Browsing by Subject "DVFS"
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Item Bottleneck identification and acceleration in multithreaded applications(2014-12) Joao, José Alberto; Patt, Yale N.When parallel applications do not fully utilize the cores that are available to them they are missing the opportunity to have better performance. Sometimes threads have to wait for other threads. I call the code segments that make other threads wait bottlenecks. Examples of these bottlenecks include contended critical sections, threads arriving late to barriers and the slowest stage of a pipelined program. Other times all threads are running but some of them, which I call lagging threads, are making less progress, setting the stage to become bottlenecks. My thesis proposes identifying the code segments that are more critical for performance and efficiently accelerating them using faster cores, by either migrating execution to large cores of an Asymmetric Chip Multi-Processor (ACMP) or executing locally on DVFS-accelerated cores. The key contribution of this dissertation is a Utility of Acceleration metric that combines a measure of the acceleration for each code segment with a measure of its criticality. This metric enables meaningful comparisons to decide which bottlenecks or lagging threads to accelerate with each of the available acceleration mechanisms. My evaluation shows significant performance improvement for single multithreaded applications and sets of multiple single- and multi-threaded applications, and also reduction in energy-delay product due to the efficient utilization of the available acceleration mechanisms.Item Circuit and System Level Design Optimization for Power Delivery And Management(2014-12-08) Xu, TongAs the VLSI technology scales to the nanometer scale, power consumption has become a critical design concern of VLSI circuits. Power gating and dynamic voltage and frequency scaling (DVFS) are two effective power management techniques that are widely utilized in modern chip designs. Various design challenges merge with these power management techniques in nanometer VLSI circuits. For example, power gating introduces unique power integrity issues and trade-offs between switching noise and rush current noise. Assuring power integrity and achieving power efficiency are two highly intertwined design challenges. In addition, these trade-offs significantly vary with the supply voltage. It is difficult to use conventional power-gated power delivery networks (PDNs) to fully meet the involved conflicting design constraints while maximizing power saving and minimizing supply noise. The DVFS controller and the DC-DC power converter are two highly intertwining enablers for DVFS-based systems. However, traditional DVFS techniques treat the design optimizations of the two as separate tasks, giving rise to sub-optimal designs. To address the above research challenges, we propose several circuit and system level design optimization techniques in this dissertation. For power-gated PDN designs, we propose systemic decoupling capacitor (decap) optimization strategies that optimally trade-off between power integrity and leakage saving. First, new global decap and re-routable decap design concepts are proposed to relax the tight interaction between power integrity and leakage power saving of power-gated PDN at a single supply voltage level. Furthermore, we propose to leverage re-routable decaps to provide flexible decap allocation structures to better suit multiple supply voltage levels. The proposed strategies are implemented in an automatic design flow for choosing optimal amount of local decaps, global decaps and re-routable decaps. The proposed techniques significantly increase leakage saving without jeopardizing power integrity. The flexible decap allocations enabled by re-routable decaps lead to optimal design trade-offs for PDNs operating with two supply voltage levels. To improve the effectiveness of DVFS, we analyze the drawbacks of circuit-level only and policy-level only optimizations and the promising opportunities resulted from the cross-layer co-optimization of the DC-DC converter and online learning based DVFS polices. We present a cross-layer approach that optimizes transition time, area, energy overhead of the DC-DC converter along with key parameters of an online learning DVFS controller. We systematically evaluate the benefits of the proposed co-optimization strategy based on several processor architectures, namely single and dual-core processors and processors with DVFS and power gating. Our results indicate that the co-optimization can introduce noticeable additional energy saving without significant performance degradation.Item Control Techniques for Uncore Power Mangement in Chip Multiprocessor Designs(2013-08-01) Xu, ZhengIn chip-multiprocessor (CMP) designs, when the number of core increases, the size of on-chip communication fabric and data storage grows accordingly and therefore the chip power challenge is exacerbated. This thesis work considers the power management for networks-on-chip (NoC) and the last level cache, which constitute the uncore in CMP designs. NoC is regarded as a scalable approach to cope with the increasing demand for on-chip communication bandwidth. The last level cache is shared among all cores. The focus of this work is on the control techniques for uncore dynamic voltage and frequency scaling. A realistic but not well-studied scenario is investigated. That is, the entire uncore shares a single voltage/frequency domain, as opposed to separated domains in most of previous works. One appealing advantage here is that data packets no longer experience the interfacing overhead across different voltage/frequency domains. The classic PI (Proportional and Integral) control method is adopted due to its simplicity, flexibility and low implementation overhead. This thesis research outcome includes three parts. First, stability of the PI control is analyzed. Second, a model-assisted PI control scheme is proposed and studied. The model assist is to address the problem that no universally good reference point exists for the control. Third, the windup issue for the PI control is investigated. Full architecture simulations are performed on public benchmark suites to validate the proposed techniques. The result show 76% energy reduction with less than 6% performance degradation compared to constantly high voltage/frequency for uncore.Item Energy Efficient Scheduling for Real-Time Systems(2012-02-14) Gupta, NikhilThe goal of this dissertation is to extend the state of the art in real-time scheduling algorithms to achieve energy efficiency. Currently, Pfair scheduling is one of the few scheduling frameworks which can optimally schedule a periodic real-time taskset on a multiprocessor platform. Despite the theoretical optimality, there exist large concerns about efficiency and applicability of Pfair scheduling in practical situations. This dissertation studies and proposes solutions to such efficiency and applicability concerns. This dissertation also explores temperature aware energy management in the domain of real-time scheduling. The thesis of this dissertation is: the implementation efficiency of Pfair scheduling algorithms can be improved. Further, temperature awareness of a real-time system can be improved while considering variation of task execution times to reduce energy consumption. This thesis is established through research in a number of directions. First, we explore the applicability of Dynamic Voltage and Frequency Scaling (DVFS) feature in the underlying platform, within Pfair scheduled systems. We propose techniques to reduce energy consumption in Pfair scheduling by using DVFS. Next, we explore the problem of quantum size selection in Pfair scheduled system so that runtime overheads are minimized. We also propose a hardware design for a central Pfair scheduler core in a multiprocessor system to minimized the overheads and energy consumption of Pfair scheduling. Finally, we propose a temperature aware energy management scheme for tasks with varying execution times.Item E³ : energy-efficient EDGE architectures(2010-08) Govindan, Madhu Sarava; Keckler, Stephen W.; Burger, Douglas C.; McKinley, Kathryn S.; Chiou, Derek; Hunt, Jr., Warren A.; Brooks, DavidIncreasing power dissipation is one of the most serious challenges facing designers in the microprocessor industry. Power dissipation, increasing wire delays, and increasing design complexity have forced industry to embrace multi-core architectures or chip multiprocessors (CMPs). While CMPs mitigate wire delays and design complexity, they do not directly address single-threaded performance. Additionally, programs must be parallelized, either manually or automatically, to fully exploit the performance of CMPs. Researchers have recently proposed an architecture called Explicit Data Graph Execution (EDGE) as an alternative to conventional CMPs. EDGE architectures are designed to be technology-scalable and to provide good single-threaded performance as well as exploit other types of parallelism including data-level and thread-level parallelism. In this dissertation, we examine the energy efficiency of a specific EDGE architecture called TRIPS Instruction Set Architecture (ISA) and two microarchitectures called TRIPS and TFlex that implement the TRIPS ISA. TRIPS microarchitecture is a first-generation design that proves the feasibility of the TRIPS ISA and distributed tiled microarchitectures. The second-generation TFlex microarchitecture addresses key inefficiencies of the TRIPS microarchitecture by matching the resource needs of applications to a composable hardware substrate. First, we perform a thorough power analysis of the TRIPS microarchitecture. We describe how we develop architectural power models for TRIPS. We then improve power-modeling accuracy using hardware power measurements on the TRIPS prototype combined with detailed Register Transfer Level (RTL) power models from the TRIPS design. Using these refined architectural power models and normalized power modeling methodologies, we perform a detailed performance and power comparison of the TRIPS microarchitecture with two different processors: 1) a low-end processor designed for power efficiency (ARM/XScale) and 2) a high-end superscalar processor designed for high performance (a variant of Power4). This detailed power analysis provides key insights into the advantages and disadvantages of the TRIPS ISA and microarchitecture compared to processors on either end of the performance-power spectrum. Our results indicate that the TRIPS microarchitecture achieves 11.7 times better energy efficiency compared to ARM, and approximately 12% better energy efficiency than Power4, in terms of the Energy-Delay-Squared (ED²) metric. Second, we evaluate the energy efficiency of the TFlex microarchitecture in comparison to TRIPS, ARM, and Power4. TFlex belongs to a class of microarchitectures called Composable Lightweight Processors (CLPs). CLPs are distributed microarchitectures designed with simple cores and are highly configurable at runtime to adapt to resource needs of applications. We develop power models for the TFlex microarchitecture based on the validated TRIPS power models. Our quantitative results indicate that by better matching execution resources to the needs of applications, the composable TFlex system can operate in both regimes of low power (similar to ARM) and high performance (similar to Power4). We also show that the composability feature of TFlex achieves a signification improvement (2 times) in the ED² metric compared to TRIPS. Third, using TFlex as our experimental platform, we examine the efficacy of processor composability as a potential performance-power trade-off mechanism. Most modern processors support a form of dynamic voltage and frequency scaling (DVFS) as a performance-power trade-off mechanism. Since the rate of voltage scaling has slowed significantly in recent process technologies, processor designers are in dire need of alternatives to DVFS. In this dissertation, we explore processor composability as an architectural alternative to DVFS. Through experimental results we show that processor composability achieves almost as good performance-power trade-offs as pure frequency scaling (no changes in supply voltages), and a much better performance-power trade-off compared to voltage and frequency scaling (both supply voltage and frequency change). Next, we explore the effects of additional performance-improving techniques for the TFlex system on its energy efficiency. Researchers have proposed a variety of techniques for improving the performance of the TFlex system. These include: (1) block mapping techniques to trade off intra-block concurrency with communication across the operand network; (2) predicate prediction and (3) operand multi-cast/broadcast mechanism. We examine each of these mechanisms in terms of its effect on the energy efficiency of TFlex, and our experimental results demonstrate the effects of operand communication, and speculation on the energy efficiency of TFlex. Finally, this dissertation evaluates a set of fine-grained power management (FGPM) policies for TFlex: instruction criticality and controlled speculation. These policies rely on a temporally and spatially fine-grained dynamic voltage and frequency scaling (DVFS) mechanism for improving power efficiency. The instruction criticality policy seeks to improve power efficiency by mapping critical computation in a program to higher performance-power levels, and by mapping non-critical computation to lower performance-power levels. Controlled speculation policy, on the other hand, maps blocks that are highly likely to be on correct execution path in a program to higher performance levels, and the other blocks to lower performance levels. Our experimental results indicate that idealized instruction criticality and controlled speculation policies improve the operating range and flexibility of the TFlex system. However, when the actual overheads of fine-grained DVFS, especially energy conversion losses of voltage regulator modules (VRMs), are considered the power efficiency advantages of these idealized policies quickly diminish. Our results also indicate that the current conversion efficiencies of on-chip VRMs need to improve to as high as 95% for the realistic policies to be feasible.Item Integrated temperature sensors in deep sub-micron CMOS technologies(2014-05) Chowdhury, Golam Rasul; Hassibi, ArjangIntegrated temperature sensors play an important role in enhancing the performance of on-chip power and thermal management systems in today's highly-integrated system-on-chip (SoC) platforms, such as microprocessors. Accurate on-chip temperature measurement is essential to maximize the performance and reliability of these SoCs. However, due to non-uniform power consumption by different functional blocks, microprocessors have fairly large thermal gradient (and variation) across their chips. In the case of multi-core microprocessors for example, there are task-specific thermal gradients across different cores on the same die. As a result, multiple temperature sensors are needed to measure the temperature profile at all relevant coordinates of the chip. Subsequently, the results of the temperature measurements are used to take corrective measures to enhance the performance, or save the SoC from catastrophic over-heating situations which can cause permanent damage. Furthermore, in a large multi-core microprocessor, it is also imperative to continuously monitor potential hot-spots that are prone to thermal runaway. The locations of such hot spots depend on the operations and instruction the processor carries out at a given time. Due to practical limitations, it is an overkill to place a big size temperature sensor nearest to all possible hot spots. Thus, an ideal on-chip temperature sensor should have minimal area so that it can be placed non-invasively across the chip without drastically changing the chip floor plan. In addition, the power consumption of the sensors should be very low to reduce the power budget overhead of thermal monitoring system, and to minimize measurement inaccuracies due to self-heating. The objective of this research is to design an ultra-small size and ultra-low power temperature sensor such that it can be placed in the intimate proximity of all possible hot spots across the chip. The general idea is to use the leakage current of a reverse-bias p-n junction diode as an operand for temperature sensing. The tasks within this project are to examine the theoretical aspect of such sensors in both Silicon-On-Insulator (SOI), and bulk Complementary Metal-Oxide Semiconductor (CMOS) technologies, implement them in deep sub-micron technologies, and ultimately evaluate their performances, and compare them to existing solutions.Item Microprocessor power management and a stand-alone benchmarking application for Android based platforms(2011-12) Yeager, Hans L.; Aziz, Adnan; Gerstlauer, AndreasComponents used in mobile hand-held devices (smart phones and tablets) vary greatly in performance and power consumption. The microprocessors used in these devices also have vastly different capabilities and manufacturing limitations leading to significant variation effects. Battery life is a significant concern to the end users of these products. A stand-alone Android application capable of benchmarking a device's performance and power consumption is introduced. The application does not require the end user to have any analytic equipment or to have a technical background. This enables individual end users to better understand their particular device's performance and battery life interaction. They may also use the application to determine if their device's performance or battery life has degraded over time. Data is also uploaded to a central location so that devices can be compared against each other. The benchmarking application is capable of resolving variation effects caused by device, environmental changes and power management actions. This application demonstrates the feasibility of creating a low cost ecosystem where thousands of devices can be quantitatively compared.Item Ocin_tsim - A DVFS Aware Simulator for NoC Design Space Exploration and Optimization(2010-07-14) Prabhu, SubodhNetworks-on-Chip (NoCs) are a general purpose, scalable replacement for shared medium wired interconnects offering many practical applications in industry. Dynamic Voltage Frequency Scaling (DVFS) is a technique whereby a chip?s voltage-frequency levels are varied at run time, often used to conserve dynamic power. Various DVFSbased NoC optimization techniques have been proposed. However, due to the resources required to validate architectural decisions through prototyping, few are implemented. As a result, designers are faced with a lack of insight into potential power savings or performance gains at early architecture stages. This thesis proposes a DVFS aware NoC simulator with support for per node power-frequency modeling to allow fine-tuning of such optimization techniques early on in the design cycle. The proposed simulator also provides a framework for benchmarking various candidate strategies to allow selective prototyping and optimization. As part of the research, DVFS extensions were built for an existing NoC performance simulator and released for public use. This thesis presents some of the preliminary results from our simulator that show the average power consumed per node for all the benchmarks in SPLASH 2 benchmark suite [74] to be quite similar to each other. This thesis also serves as a technical manual for the simulator extensions. Important links for downloading and using the simulator are provided at the end of this document in Appendix C.Item Performance prediction for dynamic voltage and frequency scaling(2014-08) Miftakhutdinov, Rustam Raisovich; Patt, Yale N.This dissertation proves the feasibility of accurate runtime prediction of processor performance under frequency scaling. The performance predictors developed in this dissertation allow processors capable of dynamic voltage and frequency scaling (DVFS) to improve their performance or energy efficiency by dynamically adapting chip or core voltages and frequencies to workload characteristics. The dissertation considers three processor configurations: the uniprocessor capable of chip-level DVFS, the private cache chip multiprocessor capable of per-core DVFS, and the shared cache chip multiprocessor capable of per-core DVFS. Depending on processor configuration, the presented performance predictors help the processor realize 72–85% of average oracle performance or energy efficiency gains.Item Predictive power management for multi-core processors(2010-12) Bircher, William Lloyd; John, Lizy Kurian; Erez, Mattan; Keckler, Steve; Lefurgy, Charles; Moon, Tess; Pan, DavidEnergy consumption by computing systems is rapidly increasing due to the growth of data centers and pervasive computing. In 2006 data center energy usage in the United States reached 61 billion kilowatt-hours (KWh) at an annual cost of 4.5 billion USD [Pl08]. It is projected to reach 100 billion KWh by 2011 at a cost of 7.4 billion USD. The nature of energy usage in these systems provides an opportunity to reduce consumption. Specifically, the power and performance demand of computing systems vary widely in time and across workloads. This has led to the design of dynamically adaptive or power managed systems. At runtime, these systems can be reconfigured to provide optimal performance and power capacity to match workload demand. This causes the system to frequently be over or under provisioned. Similarly, the power demand of the system is difficult to account for. The aggregate power consumption of a system is composed of many heterogeneous systems, each with a unique power consumption characteristic. This research addresses the problem of when to apply dynamic power management in multi-core processors by accounting for and predicting power and performance demand at the core-level. By tracking performance events at the processor core or thread-level, power consumption can be accounted for at each of the major components of the computing system through empirical, power models. This also provides accounting for individual components within a shared resource such as a power plane or top-level cache. This view of the system exposes the fundamental performance and power phase behavior, thus making prediction possible. This dissertation also presents an extensive analysis of complete system power accounting for systems and workloads ranging from servers to desktops and laptops. The analysis leads to the development of a simple, effective prediction scheme for controlling power adaptations. The proposed Periodic Power Phase Predictor (PPPP) identifies patterns of activity in multi-core systems and predicts transitions between activity levels. This predictor is shown to increase performance and reduce power consumption compared to reactive, commercial power management schemes by achieving higher average frequency in active phases and lower average frequency in idle phases.Item VLSI Implementation of Low Power Reconfigurable MIMO Detector(2009-12-02) Dash, RajballavMultiple Input Multiple Output (MIMO) systems are a key technology for next generation high speed wireless communication standards like 802.11n, WiMax etc. MIMO enables spatial multiplexing to increase channel bandwidth which requires the use of multiple antennas in the receiver and transmitter side. The increase in bandwidth comes at the cost of high silicon complexity of MIMO detectors which result, due to the intricate algorithms required for the separation of these spatially multiplexed streams. Previous implementations of MIMO detector have mainly dealt with the issue of complexity reduction, latency minimization and throughput enhancement. Although, these detectors have successfully mapped algorithms to relatively simpler circuits but still, latency and throughput of these systems need further improvements to meet standard requirements. Additionally, most of these implementations don?t deal with the requirements of reconfigurability of the detector to multiple modulation schemes and different antennae configurations. This necessary requirement provides another dimension to the implementation of MIMO detector and adds to the implementation complexity. This thesis focuses on the efficient VLSI implementation of the MIMO detector with an emphasis on performance and re-configurability to different modulation schemes. MIMO decoding in our detector is based on the fixed sphere decoding algorithm which has been simplified for an effective VLSI implementation without considerably degrading the near optimal bit error rate performance. The regularity of the architecture makes it suitable for a highly parallel and pipelined implementation. The decoder has intrinsic traits for dynamic re-configurability to different modulation and encoding schemes. This detector architecture can be easily tuned for high/low performance requirements with slight degradation/improvement in Bit Error Rate (BER) depending on needs of the overlying application. Additionally, various architectural optimizations like pipelining, parallel processing, hardware scheduling, dynamic voltage and frequency scaling have been explored to improve the performance, energy requirements and re-configurability of the design.