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Power Management is a feature of some electrical appliances, especially copiers, computers, GPUs and computer peripherals such as monitors and printers, that turns off the power or switches the system to a low-power state when inactive. In computing this is known as PC power management and is built around a standard called ACPI. This supersedes APM. All recent (consumer) computers have ACPI support. In the military, ""Power Management"" often refers to suites of equipment which permit soldiers and squads to share diverse energy sources, powering often incompatible equipment.[1]

Contents

1 Motivations 2 Processor level techniques

2.1 Heterogenous computing

3 Operating system level: Hibernation 4 Power Management in GPUs

4.1 DVFS Techniques 4.2 Power Gating Techniques

5 See also 6 References 7 External links

Motivations[edit] PC power management for computer systems is desired for many reasons, particularly:

Reduce overall energy consumption Prolong battery life for portable and embedded systems Reduce cooling requirements Reduce noise Reduce operating costs for energy and cooling

Lower power consumption also means lower heat dissipation, which increases system stability, and less energy use, which saves money and reduces the impact on the environment. Processor level techniques[edit] The power management for microprocessors can be done over the whole processor,[2] or in specific components, such as cache memory[3] and main memory.[4] With dynamic voltage scaling and dynamic frequency scaling, the CPU core voltage, clock rate, or both, can be altered to decrease power consumption at the price of potentially lower performance. This is sometimes done in real time to optimize the power-performance tradeoff. Examples:

AMD
AMD
Cool'n'Quiet AMD
AMD
PowerNow! [5] IBM EnergyScale [6] Intel SpeedStep Transmeta LongRun and LongRun2 VIA LongHaul (PowerSaver)

Additionally, processors can selectively power off internal circuitry (power gating). For example:

Newer Intel Core
Intel Core
processors support ultra-fine power control over the functional units within the processors. AMD
AMD
CoolCore technology get more efficient performance by dynamically activating or turning off parts of the processor.[7]

Intel VRT technology split the chip into a 3.3V I/O section and a 2.9V core section. The lower core voltage reduces power consumption. Heterogenous computing[edit] ARM's big.LITTLE architecture can migrate processes between faster "big" cores and more power efficient "LITTLE" cores. Operating system level: Hibernation[edit] Main article: Hibernation (computing) When a computer system hibernates it saves the contents of the RAM to disk and powers down the machine. On startup it reloads the data. This allows the system to be completely powered off while in hibernate mode. This requires a file the size of the installed RAM to be placed on the hard disk, potentially using up space even when not in hibernate mode. Hibernate mode is enabled by default in some versions of Windows and can be disabled in order to recover this disk space. Power Management in GPUs[edit] Graphics processing unit (GPUs) are used together with a CPU
CPU
to accelerate computing in variety of domains revolving around scientific, analytics, engineering, consumer and enterprise applications.[8] All of this do come with some drawbacks, the high computing capability of GPUs comes at the cost of high power dissipation. A lot of research has been done over the power dissipation issue of GPUs and a lot of different techniques have been proposed to address this issue. Dynamic voltage scaling/Dynamic frequency scaling(DVFS) and clock gating are two commonly used techniques for reducing dynamic power in GPUs. DVFS Techniques[edit] Experiments show that conventional processor DVFS policy can achieve power reduction of embedded GPUs with reasonable performance degradation.[9] New directions for designing effective DVFS schedulers for heterogeneous systems are also being explored.[10] A heterogeneous CPU- GPU
GPU
architecture, GreenGPU[11] is presented which employs DVFS in a synchronized way, both for GPU
GPU
and CPU. Green GPU
GPU
is implemented using the CUDA framework on a real physical testbed with Nvidia GeForce GPUs and AMD
AMD
Phenom II CPUs. Experimentally it is shown that the Green GPU
GPU
achieves 21.04% average energy saving and outperforms several well-designed baselines. For the mainstream GPUs which are extensively used in all kinds of commercial and personal applications several DVFS techniques exist and are built into the GPUs alone, AMD PowerTune and AMD ZeroCore Power
AMD ZeroCore Power
are the two dynamic frequency scaling technologies for AMD
AMD
graphic cards. Practical tests showed that reclocking a Geforce
Geforce
GTX 480 can achieve a 28% lower power consumption while only decreasing performance by 1% for a given task.[12] Power Gating Techniques[edit] A lot of research has been done on the dynamic power reduction with the use of DVFS techniques. However, as technology continues to shrink, leakage power will become a dominant factor.[13] Power gating is a commonly used circuit technique to remove leakage by turning off the supply voltage of unused circuits. Power gating incurs energy overhead; therefore, unused circuits need to remain idle long enough to compensate this overheads. A novel micro-architectural technique[14] for run-time power-gating caches of GPUs saves leakage energy. Based on experiments on 16 different GPU
GPU
workloads, the average energy savings achieved by the proposed technique is 54%. Shaders are the most power hungry component of a GPU, a predictive shader shut down power gating technique[15] achieves up to 46% leakage reduction on shader processors. The Predictive Shader Shutdown technique exploits workload variation across frames to eliminate leakage in shader clusters. Another technique called Deferred Geometry Pipeline seeks to minimize leakage in fixed-function geometry units by utilizing an imbalance between geometry and fragment computation across batches which removes up to 57% of the leakage in the fixed-function geometry units. A simple time-out power gating method can be applied to non-shader execution units which eliminates 83.3% of the leakage in non-shader execution units on average. All the three techniques stated above incur negligible performance degradation, less than 1%.[16] See also[edit]

Energy portal

Constant Awake Mode CPU
CPU
power dissipation Low-power electronics Dynamic voltage scaling Dynamic frequency scaling Advanced power management
Advanced power management
(APM) Advanced Configuration and Power Interface (ACPI)

Hibernate Sleep

BatteryMAX (idle detection) 80 Plus Energy Star Energy Storage as a Service (ESaaS) Green computing pmset PowerTOP - diagnostic tool The Green Grid Sleep Proxy Service Standby power Thermal Design Power VESA Display Power Management Signaling (DPMS) Run-time estimation of system and sub-system level power consumption

References[edit]

^ "Office of Naval Research - Power Management Kit". ONR. Retrieved 2015-01-15.  ^ "A Survey of Methods for Analyzing and Improving GPU
GPU
Energy Efficiency", Mittal et al., ACM Computing
Computing
Surveys, 2014. ^ "A Survey of Architectural Techniques For Improving Cache Power Efficiency", S. Mittal, SUSCOM, 4(1), 33-43, 2014 ^ "A survey of architectural techniques for DRAM power management", S. Mittal, IJHPSA, 4(2), 110-119, 2012 ^ " AMD
AMD
PowerNow! Technology with optimized power management". AMD. Retrieved 2009-04-23.  ^ "IBM EnergyScale for POWER6 Processor-Based Systems". IBM. Retrieved 2009-04-23.  ^ " AMD
AMD
Cool'n'Quiet Technology Overview". AMD. Retrieved 2009-04-23.  ^ "What is GPU
GPU
computing". Nvidia.  ^ "Dynamic voltage and frequency scaling framework for low-power embedded GPUs", Daecheol You et al., Electronics Letters (Volume:48, Issue: 21 ), 2012. ^ "Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU", Rong Ge et al., 42nd International Conference on Parallel Processing Pages 826-833, 2013. ^ "GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures", Kai Ma et al., 41st International Conference on Parallel Processing Pages 48-57, 2012. ^ "Power and performance analysis of GPU-accelerated systems", Yuki Abe et al., USENIX conference on Power-Aware Computing
Computing
and Systems Pages 10-10, 2012. ^ "Design challenges of technology scaling", Borkar, S., Micro, IEEE (Volume:19 , Issue: 4 ), 1999. ^ "Run-time power-gating in caches of GPUs for leakage energy savings", Yue Wang et al., Design, Automation & Test in Europe Conference & Exhibition (DATE), 2012 ^ "A Predictive Shutdown Technique for GPU
GPU
Shader Processors", Po-Han Wang et al., Computer
Computer
Architecture Letters (Volume:8 , Issue: 1 ), 2009 ^ " Power gating strategies on GPUs", Po-Han Wang et al., ACM Transactions on Architecture and Code Optimization (TACO) Volume 8 Issue 3, 2011

External links[edit]

Energy Star
Energy Star
- Independent List of Products Energy Star
Energy Star
- Low Carbon IT Campaign Energy Consumption Calculator Research Bibliography on Power Management

v t e

CPU
CPU
technologies

Architecture

Turing machine Post–Turing machine Universal Turing machine Quantum Turing machine Belt machine Stack machine Register machine Counter machine Pointer machine Random access machine Random access stored program machine Finite-state machine Queue automaton Von Neumann Harvard (modified) Dataflow TTA Cellular Artificial neural network

Machine learning Deep learning Neural processing unit (NPU)

Convolutional neural network Load/store architecture Register memory architecture Endianness FIFO Zero-copy NUMA HUMA HSA Mobile computing Surface computing Wearable computing Heterogeneous computing Parallel computing Concurrent computing Distributed computing Cloud computing Amorphous computing Ubiquitous computing Fabric computing Cognitive computing Unconventional computing Hypercomputation Quantum computing Adiabatic quantum computing Linear optical quantum computing Reversible computing Reverse computation Reconfigurable computing Optical computing Ternary computer Analogous computing Mechanical computing Hybrid computing Digital computing DNA computing Peptide computing Chemical computing Organic computing Wetware computing Neuromorphic computing Symmetric multiprocessing
Symmetric multiprocessing
(SMP) Asymmetric multiprocessing
Asymmetric multiprocessing
(AMP) Cache hierarchy Memory hierarchy

ISA types

ASIP CISC RISC EDGE (TRIPS) VLIW (EPIC) MISC OISC NISC ZISC Comparison

ISAs

x86 z/Architecture ARM MIPS Power Architecture
Power Architecture
(PowerPC) SPARC Mill Itanium
Itanium
(IA-64) Alpha Prism SuperH V850 Clipper VAX Unicore PA-RISC MicroBlaze RISC-V

Word size

1-bit 2-bit 4-bit 8-bit 9-bit 10-bit 12-bit 15-bit 16-bit 18-bit 22-bit 24-bit 25-bit 26-bit 27-bit 31-bit 32-bit 33-bit 34-bit 36-bit 39-bit 40-bit 48-bit 50-bit 60-bit 64-bit 128-bit 256-bit 512-bit Variable

Execution

Instruction pipelining

Bubble Operand forwarding

Out-of-order execution

Register renaming

Speculative execution

Branch predictor Memory dependence prediction

Hazards

Parallel level

Bit

Bit-serial Word

Instruction Pipelining

Scalar Superscalar

Task

Thread Process

Data

Vector

Memory

Multithreading

Temporal Simultaneous (SMT) (Hyper-threading) Speculative (SpMT) Preemptive Cooperative Clustered Multi-Thread (CMT) Hardware scout

Flynn's taxonomy

SISD SIMD
SIMD
(SWAR) SIMT MISD MIMD

SPMD

Addressing mode

CPU
CPU
performance

Instructions per second (IPS) Instructions per clock (IPC) Cycles per instruction (CPI) Floating-point operations per second (FLOPS) Transactions per second (TPS) Synaptic Updates Per Second (SUPS) Performance per watt Orders of magnitude (computing) Cache performance measurement and metric

Core count

Single-core processor Multi-core processor Manycore processor

Types

Central processing unit
Central processing unit
(CPU) GPGPU AI accelerator Vision processing unit (VPU) Vector processor Barrel processor Stream processor Digital signal processor
Digital signal processor
(DSP) I/O processor/DMA controller Network processor Baseband processor Physics processing unit
Physics processing unit
(PPU) Coprocessor Secure cryptoprocessor ASIC FPGA FPOA CPLD Microcontroller Microprocessor Mobile processor Notebook processor Ultra-low-voltage processor Multi-core processor Manycore processor Tile processor Multi-chip module
Multi-chip module
(MCM) Chip stack multi-chip modules System on a chip
System on a chip
(SoC) Multiprocessor system-on-chip (MPSoC) Programmable System-on-Chip
System-on-Chip
(PSoC) Network on a chip (NoC)

Components

Execution unit (EU) Arithmetic logic unit
Arithmetic logic unit
(ALU) Address generation unit
Address generation unit
(AGU) Floating-point unit
Floating-point unit
(FPU) Load-store unit (LSU) Branch predictor Unified Reservation Station Barrel shifter Uncore Sum addressed decoder (SAD) Front-side bus Back-side bus Northbridge (computing) Southbridge (computing) Adder (electronics) Binary multiplier Binary decoder Address decoder Multiplexer Demultiplexer Registers Cache Memory management unit
Memory management unit
(MMU) Input–output memory management unit
Input–output memory management unit
(IOMMU) Integrated Memory Controller (IMC) Power Management Unit (PMU) Translation lookaside buffer
Translation lookaside buffer
(TLB) Stack engine Register file Processor register Hardware register Memory buffer register (MBR) Program counter Microcode
Microcode
ROM Datapath Control unit Instruction unit Re-order buffer Data buffer Write buffer Coprocessor Electronic switch Electronic circuit Integrated circuit Three-dimensional integrated circuit Boolean circuit Digital circuit Analog circuit Mixed-signal integrated circuit Power management integrated circuit Quantum circuit Logic gate

Combinational logic Sequential logic Emitter-coupled logic
Emitter-coupled logic
(ECL) Transistor–transistor logic
Transistor–transistor logic
(TTL) Glue logic

Quantum gate Gate array Counter (digital) Bus (computing) Semiconductor device Clock rate CPU
CPU
multiplier Vision chip Memristor

Power management

APM ACPI Dynamic frequency scaling Dynamic voltage scaling Clock gating

Hardware security

Non-executable memory (NX bit) Memory Protection Extensions (Intel MPX) Intel Secure Key Hardware restriction (firmware) Software Guard Extensions (Intel SGX) Trusted Execution Technology Trusted Platform Module
Trusted Platform Module
(TPM) Secure cryptoprocessor Hardware security module Hengzhi chip

Related

History of general-purpose CPUs

v t e

Computer
Computer
processor power management technologies

Standards

Advanced Configuration and Power Interface (ACPI) Advanced Power Management
Advanced Power Management
(APM)

Techniques

Dynamic frequency scaling Dynamic voltage scaling Clock gating

Implementations

Power Saving

AMD
AMD
Cool'n'Quiet (desktop) AMD
AMD
PowerNow! (laptop) Intel SpeedStep Transmeta LongRun VIA LongHaul

Performance

Intel Turbo Boost AMD
AMD
Turbo Core

Graphics

AMD
AMD
Power

.