Green Computing Omer Rana [email protected]

Green Computing

Omer [email protected]

The Need

Bill St. Arnaud (CANARIE, Inc)

Impact of ICT Industry


Virtualization Techniques


Virtual Machine Monitors (IBM 1960s)

A thin software layer that sits between hardware and the operating system— virtualizing and

managing all hardware resources

IBM Mainframe

IBM VM/370

CMS MVS CMS CMS

App App App App

Ed Bugnion, VMWare

Old idea from the 1960s

• IBM VM/370 – A VMM for IBM mainframe– Multiple OS environments on expensive hardware– Desirable when few machine around

• Popular research idea in 1960s and 1970s– Entire conferences on virtual machine monitor– Hardware/VMM/OS designed together

• Interest died out in the 1980s and 1990s.– Hardware got cheap– Operating systems got more more powerful (e.g multi-

user)

Ed Bugnion, VMWare

A return to Virtual Machines

• Disco: Stanford research project (1996-):– Run commodity OSes on scalable multiprocessors– Focus on high-end: NUMA, MIPS, IRIX

• Hardware has changed:– Cheap, diverse, graphical user interface– Designed without virtualization in mind

• System Software has changed: – Extremely complex– Advanced networking protocols– But even today :

• Not always multi-user• With limitations, incompatibilities, …

Ed Bugnion, VMWare

The Problem Today

Intel Architecture

Operating System

Ed Bugnion, VMWare

The VMware Solution

Intel Architecture

Operating System

Operating System

Intel Architecture

Ed Bugnion, VMWare

VMware™ MultipleWorlds™ Technology

A thin software layer that sits between Intel hardware and the operating system— virtualizing and managing all hardware

resources

Intel Architecture

VMware MultipleWorlds

Win2000

WinNT Linux Win

2000

App App App App

Ed Bugnion, VMWare

MultipleWorlds Technology

A world is an application execution environment with its own operating system

World

Intel Architecture

VMware MultipleWorlds

Win2000

WinNT Linux Win

2000

App App App App

Ed Bugnion, VMWare

Virtual Hardware

Floppy Disks

Parallel Ports Serial/Com Ports

Ethernet

Keyboard

Mouse

Monitor(VMM)

IDE Controller SCSI Controller

Sound Card

Ed Bugnion, VMWare

Attributes of MultipleWorlds Technology

• Software compatibility– Runs pretty much all software

• Low overheads/High performance– Near “raw” machine performance

• Complete isolation– Total data isolation between virtual machines

• Encapsulation– Virtual machines are not tied to physical machines

• Resource management

Ed Bugnion, VMWare

Hosted VMware Architecture

VMware achieves both near-native execution speed and broad device support by transparently switching* between Host Mode and VMM Mode.

Guest OS Applications

Guest Operating System

Host OS Apps

Host OS

PC HardwareDisks Memory CPUNIC

VMware App Virtual Machine

VMware Driver Virtual Machine Monitor

Host Mode VMM Mode

VMware, acting as an application, uses the host to access other devices such as the hard disk, floppy, or network card

The VMware Virtual machine monitor allows each guest OS to directly access the processor (direct execution)

*VMware typically switches modes 1000 times per second

Ed Bugnion, VMWare

Hosted VMM Architecture• Advantages:

– Installs and runs like an application– Portable – host OS does I/O access– Coexists with applications running on the host

• Limits:– Subject to Host OS:

• Resource management decisions• OS failures

• Usenix 2001 paper: J. Sugerman, G. Venkitachalam and B.-H. Lim, “Virtualizing I/O on VMware

Workstation’s Hosted Architecture”.

Ed Bugnion, VMWare

Virtualizing a Network Interface

Host OS

PC HardwarePhysical NIC

VMApp

VMDriver

Guest OS

VMM

Phy

sica

l Eth

erne

t

NIC Driver

NIC Driver

Virtual Bridge

Virtual Network Hub

Ed Bugnion, VMWare

The rise of data centers

• Single place for hosting servers and data• ISP’s now take machines hosted at data

centers• Run by large companies – like BT• Manage

– Power– Computation + Data– Cooling systems– Systems Admin + Network Admin

Data Centre in Tokyo From:Satoshi Matsuoka

http://www.attokyo.co.jp/eng/facility.html

Martin J. Levy (Tier1 Research) and Josh Snowhorn (Terremark)



Requirements• Power an important design constraint:

– Electricity costs– Heat dissipation

• Two key options in clusters – enable scaling of:– Operating frequency (square relation)– Supply voltage (cubic relation)

• Balance QoS requirements – e.g.fraction of workload to process locally – with power management

From: Salim Hariri, Mazin Yousif

From: Justin Moore, Ratnesh Sharma, Rocky Shih, Jeff Chase, Chandrakant Patel, Partha Ranganathan (HP Labs)


The case for power management in HPC

• Power/energy consumption a critical issue– Energy = Heat; Heat dissipation is costly

– Limited power supply

– Non-trivial amount of money

• Consequence– Performance limited by available power

– Fewer nodes can operate concurrently

• Opportunity: bottlenecks– Bottleneck component limits performance of other components

– Reduce power of some components, not overall performance

• Today, CPU is:– Major power consumer (~100W),

– Rarely bottleneck and

– Scalable in power/performance (frequency & voltage)

Power/performance“gears”

Is CPU scaling a win?

• Two reasons:1. Frequency and voltage scaling

Performance reduction less than

Power reduction

2. Application throughputThroughput reduction less than

Performance reduction

• Assumptions– CPU large power consumer– CPU driver– Diminishing throughput gains

performance (freq)

pow

er

ap

plic

ati

on t

hro

ug

hput

performance (freq)

(1)

(2)

CPU powerP = ½ CVf2

AMD Athlon-64

• x86 ISA• 64-bit technology• Hypertransport technology – fast memory bus• Performance

– Slower clock frequency– Shorter pipeline (12 vs. 20)– SPEC2K results

• 2GHz AMD-64 is comparable to 2.8GHz P4• P4 better on average by 10% & 30% (INT & FP)

• Frequency and voltage scaling– 2000 – 800 MHz– 1.5 – 1.1 Volts

From: Vincent W. Freeh (NCSU)

LMBench results

• LMBench– Benchmarking suite

– Low-level, micro data

• Test each “gear”

GearFrequency (Mhz)

Voltage

0 2000 1.5

1 1800 1.4

2 1600 1.3

3 1400 1.2

4 1200 1.1

6 800 0.9


Operating system functions


Communication


The problem• Peak power limit, P

– Rack power– Room/utility– Heat dissipation

• Static solution, number of servers is– N = P/Pmax

– Where Pmax maximum power of individual node

• Problem– Peak power > average power (Pmax > Paverage)

– Does not use all power – N * (Pmax - Paverage) unused

– Under performs – performance proportional to N– Power consumption is not predictable


Safe over provisioning in a cluster• Allocate and manage power among M > N nodes

– Pick M > N• Eg, M = P/Paverage

– MPmax > P

– Plimit = P/M

• Goal– Use more power, safely under limit– Reduce power (& peak CPU performance) of individual nodes– Increase overall application performance

time

pow

er Pmax

Paverage

P(t)

time

pow

er

PlimitPaverage

P(t)

Pmax


Safe over provisioning in a cluster

• Benefits– Less “unused” power/energy– More efficient power use

• More performance under same power limitation – Let P be performance

– Then more performance means: MP * > NP– Or P */ P > N/M or P */ P > Plimit/Pmax

time

pow

er Pmax

Paverage

P(t)

time

pow

er

PlimitPaverage

P(t)

Pmax

unusedenergy


When is this a win?

• When P */ P > N/M

or P */ P > Plimit/Pmax

In words:

power reduction more than

performance reduction

• Two reasons:1. Frequency and voltage scaling

2. Application throughput

performance (freq)

pow

er

ap

plic

ati

on t

hro

ug

hput

P * / P

< P av

erag

e/P m

ax

P * / P

> P av

erag

e/P m

ax

performance (freq)

(1)

(2)


Feedback-directed, adaptive power control

• Uses feedback to control power/energy consumption– Given power goal

– Monitor energy consumption

– Adjust power/performance of CPU

• Several policies– Average power

– Maximum power

– Energy efficiency: select slowest gear (g) such that


A more holistic approach: Managing a Data Center


CRAC: Computer Room Air Conditioningunits


Location of Cooling Unitssix CRAC units are serving 1000 servers, consuming 270

KW of power out of a total capacity of 600 KW

http://blogs.zdnet.com/BTL/?p=4022






From:Satoshi Matsuoka




From:

Satoshi Matsuoka


Green Computing Omer Rana [email protected]

Documents

seconded bugnion

g multiusered bugnion

applicationportable

irix hardware

intel hardware

arnaud canarie

vmware workstations

guest os applicationsguest