Virtual processor frequency emulation

International audienceNowadays, virtualization is present in almost all computing infrastructures. Thanks to VM migration and server consolidation, virtualization helps in reducing power consumption in distributed environments. On another side, Dynamic Voltage and Frequency Scaling (DVFS) allows servers to dynamically modify the processor frequency (according to the CPU load) in order to achieve less energy consumption. We observe that while DVFS is widely used, it still generates a waste of energy. By default and thanks to the ondemand governor, it scales up or down the processor frequency according to the current load and the different predefined threshold (up and down). However, DVFS frequency scaling policies are based on advertised processor frequencies, i.e. the set of frequencies constitutes a discrete range of frequencies. The frequency required for a given load will be set to a frequency higher than necessary; which leads to an energy waste. In this paper, we propose a way to emulate a precise CPU frequency thanks to the DVFS management in virtualized environments. We implemented and evaluated our prototype in the Xen hypervisor

MPSoCBench : um framework para avaliação de ferramentas e metodologias para sistemas multiprocessados em chip

Orientador: Rodolfo Jardim de AzevedoTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Recentes metodologias e ferramentas de projetos de sistemas multiprocessados em chip (MPSoC) aumentam a produtividade por meio da utilização de plataformas baseadas em simuladores, antes de definir os últimos detalhes da arquitetura. No entanto, a simulação só é eficiente quando utiliza ferramentas de modelagem que suportem a descrição do comportamento do sistema em um elevado nível de abstração. A escassez de plataformas virtuais de MPSoCs que integrem hardware e software escaláveis nos motivou a desenvolver o MPSoCBench, que consiste de um conjunto escalável de MPSoCs incluindo quatro modelos de processadores (PowerPC, MIPS, SPARC e ARM), organizado em plataformas com 1, 2, 4, 8, 16, 32 e 64 núcleos, cross-compiladores, IPs, interconexões, 17 aplicações paralelas e estimativa de consumo de energia para os principais componentes (processadores, roteadores, memória principal e caches). Uma importante demanda em projetos MPSoC é atender às restrições de consumo de energia o mais cedo possível. Considerando que o desempenho do processador está diretamente relacionado ao consumo, há um crescente interesse em explorar o trade-off entre consumo de energia e desempenho, tendo em conta o domínio da aplicação alvo. Técnicas de escalabilidade dinâmica de freqüência e voltagem fundamentam-se em gerenciar o nível de tensão e frequência da CPU, permitindo que o sistema alcance apenas o desempenho suficiente para processar a carga de trabalho, reduzindo, consequentemente, o consumo de energia. Para explorar a eficiência energética e desempenho, foram adicionados recursos ao MPSoCBench, visando explorar escalabilidade dinâmica de voltaegem e frequência (DVFS) e foram validados três mecanismos com base na estimativa dinâmica de energia e taxa de uso de CPUAbstract: Recent design methodologies and tools aim at enhancing the design productivity by providing a software development platform before the definition of the final Multiprocessor System on Chip (MPSoC) architecture details. However, simulation can only be efficiently performed when using a modeling and simulation engine that supports system behavior description at a high abstraction level. The lack of MPSoC virtual platform prototyping integrating both scalable hardware and software in order to create and evaluate new methodologies and tools motivated us to develop the MPSoCBench, a scalable set of MPSoCs including four different ISAs (PowerPC, MIPS, SPARC, and ARM) organized in platforms with 1, 2, 4, 8, 16, 32, and 64 cores, cross-compilers, IPs, interconnections, 17 parallel version of software from well-known benchmarks, and power consumption estimation for main components (processors, routers, memory, and caches). An important demand in MPSoC designs is the addressing of energy consumption constraints as early as possible. Whereas processor performance comes with a high power cost, there is an increasing interest in exploring the trade-off between power and performance, taking into account the target application domain. Dynamic Voltage and Frequency Scaling techniques adaptively scale the voltage and frequency levels of the CPU allowing it to reach just enough performance to process the system workload while meeting throughput constraints, and thereby, reducing the energy consumption. To explore this wide design space for energy efficiency and performance, both for hardware and software components, we provided MPSoCBench features to explore dynamic voltage and frequency scalability (DVFS) and evaluated three mechanisms based on energy estimation and CPU usage rateDoutoradoCiência da ComputaçãoDoutora em Ciência da Computaçã

Energy Saving and Virtualization Technologies in Switching

Switching is the key functionality for many devices like electronic Router and Switch, optical Router, Network on Chips (NoCs) and so on. Basically, switching is responsible for moving data unit from one port/location to another (or multiple) port(s)/location(s). In past years, the high capacity, low delay were the main concerns when designing high-end switching unit. As new demands, requests and technologies emerge, flexibility and low power cost switching design become to weight the same as throughput and delay. On one hand, highly flexible (i.e, programming ability) switching can cope with variable needs stem from new applications (i.e, VoIP) and popular user behavior (i.e, p2p downloading); on the other hand, reduce the energy and power dissipation for switching could not only save bills and build echo system but also expand components life time. Many research efforts have been devoted to increase switching flexibility and reduce its power cost. In this thesis work, we consider to exploit virtualization as the main technique to build flexible software router in the first part, then in the second part we draw our attention on energy saving in NoC (i.e, a switching fabric designed to handle the on chip data transmission) and software router. In the first part of the thesis, we consider the virtualization inside Software Routers (SRs). SR, i.e, routers running in commodity Personal Computers (PCs), become an appealing solution compared to traditional Proprietary Routing Devices (PRD) for various reasons such as cost (the multi-vendor hardware used by SRs can be cheap, while the equipment needed by PRDs is more expensive and their training cost is higher), openness (SRs can make use of a large number of open source networking applications, while PRDs are more closed) and flexibility. The forwarding performance provided by SRs has been an obstacle to their deployment in real networks. For this reason, we proposed to aggregate multiple routing units that form an powerful SR known as the Multistage Software Router (MSR) to overcome the performance limitation for a single SR. Our results show that the throughput can increase almost linearly as the number of the internal routing devices. But some other features related to flexibility (such as power saving, programmability, router migration or easy management) have been investigated less than performance previously. We noticed that virtualization techniques become reality thanks to the quick development of the PC architectures, which are now able to easily support several logical PCs running in parallel on the same hardware. Virtualization could provide many flexible features like hardware and software decoupling, encapsulation of virtual machine state, failure recovery and security, to name a few. Virtualization permits to build multiple SRs inside one physical host and a multistage architecture exploiting only logical devices. By doing so, physical resources can be used in a more efficient way, energy savings features (switching on and off device when needed) can be introduced and logical resources could be rented on-demand instead of being owned. Since virtualization techniques are still difficult to deploy, several challenges need to be faced when trying to integrate them into routers. The main aim of the first part in this thesis is to find out the feasibility of the virtualization approach, to build and test virtualized SR (VSR), to implement the MSR exploiting logical, i.e. virtualized, resources, to analyze virtualized routing performance and to propose improvement techniques to VSR and virtual MSR (VMSR). More specifically, we considered different virtualization solutions like VMware, XEN, KVM to build VSR and VMSR, being VMware a closed source solution but with higher performance and XEN/KVM open source solutions. Firstly we built and tested each single component of our multistage architecture (i.e, back-end router, load balancer )inside the virtual infrastructure, then and we extended the performance experiments with more complex scenarios like multiple Back-end Router (BR) or Load Balancer (LB) which cooperate to route packets. Our results show that virtualization could introduce 40~\% performance penalty compare with the hardware only solution. Keep the performance limitation in mind, we developed the whole VMSR and we obtained low throughput with 64B packet flow as expected. To increase the VMSR throughput, two directions could be considered, the first one is to improve the single component ( i.e, VSR) performance and the other is to work from the topology (i.e, best allocation of the VMs into the hardware ) point of view. For the first method, we considered to tune the VSR inside the KVM and we studied closely such as Linux driver, scheduler, interconnect methodology which could impact the performance significantly with proper configuration; then we proposed two ways for the VMs allocation into physical servers to enhance the VMSR performance. Our results show that with good tuning and allocation of VMs, we could minimize the virtualization penalty and get reasonable throughput for running SRs inside virtual infrastructure and add flexibility functionalities into SRs easily. In the second part of the thesis, we consider the energy efficient switching design problem and we focus on two main architecture, the NoC and MSR. As many research works suggest, the energy cost in the Communication Technologies ( ICT ) is constantly increasing. Among the main ICT sectors, a large portion of the energy consumption is contributed by the telecommunication infrastructure and their devices, i.e, router, switch, cell phone, ip TV settle box, storage home gateway etc. More in detail, the linecards, links, System on Chip (SoC) including the transmitter/receiver on these variate devices are the main power consuming units. We firstly present the work on the power reduction of the data transmission in SoC, which is carried out by the NoC. NoC is an approach to design the communication subsystem between different Processing Units (PEs) in a SoC. PEs could be different elements such as CPU, memory, digital signal/analog signal processor etc. Different PEs performs specific tasks depending on the applications running on the chip. Different tasks need to exchange data information among each other, thus flits ( chopped packet with limited header information ) are generated by PEs. The flits are injected into the NoC by the proper interface and routed until reach the destination PEs. For the whole procedure, the NoC behaves as a packet switch network. Studies show that in general the information processing in the PEs only consume 60~\% energy while the remaining 40~\% are consumed by the NoC. More importantly, as the current network designing principle, the NoC capacity is devised to handle the peak load. This is a clear sign for energy saving when the network load is low. In our work, we considered to exploit Dynamic Voltage and Frequency Scaling (DVFS) technique, which can jointly decrease or increase the system voltage and frequency when necessary, i.e, decrease the voltage and frequency at low load scenario to save energy and reduce power dissipation. More precisely, we studied two different NoC architectures for energy saving, namely single plane chip and multi-plane chip architecture. In both cases we have a very strict constraint to be that all the links and transmitter/receivers on the same plane work at the same frequency/voltage to avoid synchronization problem. This is the main difference with many existing works in the literature which usually assume different links can work at different frequency, that is hard to be implemented in reality. For the single plane NoC, we exploited different routing schemas combined with DVFS to reduce the power for the whole chip. Our results haven been compared with the optimal value obtained by modeling the power saving formally as a quadratic programming problem. Results suggest that just by using simple load balancing routing algorithm, we can save considerable energy for the single chip NoC architecture. Furthermore, we noticed that in the single plane NoC architecture, the bottleneck link could limit the DVFS effectiveness. Then we discovered that multiplane NoC architecture is fairly easy to be implemented and it could help with the energy saving. Thus we focus on the multiplane architecture and we found out that DVFS could be more efficient when we concentrate more traffic into one plane and send the remaining flows to other planes. We compared load concentration and load balancing with different power modeling and all simulation results show that load concentration is better compared with load balancing for multiplan NoC architecture. Finally, we also present one of the the energy efficient MSR design technique, which permits the MSR to follow the day-night traffic pattern more efficiently with our on-line energy saving algorithm

ControlPULP: A RISC-V On-Chip Parallel Power Controller for Many-Core HPC Processors with FPGA-Based Hardware-In-The-Loop Power and Thermal Emulation

High-Performance Computing (HPC) processors are nowadays integrated Cyber-Physical Systems demanding complex and high-bandwidth closed-loop power and thermal control strategies. To efficiently satisfy real-time multi-input multi-output (MIMO) optimal power requirements, high-end processors integrate an on-die power controller system (PCS). While traditional PCSs are based on a simple microcontroller (MCU)-class core, more scalable and flexible PCS architectures are required to support advanced MIMO control algorithms for managing the ever-increasing number of cores, power states, and process, voltage, and temperature variability. This paper presents ControlPULP, an open-source, HW/SW RISC-V parallel PCS platform consisting of a single-core MCU with fast interrupt handling coupled with a scalable multi-core programmable cluster accelerator and a specialized DMA engine for the parallel acceleration of real-time power management policies. ControlPULP relies on FreeRTOS to schedule a reactive power control firmware (PCF) application layer. We demonstrate ControlPULP in a power management use-case targeting a next-generation 72-core HPC processor. We first show that the multi-core cluster accelerates the PCF, achieving 4.9x speedup compared to single-core execution, enabling more advanced power management algorithms within the control hyper-period at a shallow area overhead, about 0.1% the area of a modern HPC CPU die. We then assess the PCS and PCF by designing an FPGA-based, closed-loop emulation framework that leverages the heterogeneous SoCs paradigm, achieving DVFS tracking with a mean deviation within 3% the plant's thermal design power (TDP) against a software-equivalent model-in-the-loop approach. Finally, we show that the proposed PCF compares favorably with an industry-grade control algorithm under computational-intensive workloads.Comment: 33 pages, 11 figure

A Workload-Aware, Eco-Friendly Daemon for Cluster Computing

This paper presents an eco-friendly daemon that reduces power consumption while better maintaining high performance via a novel behavioral quantification of workload. Specifically, our behavioral quantification achieves a more accurate workload characterization than previous approaches by inferring "processor stall cycles due to off-chip activities." This quantification, in turn, provides a foundation upon which we construct an interval-based, power-aware, run-time algorithm that is implemented within a system-wide daemon. We then evaluate our power-aware daemon in a cluster-computing environment with the NAS Parallel Benchmarks. The results indicate that our novel behavioral quantification of workload allows our power-aware daemon to more tightly control performance while delivering substantial energy savings

Machine Learning-Based Dynamic Voltage and Frequency Scaling Error Detection

Modern microprocessors are more and more optimized for speed and power efficiency. A system that regulates these parameters is Dynamic Voltage and Frequency Scaling (DVFS). Generally, all bugs or errors in a microarchitecture fall under two categories: performance and logical. These errors can apply to any component of the microarchitecture. A performance error is an error that results not in a logically incorrect output of a system, but a slowdown in the production of that output. Most broadly, errors related to DVFS would be not increasing voltage and frequency leading to slower execution in real time, or the inverse (increasing voltage and frequency) leading to wasteful power consumption and chip degradation. The first slows down the machine unnecessarily, and the second decreases expected battery time. Using machine learning to analyze data extracted from gem5 to detect these errors is the objective of this project

Simulating Execution Time and Power Consumption of Real-Time Tasks on Embedded Platforms

In this paper, we present PARTSim, an open-source power/thermal-aware simulator for embedded real-time systems. This tool is a fork of the well-known RTSim simulator, which can simulate the timing behavior of a set of real-time tasks with various characteristics when running on a multi-processor platform in presence of a number of real-time scheduling policies. PARTSim extends the functionality of RTSim by introducing support for power-aware embedded platforms exhibiting frequency scaling and specific architectural patterns like the ARM big.LITTLE and DynamIQ ones. Experimental results that compare simulated data against execution profiles collected on real platforms show a simulation error under 10 % for both execution time and power consumption at 90th percentile when simulating the effects of DVFS

Comprehensive characterization of an open source document search engine

This work performs a thorough characterization and analysis of the open source Lucene search library. The article describes in detail the architecture, functionality, and micro-architectural behavior of the search engine, and investigates prominent online document search research issues. In particular, we study how intra-server index partitioning affects the response time and throughput, explore the potential use of low power servers for document search, and examine the sources of performance degradation ands the causes of tail latencies. Some of our main conclusions are the following: (a) intra-server index partitioning can reduce tail latencies but with diminishing benefits as incoming query traffic increases, (b) low power servers given enough partitioning can provide same average and tail response times as conventional high performance servers, (c) index search is a CPU-intensive cache-friendly application, and (d) C-states are the main culprits for performance degradation in document search.Web of Science162art. no. 1

ADAPTIVE POWER MANAGEMENT FOR COMPUTERS AND MOBILE DEVICES

Power consumption has become a major concern in the design of computing systems today. High power consumption increases cooling cost, degrades the system reliability and also reduces the battery life in portable devices. Modern computing/communication devices support multiple power modes which enable power and performance tradeoff. Dynamic power management (DPM), dynamic voltage and frequency scaling (DVFS), and dynamic task migration for workload consolidation are system level power reduction techniques widely used during runtime. In the first part of the dissertation, we concentrate on the dynamic power management of the personal computer and server platform where the DPM, DVFS and task migrations techniques are proved to be highly effective. A hierarchical energy management framework is assumed, where task migration is applied at the upper level to improve server utilization and energy efficiency, and DPM/DVFS is applied at the lower level to manage the power mode of individual processor. This work focuses on estimating the performance impact of workload consolidation and searching for optimal DPM/DVFS that adapts to the changing workload. Machine learning based modeling and reinforcement learning based policy optimization techniques are investigated. Mobile computing has been weaved into everyday lives to a great extend in recent years. Compared to traditional personal computer and server environment, the mobile computing environment is obviously more context-rich and the usage of mobile computing device is clearly imprinted with user\u27s personal signature. The ability to learn such signature enables immense potential in workload prediction and energy or battery life management. In the second part of the dissertation, we present two mobile device power management techniques which take advantage of the context-rich characteristics of mobile platform and make adaptive energy management decisions based on different user behavior. We firstly investigate the user battery usage behavior modeling and apply the model directly for battery energy management. The first technique aims at maximizing the quality of service (QoS) while keeping the risk of battery depletion below a given threshold. The second technique is an user-aware streaming strategies for energy efficient smartphone video playback applications (e.g. YouTube) that minimizes the sleep and wake penalty of cellular module and at the same time avoid the energy waste from excessive downloading. Runtime power and thermal management has attracted substantial interests in multi-core distributed embedded systems. Fast performance evaluation is an essential step in the research of distributed power and thermal management. In last part of the dissertation, we present an FPGA based emulator of multi-core distributed embedded system designed to support the research in runtime power/thermal management. Hardware and software supports are provided to carry out basic power/thermal management actions including inter-core or inter-FPGA communications, runtime temperature monitoring and dynamic frequency scaling