Scheduling for Reduced CPU Energy

Size: px
Start display at page:

Download "Scheduling for Reduced CPU Energy"

Transcription

1 Scheduling for Reduced CPU Energy M. Weiser, B. Welch, A. Demers and S. Shenker Appears in "Proceedings of the First Symposium on Operating Systems Design and Implementation," Usenix Association, November 1994 Apresentado por Ricardo Carrano para Sistemas de Tempo Real e Embarcados IC / UFF

2 Abstract Introduces MIPJ Examines a class of methods to reduce MIPJ based on the dynamic control of system clock speed by the OS scheduler Question: What are the right scheduling algorithms for taking advantage of reduced clock-speed, especially in the presence of applications demanding ever more IPSs? Result: Adjusting clock speed at a fine grain, saves substantial CPU energy (with little impact on performance) Sistemas de Tempo Real e Embarcados 2

3 Outline An Energy Metric for CPUS Motivation The experiment Trace Data Assumptions and Simulations Three algorithms (OPT, FUTURE and PAST) Evaluating the Algorithms Conclusions Sistemas de Tempo Real e Embarcados 3

4 Motivation: components energy use Dominated by display and disk But CPU is significant Common approach (at the time): Power down when idle Proposed (new) approach: Minimize idle time Sistemas de Tempo Real e Embarcados 4

5 An Energy Metric for CPUs MIPJ: new metric for CPU energy performance MIPJ = MIPS/WATTS MIPS stands for any workload-per-time bench mark Examples MIPS W MIPJ: MIPS Alpha 40W MIPJ: 5 Laptops: Motorola MIPS/300mW: MIPJ: 20 Sistemas de Tempo Real e Embarcados 5

6 More recent data: Energy per Instruction Trends in Intel Microprocessors Grochowski and Annavaram Microarchitecture Research Lab Intel Corporation Core Duo and Pentium M reverse the trend towards ever-greater EPI (but the arrow still points up) ( ) improving IPC has emerged as the more energy-efficient of the two techniques. (as opposed to increasing frequency). Sistemas de Tempo Real e Embarcados 6

7 How to reduce MIPJ? Other things equal, MIPJ is unchanged by changes in clock speed. Reducing clock speed causes a linear reduction in energy consumption The two cancel But a reduced clock speed creates an opportunity for quadratic energy savings Clock speed reduced by n energy per cycle reduced by n 2. So, dynamic control of system clock speed by the OS scheduler do saves energy Reducing voltage, Reversible logic, Adiabatic logic Sistemas de Tempo Real e Embarcados 7

8 Adiabatic Logic Benjamin Gojman (August 8, 2004) As circuits get smaller and faster, their energy dissipation greatly increases a problem that adiabatic circuits promises to solves Adiabatic process total heat or energy in the system remains constant. Term given to low-power electronic circuits that implement reversible logic. CMOS technology dissipate energy as heat mostly when switching. There are two fundamental rules CMOS adiabatic circuits must follow never to turn on a transistor when there is a voltage difference between the drain and source. never to turn off a transistor that has current flowing through it. Sistemas de Tempo Real e Embarcados 8

9 The experiment Simulations over real traces Lengthen runtime of individually scheduled segments of the trace in order to eliminate idle time. The idea is to stretch runtime into idle times Sistemas de Tempo Real e Embarcados 9

10 The experiments: Trace Data Taken from UNIX stations Over periods up to several hours on a work day Workload includes SW devel., documentation, , simulation, etc Other traces taken during specific workload Sistemas de Tempo Real e Embarcados 10

11 The experiment: assumptions (1/2) No reordering of tasks Sleep events classified into hard and soft Disk request time are hard (non-deterministic) Keystrokes, for example, can be stretched No energy consumption when idle Energy/instructions in proportion to n 2 when running at speed n n varies between minimum relative speed and 1.0 (full speed) Sistemas de Tempo Real e Embarcados 11

12 The experiment: assumptions (2/2) No time to switch speeds Turning off due to power saving skipped/ignored Lower bound to practical speed (5V full speed): 0.2, 0.44 or , 2.2 and 3.3 V Speed adjusted linearly with voltage Sistemas de Tempo Real e Embarcados 12

13 Scheduling algorithms Three types of scheduling OPT: unbounded-delay, perfect-future FUTURE: bounded-delay, limited-future PAST: bounded-delay, limited-past Sistemas de Tempo Real e Embarcados 13

14 OPT Takes the entire trace Stretches all the runtimes to fill all the idle times Off periods (90% of idle times over 30s) not available for stretching Impractical future knowledge Undesirable large delays no regard to interactivity Sistemas de Tempo Real e Embarcados 14

15 FUTURE Like OPT but peers only a small window into the future Stretches runtime into idle time only within this window setting window size of 10 to 50ms interactive response will remain high Impractical: future knowledge Desirable: limited delay Sistemas de Tempo Real e Embarcados 15

16 PAST Practical version of FUTURE Looks a fixed window into the past Assumes the next will be like the previous The algorithm follows... Sistemas de Tempo Real e Embarcados 16

17 PAST algorithm Process previous window and computes: run_cycles number of non-idle CPU cycles idle_cycles idle CPU cycles, hard and soft. excess_cycles left over because we ran too slow. run_percent = run_cycles / (idle_cycles + run_cycles) Adjusts speed accordingly If excess_cycles > idle_cycles newspeed = 1.0 elseif run_percent > 0.7 newspeed = speed elseif run_percent < 0.5 newspeed = speed (0.6 run_percent) Sistemas de Tempo Real e Embarcados 17

18 Evaluating the Algorithms PAST beats FUTURE, because excess cycles are deferred Algorithms and Minimum speeds allowed Sistemas de Tempo Real e Embarcados 21

19 Penalty at 20ms Excess cycles built up Most intervals have no excess cycles Time it would take to execute them at full speed 20msec Sistemas de Tempo Real e Embarcados 22

20 Penalty at 2.2V The peak shifts right as the interval length increases Sistemas de Tempo Real e Embarcados 23

21 PAST (Min Volts, 20ms) Minimum speed does not always result in the minimum energy 2.2V almost as good as 1.0V Kestrel march 1 Sistemas de Tempo Real e Embarcados 24

22 PAST (2.2V vs. Interval) Longer adjustment periods result in more savings Sistemas de Tempo Real e Embarcados 26

23 Excess Cycles Lower minimum voltage more excess cycles Sistemas de Tempo Real e Embarcados 27

24 Longer interval more excess cycles Sistemas de Tempo Real e Embarcados 28

25 Conclusions (1/2) PAST, with a 50ms window, saves energy: up to 50% for conservative assumptions (3.3V) up to 70% for more aggressive assumptions (2.2V) Savings depends on the interval between speed adjustments. too fine: less power saved (CPU usage bursty). too coarse: excess cycles built up during a slow interval will adversely affect interactive response. interval of 20 or 30 milliseconds: good compromise: power savings vs interactive response. Sistemas de Tempo Real e Embarcados 29

26 Conclusions (2/2) Too low a min. speed less efficiency more excess cycles must speed up to catch up. If an effective way of predicting workload can be found, then significant power can be saved. adjusting the processor speed at a fine grain so it is just fast enough to accommodate the workload. The tortoise is more efficient than the hare: better to spread work out by reducing cycle time (and voltage) than to run the CPU at full speed for short bursts and then idle. But QoS is not actually taken into account Hard and soft idle cycles are no guarantee for RT systems Sistemas de Tempo Real e Embarcados 30

Amdahl's Law. Execution time new = ((1 f) + f/s) Execution time. S. Then:

Amdahl's Law. Execution time new = ((1 f) + f/s) Execution time. S. Then: Amdahl's Law Useful for evaluating the impact of a change. (A general observation.) Insight: Improving a feature cannot improve performance beyond the use of the feature Suppose we introduce a particular

More information

Power in Digital CMOS Circuits. Fruits of Scaling SpecInt 2000

Power in Digital CMOS Circuits. Fruits of Scaling SpecInt 2000 Power in Digital CMOS Circuits Mark Horowitz Computer Systems Laboratory Stanford University horowitz@stanford.edu Copyright 2004 by Mark Horowitz MAH 1 Fruits of Scaling SpecInt 2000 1000.00 100.00 10.00

More information

Dynamic I/O Power Management for Hard Real-time Systems 1

Dynamic I/O Power Management for Hard Real-time Systems 1 Dynamic I/O Power Management for Hard Real-time Systems 1 Vishnu Swaminathan y, Krishnendu Chakrabarty y and S. S. Iyengar z y Department of Electrical & Computer Engineering z Department of Computer Science

More information

Lecture 2: CMOS technology. Energy-aware computing

Lecture 2: CMOS technology. Energy-aware computing Energy-Aware Computing Lecture 2: CMOS technology Basic components Transistors Two types: NMOS, PMOS Wires (interconnect) Transistors as switches Gate Drain Source NMOS: When G is @ logic 1 (actually over

More information

MICROPROCESSOR REPORT. THE INSIDER S GUIDE TO MICROPROCESSOR HARDWARE

MICROPROCESSOR REPORT.   THE INSIDER S GUIDE TO MICROPROCESSOR HARDWARE MICROPROCESSOR www.mpronline.com REPORT THE INSIDER S GUIDE TO MICROPROCESSOR HARDWARE ENERGY COROLLARIES TO AMDAHL S LAW Analyzing the Interactions Between Parallel Execution and Energy Consumption By

More information

Che-Wei Chang Department of Computer Science and Information Engineering, Chang Gung University

Che-Wei Chang Department of Computer Science and Information Engineering, Chang Gung University Che-Wei Chang chewei@mail.cgu.edu.tw Department of Computer Science and Information Engineering, Chang Gung University } 2017/11/15 Midterm } 2017/11/22 Final Project Announcement 2 1. Introduction 2.

More information

Lecture 12: Energy and Power. James C. Hoe Department of ECE Carnegie Mellon University

Lecture 12: Energy and Power. James C. Hoe Department of ECE Carnegie Mellon University 18 447 Lecture 12: Energy and Power James C. Hoe Department of ECE Carnegie Mellon University 18 447 S18 L12 S1, James C. Hoe, CMU/ECE/CALCM, 2018 Housekeeping Your goal today a working understanding of

More information

Intro To Digital Logic

Intro To Digital Logic Intro To Digital Logic 1 Announcements... Project 2.2 out But delayed till after the midterm Midterm in a week Covers up to last lecture + next week's homework & lab Nick goes "H-Bomb of Justice" About

More information

CIS 371 Computer Organization and Design

CIS 371 Computer Organization and Design CIS 371 Computer Organization and Design Unit 13: Power & Energy Slides developed by Milo Mar0n & Amir Roth at the University of Pennsylvania with sources that included University of Wisconsin slides by

More information

Performance, Power & Energy. ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So

Performance, Power & Energy. ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So Performance, Power & Energy ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So Recall: Goal of this class Performance Reconfiguration Power/ Energy H. So, Sp10 Lecture 3 - ELEC8106/6102 2 PERFORMANCE EVALUATION

More information

ENERGY EFFICIENT TASK SCHEDULING OF SEND- RECEIVE TASK GRAPHS ON DISTRIBUTED MULTI- CORE PROCESSORS WITH SOFTWARE CONTROLLED DYNAMIC VOLTAGE SCALING

ENERGY EFFICIENT TASK SCHEDULING OF SEND- RECEIVE TASK GRAPHS ON DISTRIBUTED MULTI- CORE PROCESSORS WITH SOFTWARE CONTROLLED DYNAMIC VOLTAGE SCALING ENERGY EFFICIENT TASK SCHEDULING OF SEND- RECEIVE TASK GRAPHS ON DISTRIBUTED MULTI- CORE PROCESSORS WITH SOFTWARE CONTROLLED DYNAMIC VOLTAGE SCALING Abhishek Mishra and Anil Kumar Tripathi Department of

More information

PERFORMANCE METRICS. Mahdi Nazm Bojnordi. CS/ECE 6810: Computer Architecture. Assistant Professor School of Computing University of Utah

PERFORMANCE METRICS. Mahdi Nazm Bojnordi. CS/ECE 6810: Computer Architecture. Assistant Professor School of Computing University of Utah PERFORMANCE METRICS Mahdi Nazm Bojnordi Assistant Professor School of Computing University of Utah CS/ECE 6810: Computer Architecture Overview Announcement Jan. 17 th : Homework 1 release (due on Jan.

More information

CSE140L: Components and Design Techniques for Digital Systems Lab. Power Consumption in Digital Circuits. Pietro Mercati

CSE140L: Components and Design Techniques for Digital Systems Lab. Power Consumption in Digital Circuits. Pietro Mercati CSE140L: Components and Design Techniques for Digital Systems Lab Power Consumption in Digital Circuits Pietro Mercati 1 About the final Friday 09/02 at 11.30am in WLH2204 ~2hrs exam including (but not

More information

Performance Metrics & Architectural Adaptivity. ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So

Performance Metrics & Architectural Adaptivity. ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So Performance Metrics & Architectural Adaptivity ELEC8106/ELEC6102 Spring 2010 Hayden Kwok-Hay So What are the Options? Power Consumption Activity factor (amount of circuit switching) Load Capacitance (size

More information

Lecture 2: Metrics to Evaluate Systems

Lecture 2: Metrics to Evaluate Systems Lecture 2: Metrics to Evaluate Systems Topics: Metrics: power, reliability, cost, benchmark suites, performance equation, summarizing performance with AM, GM, HM Sign up for the class mailing list! Video

More information

Low power Architectures. Lecture #1:Introduction

Low power Architectures. Lecture #1:Introduction Low power Architectures Lecture #1:Introduction Dr. Avi Mendelson mendlson@ee.technion.ac.il Contributors: Ronny Ronen, Eli Savransky, Shekhar Borkar, Fred PollackP Technion, EE department Dr. Avi Mendelson,

More information

A Dynamic Real-time Scheduling Algorithm for Reduced Energy Consumption

A Dynamic Real-time Scheduling Algorithm for Reduced Energy Consumption A Dynamic Real-time Scheduling Algorithm for Reduced Energy Consumption Rohini Krishnapura, Steve Goddard, Ala Qadi Computer Science & Engineering University of Nebraska Lincoln Lincoln, NE 68588-0115

More information

Tradeoff between Reliability and Power Management

Tradeoff between Reliability and Power Management Tradeoff between Reliability and Power Management 9/1/2005 FORGE Lee, Kyoungwoo Contents 1. Overview of relationship between reliability and power management 2. Dakai Zhu, Rami Melhem and Daniel Moss e,

More information

An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms

An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms Sonal Saha Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfilment of the requirements

More information

CPU Consolidation versus Dynamic Voltage and Frequency Scaling in a Virtualized Multi-Core Server: Which is More Effective and When

CPU Consolidation versus Dynamic Voltage and Frequency Scaling in a Virtualized Multi-Core Server: Which is More Effective and When 1 CPU Consolidation versus Dynamic Voltage and Frequency Scaling in a Virtualized Multi-Core Server: Which is More Effective and When Inkwon Hwang, Student Member and Massoud Pedram, Fellow, IEEE Abstract

More information

TDDB68 Concurrent programming and operating systems. Lecture: CPU Scheduling II

TDDB68 Concurrent programming and operating systems. Lecture: CPU Scheduling II TDDB68 Concurrent programming and operating systems Lecture: CPU Scheduling II Mikael Asplund, Senior Lecturer Real-time Systems Laboratory Department of Computer and Information Science Copyright Notice:

More information

EECS 427 Lecture 11: Power and Energy Reading: EECS 427 F09 Lecture Reminders

EECS 427 Lecture 11: Power and Energy Reading: EECS 427 F09 Lecture Reminders EECS 47 Lecture 11: Power and Energy Reading: 5.55 [Adapted from Irwin and Narayanan] 1 Reminders CAD5 is due Wednesday 10/8 You can submit it by Thursday 10/9 at noon Lecture on 11/ will be taught by

More information

Origami: Folding Warps for Energy Efficient GPUs

Origami: Folding Warps for Energy Efficient GPUs Origami: Folding Warps for Energy Efficient GPUs Mohammad Abdel-Majeed*, Daniel Wong, Justin Huang and Murali Annavaram* * University of Southern alifornia University of alifornia, Riverside Stanford University

More information

TOWARD THE PLACEMENT OF POWER MANAGEMENT POINTS IN REAL-TIME APPLICATIONS

TOWARD THE PLACEMENT OF POWER MANAGEMENT POINTS IN REAL-TIME APPLICATIONS Chapter 1 TOWARD THE PLACEMENT OF POWER MANAGEMENT POINTS IN REAL-TIME APPLICATIONS Nevine AbouGhazaleh, Daniel Mossé, Bruce Childers, Rami Melhem Department of Computer Science University of Pittsburgh

More information

UC Santa Barbara. Operating Systems. Christopher Kruegel Department of Computer Science UC Santa Barbara

UC Santa Barbara. Operating Systems. Christopher Kruegel Department of Computer Science UC Santa Barbara Operating Systems Christopher Kruegel Department of Computer Science http://www.cs.ucsb.edu/~chris/ Many processes to execute, but one CPU OS time-multiplexes the CPU by operating context switching Between

More information

Introduction to CMOS VLSI Design (E158) Lecture 20: Low Power Design

Introduction to CMOS VLSI Design (E158) Lecture 20: Low Power Design Harris Introduction to CMOS VLSI Design (E158) Lecture 20: Low Power Design David Harris Harvey Mudd College David_Harris@hmc.edu Based on EE271 developed by Mark Horowitz, Stanford University MAH E158

More information

Where Does Power Go in CMOS?

Where Does Power Go in CMOS? Power Dissipation Where Does Power Go in CMOS? Dynamic Power Consumption Charging and Discharging Capacitors Short Circuit Currents Short Circuit Path between Supply Rails during Switching Leakage Leaking

More information

Optimizing Energy Consumption under Flow and Stretch Constraints

Optimizing Energy Consumption under Flow and Stretch Constraints Optimizing Energy Consumption under Flow and Stretch Constraints Zhi Zhang, Fei Li Department of Computer Science George Mason University {zzhang8, lifei}@cs.gmu.edu November 17, 2011 Contents 1 Motivation

More information

A Mathematical Solution to. by Utilizing Soft Edge Flip Flops

A Mathematical Solution to. by Utilizing Soft Edge Flip Flops A Mathematical Solution to Power Optimal Pipeline Design by Utilizing Soft Edge Flip Flops M. Ghasemazar, B. Amelifard, M. Pedram University of Southern California Department of Electrical Engineering

More information

CHAPTER 5 - PROCESS SCHEDULING

CHAPTER 5 - PROCESS SCHEDULING CHAPTER 5 - PROCESS SCHEDULING OBJECTIVES To introduce CPU scheduling, which is the basis for multiprogrammed operating systems To describe various CPU-scheduling algorithms To discuss evaluation criteria

More information

Thermal Scheduling SImulator for Chip Multiprocessors

Thermal Scheduling SImulator for Chip Multiprocessors TSIC: Thermal Scheduling SImulator for Chip Multiprocessors Kyriakos Stavrou Pedro Trancoso CASPER group Department of Computer Science University Of Cyprus The CASPER group: Computer Architecture System

More information

Lecture 6 Power Zhuo Feng. Z. Feng MTU EE4800 CMOS Digital IC Design & Analysis 2010

Lecture 6 Power Zhuo Feng. Z. Feng MTU EE4800 CMOS Digital IC Design & Analysis 2010 EE4800 CMOS Digital IC Design & Analysis Lecture 6 Power Zhuo Feng 6.1 Outline Power and Energy Dynamic Power Static Power 6.2 Power and Energy Power is drawn from a voltage source attached to the V DD

More information

ECE321 Electronics I

ECE321 Electronics I ECE321 Electronics I Lecture 1: Introduction to Digital Electronics Payman Zarkesh-Ha Office: ECE Bldg. 230B Office hours: Tuesday 2:00-3:00PM or by appointment E-mail: payman@ece.unm.edu Slide: 1 Textbook

More information

EE382 Processor Design Winter 1999 Chapter 2 Lectures Clocking and Pipelining

EE382 Processor Design Winter 1999 Chapter 2 Lectures Clocking and Pipelining Slide 1 EE382 Processor Design Winter 1999 Chapter 2 Lectures Clocking and Pipelining Slide 2 Topics Clocking Clock Parameters Latch Types Requirements for reliable clocking Pipelining Optimal pipelining

More information

Chapter 6: CPU Scheduling

Chapter 6: CPU Scheduling Chapter 6: CPU Scheduling Basic Concepts Scheduling Criteria Scheduling Algorithms Multiple-Processor Scheduling Real-Time Scheduling Algorithm Evaluation 6.1 Basic Concepts Maximum CPU utilization obtained

More information

Measurement & Performance

Measurement & Performance Measurement & Performance Timers Performance measures Time-based metrics Rate-based metrics Benchmarking Amdahl s law Topics 2 Page The Nature of Time real (i.e. wall clock) time = User Time: time spent

More information

Measurement & Performance

Measurement & Performance Measurement & Performance Topics Timers Performance measures Time-based metrics Rate-based metrics Benchmarking Amdahl s law 2 The Nature of Time real (i.e. wall clock) time = User Time: time spent executing

More information

Optimal Voltage Allocation Techniques for Dynamically Variable Voltage Processors

Optimal Voltage Allocation Techniques for Dynamically Variable Voltage Processors Optimal Allocation Techniques for Dynamically Variable Processors 9.2 Woo-Cheol Kwon CAE Center Samsung Electronics Co.,Ltd. San 24, Nongseo-Ri, Kiheung-Eup, Yongin-City, Kyounggi-Do, Korea Taewhan Kim

More information

Digital Integrated Circuits A Design Perspective

Digital Integrated Circuits A Design Perspective Digital Integrated Circuits Design Perspective Designing Combinational Logic Circuits Fuyuzhuo School of Microelectronics,SJTU Introduction Digital IC Dynamic Logic Introduction Digital IC 2 EE141 Dynamic

More information

CSE 380 Computer Operating Systems

CSE 380 Computer Operating Systems CSE 380 Computer Operating Systems Instructor: Insup Lee & Dianna Xu University of Pennsylvania, Fall 2003 Lecture Note 3: CPU Scheduling 1 CPU SCHEDULING q How can OS schedule the allocation of CPU cycles

More information

Evaluating Linear Regression for Temperature Modeling at the Core Level

Evaluating Linear Regression for Temperature Modeling at the Core Level Evaluating Linear Regression for Temperature Modeling at the Core Level Dan Upton and Kim Hazelwood University of Virginia ABSTRACT Temperature issues have become a first-order concern for modern computing

More information

Scheduling of Frame-based Embedded Systems with Rechargeable Batteries

Scheduling of Frame-based Embedded Systems with Rechargeable Batteries Scheduling of Frame-based Embedded Systems with Rechargeable Batteries André Allavena Computer Science Department Cornell University Ithaca, NY 14853 andre@cs.cornell.edu Daniel Mossé Department of Computer

More information

Last Lecture. Power Dissipation CMOS Scaling. EECS 141 S02 Lecture 8

Last Lecture. Power Dissipation CMOS Scaling. EECS 141 S02 Lecture 8 EECS 141 S02 Lecture 8 Power Dissipation CMOS Scaling Last Lecture CMOS Inverter loading Switching Performance Evaluation Design optimization Inverter Sizing 1 Today CMOS Inverter power dissipation» Dynamic»

More information

Energy Estimation for CPU-Events Dependent on Frequency Scaling and Clock Gating. Philip P. Moltmann

Energy Estimation for CPU-Events Dependent on Frequency Scaling and Clock Gating. Philip P. Moltmann Energy Estimation for CPU-Events Dependent on Frequency Scaling and Clock Gating Philip P. Moltmann System Architecture Group (IBDS Bellosa) Department of Computer Science University of Karlsruhe (TH)

More information

Performance, Power & Energy

Performance, Power & Energy Recall: Goal of this class Performance, Power & Energy ELE8106/ELE6102 Performance Reconfiguration Power/ Energy Spring 2010 Hayden Kwok-Hay So H. So, Sp10 Lecture 3 - ELE8106/6102 2 What is good performance?

More information

Dynamic Voltage and Frequency Scaling Under a Precise Energy Model Considering Variable and Fixed Components of the System Power Dissipation

Dynamic Voltage and Frequency Scaling Under a Precise Energy Model Considering Variable and Fixed Components of the System Power Dissipation Dynamic Voltage and Frequency Scaling Under a Precise Energy Model Csidering Variable and Fixed Compents of the System Power Dissipati Kihwan Choi W-bok Lee Ramakrishna Soma Massoud Pedram University of

More information

Impact of Scaling on The Effectiveness of Dynamic Power Reduction Schemes

Impact of Scaling on The Effectiveness of Dynamic Power Reduction Schemes Impact of Scaling on The Effectiveness of Dynamic Power Reduction Schemes D. Duarte Intel Corporation david.e.duarte@intel.com N. Vijaykrishnan, M.J. Irwin, H-S Kim Department of CSE, Penn State University

More information

Minimum Energy Consumption for Rate Monotonic Tasks

Minimum Energy Consumption for Rate Monotonic Tasks Minimum Energy Consumption for Rate Monotonic Tasks Saneev Baskiyar Chiao Ching Huang Tin-Yau Tam Abstract Limited battery power is a typical constraint in stand-alone embedded systems. One way to extend

More information

Intraprogram Dynamic Voltage Scaling: Bounding Opportunities with Analytic Modeling

Intraprogram Dynamic Voltage Scaling: Bounding Opportunities with Analytic Modeling Intraprogram Dynamic Voltage Scaling: Bounding Opportunities with Analytic Modeling FEN XIE, MARGARET MARTONOSI, and SHARAD MALIK Princeton University Dynamic voltage scaling (DVS) has become an important

More information

CMP N 301 Computer Architecture. Appendix C

CMP N 301 Computer Architecture. Appendix C CMP N 301 Computer Architecture Appendix C Outline Introduction Pipelining Hazards Pipelining Implementation Exception Handling Advanced Issues (Dynamic Scheduling, Out of order Issue, Superscalar, etc)

More information

Process Scheduling for RTS. RTS Scheduling Approach. Cyclic Executive Approach

Process Scheduling for RTS. RTS Scheduling Approach. Cyclic Executive Approach Process Scheduling for RTS Dr. Hugh Melvin, Dept. of IT, NUI,G RTS Scheduling Approach RTS typically control multiple parameters concurrently Eg. Flight Control System Speed, altitude, inclination etc..

More information

Skew-Tolerant Circuit Design

Skew-Tolerant Circuit Design Skew-Tolerant Circuit Design David Harris David_Harris@hmc.edu December, 2000 Harvey Mudd College Claremont, CA Outline Introduction Skew-Tolerant Circuits Traditional Domino Circuits Skew-Tolerant Domino

More information

Lecture 13: Sequential Circuits, FSM

Lecture 13: Sequential Circuits, FSM Lecture 13: Sequential Circuits, FSM Today s topics: Sequential circuits Finite state machines 1 Clocks A microprocessor is composed of many different circuits that are operating simultaneously if each

More information

DC-DC Converter-Aware Power Management for Battery-Operated Embedded Systems

DC-DC Converter-Aware Power Management for Battery-Operated Embedded Systems 53.2 Converter-Aware Power Management for Battery-Operated Embedded Systems Yongseok Choi and Naehyuck Chang School of Computer Science & Engineering Seoul National University Seoul, Korea naehyuck@snu.ac.kr

More information

Scheduling I. Today. Next Time. ! Introduction to scheduling! Classical algorithms. ! Advanced topics on scheduling

Scheduling I. Today. Next Time. ! Introduction to scheduling! Classical algorithms. ! Advanced topics on scheduling Scheduling I Today! Introduction to scheduling! Classical algorithms Next Time! Advanced topics on scheduling Scheduling out there! You are the manager of a supermarket (ok, things don t always turn out

More information

EE 466/586 VLSI Design. Partha Pande School of EECS Washington State University

EE 466/586 VLSI Design. Partha Pande School of EECS Washington State University EE 466/586 VLSI Design Partha Pande School of EECS Washington State University pande@eecs.wsu.edu Lecture 8 Power Dissipation in CMOS Gates Power in CMOS gates Dynamic Power Capacitance switching Crowbar

More information

L16: Power Dissipation in Digital Systems. L16: Spring 2007 Introductory Digital Systems Laboratory

L16: Power Dissipation in Digital Systems. L16: Spring 2007 Introductory Digital Systems Laboratory L16: Power Dissipation in Digital Systems 1 Problem #1: Power Dissipation/Heat Power (Watts) 100000 10000 1000 100 10 1 0.1 4004 80088080 8085 808686 386 486 Pentium proc 18KW 5KW 1.5KW 500W 1971 1974

More information

CMPEN 411 VLSI Digital Circuits Spring 2012 Lecture 17: Dynamic Sequential Circuits And Timing Issues

CMPEN 411 VLSI Digital Circuits Spring 2012 Lecture 17: Dynamic Sequential Circuits And Timing Issues CMPEN 411 VLSI Digital Circuits Spring 2012 Lecture 17: Dynamic Sequential Circuits And Timing Issues [Adapted from Rabaey s Digital Integrated Circuits, Second Edition, 2003 J. Rabaey, A. Chandrakasan,

More information

Quantitative Estimation of the Performance Delay with Propagation Effects in Disk Power Savings

Quantitative Estimation of the Performance Delay with Propagation Effects in Disk Power Savings Quantitative Estimation of the Performance Delay with Propagation Effects in Disk Power Savings Feng Yan 1, Xenia Mountrouidou 1, Alma Riska 2, and Evgenia Smirni 1 1 College of William and Mary, Williamsburg,

More information

Energy-Efficient Real-Time Task Scheduling in Multiprocessor DVS Systems

Energy-Efficient Real-Time Task Scheduling in Multiprocessor DVS Systems Energy-Efficient Real-Time Task Scheduling in Multiprocessor DVS Systems Jian-Jia Chen *, Chuan Yue Yang, Tei-Wei Kuo, and Chi-Sheng Shih Embedded Systems and Wireless Networking Lab. Department of Computer

More information

TDDI04, K. Arvidsson, IDA, Linköpings universitet CPU Scheduling. Overview: CPU Scheduling. [SGG7] Chapter 5. Basic Concepts.

TDDI04, K. Arvidsson, IDA, Linköpings universitet CPU Scheduling. Overview: CPU Scheduling. [SGG7] Chapter 5. Basic Concepts. TDDI4 Concurrent Programming, Operating Systems, and Real-time Operating Systems CPU Scheduling Overview: CPU Scheduling CPU bursts and I/O bursts Scheduling Criteria Scheduling Algorithms Multiprocessor

More information

The Elusive Metric for Low-Power Architecture Research

The Elusive Metric for Low-Power Architecture Research The Elusive Metric for Low-Power Architecture Research Hsien-Hsin Hsin Sean Lee Joshua B. Fryman A. Utku Diril Yuvraj S. Dhillon Center for Experimental Research in Computer Systems Georgia Institute of

More information

CSE140L: Components and Design Techniques for Digital Systems Lab. FSMs. Instructor: Mohsen Imani. Slides from Tajana Simunic Rosing

CSE140L: Components and Design Techniques for Digital Systems Lab. FSMs. Instructor: Mohsen Imani. Slides from Tajana Simunic Rosing CSE140L: Components and Design Techniques for Digital Systems Lab FSMs Instructor: Mohsen Imani Slides from Tajana Simunic Rosing Source: Vahid, Katz 1 FSM design example Moore vs. Mealy Remove one 1 from

More information

Energy-Constrained Scheduling for Weakly-Hard Real-Time Systems

Energy-Constrained Scheduling for Weakly-Hard Real-Time Systems Energy-Constrained Scheduling for Weakly-Hard Real-Time Systems Tarek A. AlEnawy and Hakan Aydin Computer Science Department George Mason University Fairfax, VA 23 {thassan1,aydin}@cs.gmu.edu Abstract

More information

Module 5: CPU Scheduling

Module 5: CPU Scheduling Module 5: CPU Scheduling Basic Concepts Scheduling Criteria Scheduling Algorithms Multiple-Processor Scheduling Real-Time Scheduling Algorithm Evaluation 5.1 Basic Concepts Maximum CPU utilization obtained

More information

A Novel Software Solution for Localized Thermal Problems

A Novel Software Solution for Localized Thermal Problems A Novel Software Solution for Localized Thermal Problems Sung Woo Chung 1,* and Kevin Skadron 2 1 Division of Computer and Communication Engineering, Korea University, Seoul 136-713, Korea swchung@korea.ac.kr

More information

Energy-efficient Mapping of Big Data Workflows under Deadline Constraints

Energy-efficient Mapping of Big Data Workflows under Deadline Constraints Energy-efficient Mapping of Big Data Workflows under Deadline Constraints Presenter: Tong Shu Authors: Tong Shu and Prof. Chase Q. Wu Big Data Center Department of Computer Science New Jersey Institute

More information

Implications on the Design

Implications on the Design Implications on the Design Ramon Canal NCD Master MIRI NCD Master MIRI 1 VLSI Basics Resistance: Capacity: Agenda Energy Consumption Static Dynamic Thermal maps Voltage Scaling Metrics NCD Master MIRI

More information

The "schedutil" frequency scaling governor. Giovanni Gherdovich October 7 th, 2018

The schedutil frequency scaling governor. Giovanni Gherdovich October 7 th, 2018 The "schedutil" frequency scaling governor Giovanni Gherdovich October 7 th, 2018 ggherdovich@suse.cz Agenda > schedutil intro > frequency scale invariance > PELT > util_est 2 Questions, anytime 3 terminology

More information

Process Scheduling. Process Scheduling. CPU and I/O Bursts. CPU - I/O Burst Cycle. Variations in Bursts. Histogram of CPU Burst Times

Process Scheduling. Process Scheduling. CPU and I/O Bursts. CPU - I/O Burst Cycle. Variations in Bursts. Histogram of CPU Burst Times Scheduling The objective of multiprogramming is to have some process running all the time The objective of timesharing is to have the switch between processes so frequently that users can interact with

More information

Floating Point Representation and Digital Logic. Lecture 11 CS301

Floating Point Representation and Digital Logic. Lecture 11 CS301 Floating Point Representation and Digital Logic Lecture 11 CS301 Administrative Daily Review of today s lecture w Due tomorrow (10/4) at 8am Lab #3 due Friday (9/7) 1:29pm HW #5 assigned w Due Monday 10/8

More information

A Control-Theoretic Approach to Dynamic Voltage Scheduling

A Control-Theoretic Approach to Dynamic Voltage Scheduling A Control-Theoretic Approach to Dynamic Voltage Scheduling Ankush Varma, Brinda Ganesh, Mainak Sen, Suchismita Roy Choudhury, Lakshmi Srinivasan, and Bruce Jacob Dept. of Electrical & Computer Engineering

More information

EE115C Winter 2017 Digital Electronic Circuits. Lecture 6: Power Consumption

EE115C Winter 2017 Digital Electronic Circuits. Lecture 6: Power Consumption EE115C Winter 2017 Digital Electronic Circuits Lecture 6: Power Consumption Four Key Design Metrics for Digital ICs Cost of ICs Reliability Speed Power EE115C Winter 2017 2 Power and Energy Challenges

More information

Efficient Power Management Schemes for Dual-Processor Fault-Tolerant Systems

Efficient Power Management Schemes for Dual-Processor Fault-Tolerant Systems Efficient Power Management Schemes for Dual-Processor Fault-Tolerant Systems Yifeng Guo, Dakai Zhu The University of Texas at San Antonio Hakan Aydin George Mason University Outline Background and Motivation

More information

1.7 Digital Logic Inverters

1.7 Digital Logic Inverters 11/5/2004 section 1_7 Digital nverters blank 1/2 1.7 Digital Logic nverters Reading Assignment: pp. 40-48 Consider the ideal digital logic inverter. Q: A: H: The deal nverter Q: A: H: Noise Margins H:

More information

EE241 - Spring 2001 Advanced Digital Integrated Circuits

EE241 - Spring 2001 Advanced Digital Integrated Circuits EE241 - Spring 21 Advanced Digital Integrated Circuits Lecture 12 Low Power Design Self-Resetting Logic Signals are pulses, not levels 1 Self-Resetting Logic Sense-Amplifying Logic Matsui, JSSC 12/94 2

More information

EE 5211 Analog Integrated Circuit Design. Hua Tang Fall 2012

EE 5211 Analog Integrated Circuit Design. Hua Tang Fall 2012 EE 5211 Analog Integrated Circuit Design Hua Tang Fall 2012 Today s topic: 1. Introduction to Analog IC 2. IC Manufacturing (Chapter 2) Introduction What is Integrated Circuit (IC) vs discrete circuits?

More information

Digital Integrated Circuits Designing Combinational Logic Circuits. Fuyuzhuo

Digital Integrated Circuits Designing Combinational Logic Circuits. Fuyuzhuo Digital Integrated Circuits Designing Combinational Logic Circuits Fuyuzhuo Introduction Digital IC Dynamic Logic Introduction Digital IC EE141 2 Dynamic logic outline Dynamic logic principle Dynamic logic

More information

CPU Scheduling. CPU Scheduler

CPU Scheduling. CPU Scheduler CPU Scheduling These slides are created by Dr. Huang of George Mason University. Students registered in Dr. Huang s courses at GMU can make a single machine readable copy and print a single copy of each

More information

Robust Optimization of a Chip Multiprocessor s Performance under Power and Thermal Constraints

Robust Optimization of a Chip Multiprocessor s Performance under Power and Thermal Constraints Robust Optimization of a Chip Multiprocessor s Performance under Power and Thermal Constraints Mohammad Ghasemazar, Hadi Goudarzi and Massoud Pedram University of Southern California Department of Electrical

More information

The Influence of Transistor Properties on Performance Metrics and the Energy-Efficiency of Parallel Computations

The Influence of Transistor Properties on Performance Metrics and the Energy-Efficiency of Parallel Computations RZ 3829 (# Z1208-001) 08/09/2012 Computer Science 5 pages Research Report The Influence of Transistor Properties on Performance Metrics and the Energy-Efficiency of Parallel Computations P. Stanley-Marbell

More information

Advances in processor, memory, and communication technologies

Advances in processor, memory, and communication technologies Discrete and continuous min-energy schedules for variable voltage processors Minming Li, Andrew C. Yao, and Frances F. Yao Department of Computer Sciences and Technology and Center for Advanced Study,

More information

Power-Saving Scheduling for Weakly Dynamic Voltage Scaling Devices

Power-Saving Scheduling for Weakly Dynamic Voltage Scaling Devices Power-Saving Scheduling for Weakly Dynamic Voltage Scaling Devices Jian-Jia Chen 1, Tei-Wei Kuo 2, and Hsueh-I Lu 2 1 Department of Computer Science and Information Engineering National Taiwan University,

More information

Scheduling I. Today Introduction to scheduling Classical algorithms. Next Time Advanced topics on scheduling

Scheduling I. Today Introduction to scheduling Classical algorithms. Next Time Advanced topics on scheduling Scheduling I Today Introduction to scheduling Classical algorithms Next Time Advanced topics on scheduling Scheduling out there You are the manager of a supermarket (ok, things don t always turn out the

More information

Status. Embedded System Design and Synthesis. Power and temperature Definitions. Acoustic phonons. Optic phonons

Status. Embedded System Design and Synthesis. Power and temperature Definitions. Acoustic phonons. Optic phonons Status http://robertdick.org/esds/ Office: EECS 2417-E Department of Electrical Engineering and Computer Science University of Michigan Specification, languages, and modeling Computational complexity,

More information

CycleTandem: Energy-Saving Scheduling for Real-Time Systems with Hardware Accelerators

CycleTandem: Energy-Saving Scheduling for Real-Time Systems with Hardware Accelerators CycleTandem: Energy-Saving Scheduling for Real-Time Systems with Hardware Accelerators Sandeep D souza and Ragunathan (Raj) Rajkumar Carnegie Mellon University High (Energy) Cost of Accelerators Modern-day

More information

Mark Redekopp, All rights reserved. Lecture 1 Slides. Intro Number Systems Logic Functions

Mark Redekopp, All rights reserved. Lecture 1 Slides. Intro Number Systems Logic Functions Lecture Slides Intro Number Systems Logic Functions EE 0 in Context EE 0 EE 20L Logic Design Fundamentals Logic Design, CAD Tools, Lab tools, Project EE 357 EE 457 Computer Architecture Using the logic

More information

MODULE 5 Chapter 7. Clocked Storage Elements

MODULE 5 Chapter 7. Clocked Storage Elements MODULE 5 Chapter 7 Clocked Storage Elements 3/9/2015 1 Outline Background Clocked Storage Elements Timing, terminology, classification Static CSEs Latches Registers Dynamic CSEs Latches Registers 3/9/2015

More information

Analytical Model for Sensor Placement on Microprocessors

Analytical Model for Sensor Placement on Microprocessors Analytical Model for Sensor Placement on Microprocessors Kyeong-Jae Lee, Kevin Skadron, and Wei Huang Departments of Computer Science, and Electrical and Computer Engineering University of Virginia kl2z@alumni.virginia.edu,

More information

Computation Offloading Strategy Optimization with Multiple Heterogeneous Servers in Mobile Edge Computing

Computation Offloading Strategy Optimization with Multiple Heterogeneous Servers in Mobile Edge Computing IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING VOL XX NO YY MONTH 019 1 Computation Offloading Strategy Optimization with Multiple Heterogeneous Servers in Mobile Edge Computing Keqin Li Fellow IEEE Abstract

More information

EEC 216 Lecture #3: Power Estimation, Interconnect, & Architecture. Rajeevan Amirtharajah University of California, Davis

EEC 216 Lecture #3: Power Estimation, Interconnect, & Architecture. Rajeevan Amirtharajah University of California, Davis EEC 216 Lecture #3: Power Estimation, Interconnect, & Architecture Rajeevan Amirtharajah University of California, Davis Outline Announcements Review: PDP, EDP, Intersignal Correlations, Glitching, Top

More information

ICS 233 Computer Architecture & Assembly Language

ICS 233 Computer Architecture & Assembly Language ICS 233 Computer Architecture & Assembly Language Assignment 6 Solution 1. Identify all of the RAW data dependencies in the following code. Which dependencies are data hazards that will be resolved by

More information

Alternative Timing in Digital Logic. George G. Conover

Alternative Timing in Digital Logic. George G. Conover Alternative Timing in Digital Logic by George G. Conover A thesis submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Master of Science Auburn,

More information

Timing Driven Power Gating in High-Level Synthesis

Timing Driven Power Gating in High-Level Synthesis Timing Driven Power Gating in High-Level Synthesis Shih-Hsu Huang and Chun-Hua Cheng Department of Electronic Engineering Chung Yuan Christian University, Taiwan Outline Introduction Motivation Our Approach

More information

Lecture 34: Portable Systems Technology Background Professor Randy H. Katz Computer Science 252 Fall 1995

Lecture 34: Portable Systems Technology Background Professor Randy H. Katz Computer Science 252 Fall 1995 Lecture 34: Portable Systems Technology Background Professor Randy H. Katz Computer Science 252 Fall 1995 RHK.F95 1 Technology Trends: Microprocessor Capacity 100000000 10000000 Pentium Transistors 1000000

More information

Leakage Minimization Using Self Sensing and Thermal Management

Leakage Minimization Using Self Sensing and Thermal Management Leakage Minimization Using Self Sensing and Thermal Management Alireza Vahdatpour Computer Science Department University of California, Los Angeles alireza@cs.ucla.edu Miodrag Potkonjak Computer Science

More information

Variation-Resistant Dynamic Power Optimization for VLSI Circuits

Variation-Resistant Dynamic Power Optimization for VLSI Circuits Process-Variation Variation-Resistant Dynamic Power Optimization for VLSI Circuits Fei Hu Department of ECE Auburn University, AL 36849 Ph.D. Dissertation Committee: Dr. Vishwani D. Agrawal Dr. Foster

More information

Online Energy-Aware I/O Device Scheduling for Hard Real-Time Systems with Shared Resources

Online Energy-Aware I/O Device Scheduling for Hard Real-Time Systems with Shared Resources Online Energy-Aware I/O Device Scheduling for Hard Real-Time Systems with Shared Resources Abstract The challenge in conserving energy in embedded real-time systems is to reduce power consumption while

More information

An Efficient Energy-Optimal Device-Scheduling Algorithm for Hard Real-Time Systems

An Efficient Energy-Optimal Device-Scheduling Algorithm for Hard Real-Time Systems An Efficient Energy-Optimal Device-Scheduling Algorithm for Hard Real-Time Systems S. Chakravarthula 2 S.S. Iyengar* Microsoft, srinivac@microsoft.com Louisiana State University, iyengar@bit.csc.lsu.edu

More information

Speed Modulation in Energy-Aware Real-Time Systems

Speed Modulation in Energy-Aware Real-Time Systems Speed Modulation in Energy-Aware Real-Time Systems Enrico Bini Scuola Superiore S. Anna, Italy e.bini@sssup.it Giorgio Buttazzo University of Pavia, Italy buttazzo@unipv.it Giuseppe Lipari Scuola Superiore

More information