vez, comprometen el rendimiento del resto del sistema. Un efecto colateral es el "Head-of-Line blocking", mediante el que paquetes congestionados en la cabeza de la cola impiden que otros paquetes no congestionados avancen. Con el fin de solucionar este problema, en ésta tesis, en primer lugar, proponemos técnicas novedosas de control de congestión para incrementar el rendimiento del sistema mediante la eliminación del "Head-of-Line blocking", mientras que, por otra parte, proponemos soluciones combinadas adaptadas a DVFS con el fin de conseguir mejoras en términos de rendimiento y energía. Además, proponemos una técnica de "power-gating" orientada a rutas de datos, la cual es capaz de detectar flujos de datos compartiendo recursos a lo largo de rutas y apagar dichos recursos de forma dinámica cuando no son necesarios. Con todas éstas soluciones combinadas podemos reducir el consumo de energía de la NoC en comparación con otras técnicas presentes en el estado del arte.Hui en dia, gr\`acies a les millores en l'escala d'integraci\'o, cada vegada s'integren m\'es i m\'es nuclis en un mateix xip, la qual cosa millora les seues prestacions. Per tal d'interconectar tots els nodes dins el xip es fa \'us d'una Xarxa en Xip (NoC; Network-on-Chip), la qual \'es l'encarregada d'intercanviar informaci\'o entre els nuclis. No obstant aix\`o, incrementar el nombre de nuclis en el xip tamb\'e comporta un important augment en el consum de la NoC, la qual cosa fa que aquesta es convertisca en una de les parts m\'es costoses del xip en termes de consum. Per aix\`o, en els \'ultims anys s'han proposat diverses t\`ecniques d'estalvi d'energia orientades a reduir el consum de la NoC mitjançant l'\'us de DVFS (Dynamic Voltage and Frequency Scaling) o estrat\`egies basades en ``power-gating''. Malgrat aix\`o, aquestes millores en les prestacions normalment s'obtenen a costa de sacrificar, en major o menor mesura, les prestacions del sistema i augmenta aix\'i el risc de saturar la xarxa al generar-se punts de congesti\'o, que al mateix temps, comprometen el rendiment de la resta del sistema. Un efecte col-lateral \'es el ``Head-of- Line blocking'', mitjançant el qual, els paquets congestionats al cap de la cua, impedixen que altres paquets no congestionats avancen. A fi de solucionar eixe problema, en aquesta tesi, en primer lloc, proposem noves t\`ecniques de control de congesti\'o amb l'objectiu d'incrementar el rendiment del sistema per mitj\`a de l'eliminaci\'o del ``Head-of- Line blocking'', i d'altra banda, proposem solucions combinades adaptades a DVFS amb la finalitat d'aconseguir millores en termes de rendiment i energia. A m\'es, proposem una t\`ecnica de ``power-gating'' orientada a rutes de dades, la qual \'es capa\c c de detectar fluxos de dades al compartir recursos al llarg de les rutes i apagar eixos recursos de forma din\`amica quan no s\'on necessaris. Amb totes aquestes solucions combinades podem reduir el consum d'energia de la NoC en comparaci\'o amb altres t\`ecniques presents en l'estat de l'art.Escamilla López, JV. (2017). Head-of-Line Blocking Reduction in Power-Efficient Networks-on-Chip [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90419TESISCompendi

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.Siirretty Doriast

Energy-Efficient and Reliable Computing in Dark Silicon Era

Dark silicon denotes the phenomenon that, due to thermal and power constraints, the fraction of transistors that can operate at full frequency is decreasing in each technology generation. Moore’s law and Dennard scaling had been backed and coupled appropriately for five decades to bring commensurate exponential performance via single core and later muti-core design. However, recalculating Dennard scaling for recent small technology sizes shows that current ongoing multi-core growth is demanding exponential thermal design power to achieve linear performance increase. This process hits a power wall where raises the amount of dark or dim silicon on future multi/many-core chips more and more. Furthermore, from another perspective, by increasing the number of transistors on the area of a single chip and susceptibility to internal defects alongside aging phenomena, which also is exacerbated by high chip thermal density, monitoring and managing the chip reliability before and after its activation is becoming a necessity. The proposed approaches and experimental investigations in this thesis focus on two main tracks: 1) power awareness and 2) reliability awareness in dark silicon era, where later these two tracks will combine together. In the first track, the main goal is to increase the level of returns in terms of main important features in chip design, such as performance and throughput, while maximum power limit is honored. In fact, we show that by managing the power while having dark silicon, all the traditional benefits that could be achieved by proceeding in Moore’s law can be also achieved in the dark silicon era, however, with a lower amount. Via the track of reliability awareness in dark silicon era, we show that dark silicon can be considered as an opportunity to be exploited for different instances of benefits, namely life-time increase and online testing. We discuss how dark silicon can be exploited to guarantee the system lifetime to be above a certain target value and, furthermore, how dark silicon can be exploited to apply low cost non-intrusive online testing on the cores. After the demonstration of power and reliability awareness while having dark silicon, two approaches will be discussed as the case study where the power and reliability awareness are combined together. The first approach demonstrates how chip reliability can be used as a supplementary metric for power-reliability management. While the second approach provides a trade-off between workload performance and system reliability by simultaneously honoring the given power budget and target reliability

BlackOut: Enabling fine-grained power gating of buffers in Network-on-Chip routers

The Network-on-Chip (NoC) router buffers play an instrumental role in the performance of both the interconnection fabric and the entire multi-/many-core system. Nevertheless, the buffers also constitute the major leakage power consumers in NoC implementations. Traditionally, they are designed to accommodate worst-case traffic scenarios, so they tend to remain idle, or under-utilized, for extended periods of time. The under-utilization of these valuable resources is exemplified when one profiles real application workloads; the generated traffic is bursty in nature, whereby high traffic periods are sporadic and infrequent, in general. The mitigation of the leakage power consumption of NoC buffers via power gating has been explored in the literature, both at coarse (router-level) and fine (buffer-level) granularities. However, power gating at the router granularity is suitable only for low and medium traffic conditions, where the routers have enough opportunities to be powered down. Under high traffic, the sleeping potential rapidly diminishes. Moreover, disabling an entire router greatly affects the NoC functionality and the network connectivity. This article presents BlackOut, a fine-grained power-gating methodology targeting individual router buffers. The goal is to minimize leakage power consumption, without adversely impacting the system performance. The proposed framework is agnostic of the routing algorithm and the network topology, and it is applicable to any router micro-architecture. Evaluation results obtained using both synthetic traffic patterns and real applications in 64-core systems indicate energy savings of up to 70%, as compared to a baseline NoC, with a near-negligible performance overhead of around 2%. BlackOut is also shown to significantly outperformby 35%, on averagetwo current state-of-the-art power-gating solutions, in terms of energy savings. Not tailored to any topology, routing algorithm and NoC router architecture.Router-to-router communication. No need for custom, region-based/global networks.Effective at low, medium and high traffic. Other solutions are more restrictive.+35% energy saving, on average, against two state-of-the-art power-gating solutions.Negligible performance overhead (+2%) compared to the baseline architecture

Machine Learning for Architectural Design Space Exploration and Resource Control

Machine learning has enabled significant advancements in diverse fields, yet, with a few exceptions, has had limited impact on computer architecture. Recent work, however, has begun to explore broader application to design, optimization, and simulation. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This thesis first reviews existing work applying machine learning to architecture, ranging from simulation and run-time optimization, to individual component design involving the memory system, branch predictors, networks-on-chip, and GPUs. Next, the thesis presents a novel deep-reinforcement-learning framework for design space exploration. Finally, the thesis introduces an innovative strategy for resource optimization with multiple co-scheduled workloads. Taken together, these works present a promising future for machine-learning-based architectural design