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Dan Reed [email protected] Multicore and Scalable Computing Strategist Managing Director, Data Center Futures

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Page 1: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

Dan [email protected]

Multicore and Scalable Computing StrategistManaging Director, Data Center Futures

Page 2: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Not the financial markets …

It’s that other sound …

The pull of commercial economicsManycore processors and accelerators

Software as a service and cloud computing

Page 3: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Think aboutDisks

FLASH

PCM

and the future

Good

Not Good

Page 4: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Double the number of cores instead of speed

No, at least without major innovationSequential code

Lack of parallel algorithms

Difficult programming

Few abstractions

Parallelism will change the computing landscape

If existing applications cannot use parallelismNew applications and systems will arise

Software plus services

Mobile computing

4

Page 5: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

5 5

Page 6: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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When applications are hostedEven sequential ones are embarrassingly parallel

Few dependencies among users

Moore’s benefits accrue to platform owner2x processors →

½ servers (+ ½ power, space, cooling …)

Or 2x service at the same cost

Tradeoffs not entirely one-sided due tolatency, bandwidth, privacy, off-line considerations

capital investment, security, programming problems

6

Page 7: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

7 Source: Dennis Gannon

OS

Virtualization

Parallel

Frameworks

GFS, BigTable,

MapReduce

Amazon S3/EC2

Hadoop

Hadoop over

EC3

AppEngine

cohesive

caroline

Astoria

Microsoft

Mesh

RightScale, GigaSpaces,

Elastra, 3Tera

What Goes Here?

Software as a

Service

Spanned by three points, each defining an approachExploit parallelism, Ease deployment, Provide service access

Page 8: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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All answers must be complete, backed by rigorous mathematical, scientific and business analyses. Each incorrect response will be penalized $5B (U.S.) and loss of turn.

Q1: Compare and contrast two possible designs for an international network of data centers for web 2.0 applications that optimize energy, performance, reliability, total cost of ownership and time to market.

Q2: Repeat Q1, but for a workload of (choose one) financial services, scientific and technical applications, or rich multimedia.

Page 9: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

www.azure.com

Page 10: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Massive commodity servers

Energy intensive infrastructure

Cooling inefficiencies

Environmental issues

Expensive UPS support

Enterprise TCP/IP networks

Long deployment timesConstruction and integration

Diverse services and SLAs

Explosive growthdemand and expectations

Page 11: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Cooling technologiesOperating points, phase change, liquid, …

New packaging technologiesOptoelectronics, memory stacking, …

New storage models/algorithmsDisks are not part of the future

Locality-aware algorithmsThe speed of light is pretty slow

Programming modelsEffective scale-invariant abstractions

Intelligent power managementAdaptation and power down

System adaptation and integrationReliability and power as first class objects

Page 12: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Belady, C., “In the Data Center, Power and Cooling Costs More than IT

Equipment it Supports”, Electronics Cooling Magazine (February 2007)

Source: Mike Manos/Christian Belady

Page 13: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

Assumptions

Facility: ~$200M for SMALL 15 MW facility (15-year amortization)

Servers: ~$2K/each, roughly 50,000 (3-year amortization)

Commercial power: ~$0.07/kWhr

On-site security/administration: 15 people @ ~$100K/year

Source: James Hamilton

$2,984,653

$1,700,025

$1,328,040

Servers

Infrastructure

Power

Monthly Costs

3 year server and 15 year infrastructure amortization

=PMT(5%/12,12*3,50000*2000,0,1)

=PMT(5%/12,12*15,200000000,0,1)-(100000/12*15)

=15,000,000/1000*1.7*0.07*24*31

• Observations

• $3M/month from charges related to power

• Power costs rising and server costs declining

Page 14: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Measures of data center infrastructure efficiency

Power Usage EffectivenessPUE = (Total Facility Power)/(IT Equipment Power)

Data Center Infrastructure EfficiencyDCiE = (IT Equipment Power)/(Total Facility Power) * 100%

Advanced Data Centers

Source: James Hamilton

Page 15: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Page 16: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Environmental responsibilityManaging under the 100 MW envelope

Adaptive systems management

Provisioning 25,000 serversHardware: at most one week after delivery

Software: at most a few hours

Resilience during a blackout/disasterData center failure

Service rollover for 20M customers

Programming the entire data centerPower, environmentals, provisioning

Component tracking, resilience, …

Page 17: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Processors

Storage

Networks

Packaging

Software

On-chip

FLASH

PCMLow power

Virtualization

Optical Interconnect

Multicore

Heterogeneity

Optics

Distributed routing

Non-TCP/IP

Chip stacking

Modularity

Liquid cooling

Over-provisioned

Introspection

Tier-splitting

Adaptation

Resilience

Page 18: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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It’s experiences, not devicesMultimodal interfaces

phone (both smart and stupid), netbook

laptop/desktop, TV, Surface, this room

We will interact using all of these devices … … often many in one session.

The browser is so 1990s

Adaptive tier splitting will be necessaryAt different times, different parts of the experiences …

… will run in the client and other times in the data center

Page 19: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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You walk into a meeting …… but you don’t recognize everybody

Your “SenseCam” phone automaticallylocates faces

extracts features

contacts data center

The face is compared to cloud data sources

It is recognized and a summary is generatedReturned by audio, text and/or imagry

Page 20: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Data center temperature zonesThey’re not chiseled in stone

Operate at >90F insteadPerhaps accept more component failures

But, this is not necessarily true

Aggressively embrace airside economizationAmbient air, with minimal conditioning

Recognize the power of alternative coolingLiquid, phase change, …

Page 21: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Service Level Agreements (SLAs)Typically written by lawyers

Not necessarily translatable into delivered service

Internal and external

ExamplesReliability (downtime)

Data integrity (probability of loss)

Security and privacy

Power and performance (many axes)

One possible approach for SLA and power controlReal-time measurement

Closed loop adaptive control

Page 22: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

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Liquid cooled or resilient air

DC power, single voltage

Custom hardware designMinimalist and new technologies

Over-provisioned for component failure

Flat, non-IP network addressing

Integrated instrumentation and control

Dynamic, adaptive system software

Page 23: Dan Reed reed@microsoft.com Multicore and Scalable Computing … › CS › html › SC08ExascalePowerWorkshop... · 2010-11-02 · rigorous mathematical, scientific and business

© 2008 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it

should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.

MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.