Dynamic power management (DPM) is a design methodology for dynamically reconfiguring systems to provide the requested services and performance levels with a minimum number of active components or a minimum load on such components. DPM encompasses a set of techniques that achieves energy-efficient computation by selectively turning off (or reducing the performance of) system components when they are idle (or partially unexploited). In this paper, we survey several approaches to system-level dynamic power management. We first describe how systems employ power-manageable components and how the use of dynamic reconfiguration can impact the overall power consumption. We then analyze DPM implementation issues in electronic systems, and we survey recent initiatives in standardizing the hardware/software interface to enable software-controlled power management of hardware components.

A survey of design techniques for system-level dynamic power management : Special section on low-power electronics and design

Dynamic power management (DPM) is a design methodology for dynamically reconfiguring systems to provide the requested services and performance levels with a minimum number of active components or a minimum load on such components DPM encompasses a set of techniques that achieves energy-efficient computation by selectively turning off (or reducing the performance of) system components when they are idle (or partially unexploited) In this paper, we survey several approaches to system-level dynamic power management We first describe how systems employ power-manageable components and how the use of dynamic reconfiguration can impact the overall power consumption We then analyze DPM implementation issues in electronic systems, and we survey recent initiatives in standardizing the hardware/software interface to enable software-controlled power management of hardware components

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A survey of design techniques for system-level dynamic power management

Dynamic power management schemes (also called policies) reduce the power consumption of complex electronic systems by trading off performance for power in a controlled fashion, taking system workload into account. In a power-managed system it is possible to set components into different states, each characterized by performance and power consumption levels. The main function of a power management policy is to decide when to perform component state transitions and which transition should be performed, depending on system history, workload, and performance constraints. In the past, power management policies have been formulated heuristically. The main contribution of this paper is to introduce a finite-state, abstract system model for power-managed systems based on Markov decision processes. Under this model, the problem of finding policies that optimally tradeoff performance for power can be cast as a stochastic optimization problem and solved exactly and efficiently. The applicability and generality of the approach are assessed by formulating the Markov model and optimizing power management policies for several systems.

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Policy optimization for dynamic power management

This tutorial surveys design methods for energy-efficient system-level design. We consider electronic sytems consisting of a hardware platform and software layers. We consider the three major constituents of hardware that consume energy, namely computation, communication, and storage units, and we review methods of reducing their energy consumption. We also study models for analyzing the energy cost of software, and methods for energy-efficient software design and compilation. This survery is organized around three main phases of a system design: conceptualization and modeling design and implementation, and runtime management. For each phase, we review recent techniques for energy-efficient design of both hardware and software.

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System-level power optimization: techniques and tools

The increasing popularity of power constrained mobile computers and embedded computing applications drives the need for analyzing and optimizing power in all the components of a system. Software constitutes a major component of today's systems, and its role is projected to grow even further. Thus, an ever increasing portion of the functionality of today's systems is in the form of instructions, as opposed to gates. This motivates the need for analyzing power consumption from the point of view of instructions--something that traditional circuit and gate level power analysis tools are inadequate for. This paper describes an alternative, measurement based instruction level power analysis approach that provides an accurate and practical way of quantifying the power cost of soft-ware. This technique has been applied to three commercial, architecturally different processors. The salient results of these analyses are summarized. Instruction level analysis of a processor helps in the development of models for power consumption of software executing on that processor. The power models for the subject processors are described and interesting observations resulting from the comparison of these models are highlighted. The ability to evaluate software in terms of power consumption makes it feasible to seach fow low power implementations of given programs. In addition, it can guide the development of general tools and techniques for low power software. Several ideas in this regard as motivated by the power analysis of the subject processors are also described.

Instruction level power analysis and optimization of software

The PowerPC 603 incorporates a variety of features to reduce power dissipation: dynamic idle-time shutdown of separate execution units, low-power cache design, and power considerations for standard cells, data-path elements, and clocking. System-level features include three software-programmable static power management modes and a hardware-programmable phase-lock loop. Operating at 80 MHz, the 603 typically dissipates 2.2 W, while achieving an estimated 75 Specint92 and 85 Specfp92. >

J. Eno

Papers

PowerPC 603, a microprocessor for portable computers