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Open Cloud Computing

A Case for HPC

CRO NGI Day

Zagreb, Oct, 26th

Philippe Trautmann

HPC Business Development Manager

Global Education @ Research

(2)

Agenda

The Cloud

HPC and Cloud: any needs?

Cloud Computing from Sun

Getting Started

(3)

The Cloud

The illusion of

infinite computing

resources

The elimination of

an up-front

commitment

Pay for use of

computing

resources

(4)

What Does Cloud Mean?

“ A

fundamental shift in the computing paradigm

- Steve Ballmer, CEO Microsoft

The return of the mainframe, and the mainframe is a set of computers. You never visit

them, you never see them. But they're out there.”

- Eric Schmidt, CEO Google

“It's nothing more than a faddish term for the established concept of computers linked by

networks. A cloud is water vapour”

- Larry Ellison, CEO Oracle

You build your app, and you inherit our architecture”

- Marc Benioff, CEO SalesForce.com

“The Truth Is Rarely Pure And Never Simple”

(5)

Public

Business Models

Private

Hybrid

You don’t know

who else is on the

same server,

network or disk

that you are

You own the server,

network and disk,

and decide who

gets to run on it with

you

You own some

parts and are

sharing some

parts, though in a

(6)

Application Domains

Domains Drive Differences

in Hardware and Software Architecture

HPC

Intelligence

Medical

Analytics

Finance

Web

(7)

Faster time-to-market

Reduction of custom

software

Pay only for what you

use

Grow infrastructure

with business

Cloud Computing Layers

Applications offered on-demand over

the network (salesforce.com)

Basic storage and compute capabilities offered

as a service (Amazon web services)

Developer platform with built-in services

(Google App Engine)

Infrastructure as a Service

Platform as a Service

(8)

8

HPC market

requirements

(9)

HPC Market Overview

Server Revenue by IDC Competitive Segments

Segment Price Range

Supercomputer $500K and up $2.58 3.20% 1.50%

Division $250K - $500K $1.30 1.60% -0.70%

Department $100k - $250K $3.62 7.10% -0.04%

Workgroup <100K $1.73 1.90% -0.06%

2009

TAM $B (07 – 13)CAGR DOWN SIDECAGR

HP IBM Dell Other Sun

HP

IBM

DELL

Other

SUN

IDC Server Revenue by Vendor 2008

IDC Estimates that for every $ spent on Servers

An additional $.39 is spent on storage

An additional $.25 is spent on services

IDC HPC Application/Industry Forecast

Servers Storage Application Segment 2009 ($K) 2013 ($K) 2009 ($K) University Academic $1,800,235 $2,337,419 6.75% $571,344 16.27% Govt. Lab $1,425,431 $1,863,896 6.93% $433,087 12.33% Bio Sciences $1,217,297 $1,781,031 9.98% $652,271 18.57% CAE $952,761 $1,562,311 13.16% $455,087 12.96% Defense $871,585 $1,186,212 8.01% $414,288 11.80% EDA $613,729 $948,920 11.51% $173,687 4.94% DCC & Distribution $576,228 $835,046 9.72% $269,913 7.68% Geosciences & Geo Engineering $529,772 $807,039 11.10% $222,042 6.32% Weather $371,260 $545,329 10.09% $119,956 3.42% Economics /Financial $261,750 $421,115 12.62% $64,663 1.84% Chemical Engineering $223,468 $260,900 3.95% $88,262 2.51%

Other $182,756 $140,644 -6.34% $20,227 0.58%

Mechanical Design & Drafting $106,400 $98,205 -1.98% $27,568 0.78% Total Revenue $9,132,672 $12,788,067 4.10% $3,512,395 100.00%

CAGR

(10)

The Importance of HPC

Reduce costs and increase efficiency

Improve quality and be first to market

Make better and faster decisions

Applications becoming increasingly computationally

intensive

Required to run more and more of these

applications

Need to analyze more and more data

HPC

can solve these problems and is now a

required technology to stay competitive

(11)

The “P” in HPC

Technical limitations – system, storage, interconnect,

complexity

Exploding Data Requirements

Increasing fidelity of modeling and simulation

Instruments that spit out PetaBytes of Data

Requirement for collaborative research

Complexity of Use

Need reliable solutions that are easy to architect, deploy and

use

Space, power and cooling issues

(12)

Time to

Load Data

Time to Compute

Time to

Store

Data

2009

2011

You can only compute as fast as you can move the data

Exponential

Data Growth

Time to

Load Data

Time to

Store

Data

Time

to

Compute

(13)

Barriers to HPC:

I/O Bottlenecks – Application Enemy #1

• Prevents applications from scaling

• Leads to poor overall application performance

• Complex – CPU? Memory? Storage?

Interconnect? Application?

• Removing I/O Bottlenecks requires an

end-to-end approach

(14)

IDC: Cloud costs vs.DataCenter

£0.00

£5,000,000.00

£10,000,000.00

£15,000,000.00

£20,000,000.00

£25,000,000.00

£30,000,000.00

Start

up

cost

Year

1

Year

2

Year

3

Year

4

Year

5

Year

6

Year

7

Year

8

Year

9

Year

10

Data Centre

Cloud

In H2 2009, IDC analyzed the costs of running 100% of a typical

large businesses IT infrastructure in a DC versus the cloud:

After year 3,

cloud costs

exceeded the

DC

Final Score

DC: £15M

Cloud: £26M

Even with 3 year

refresh cycles of 30%,

DC remains much

cheaper

(15)

The Real Problems On The Horizon That

Will Make Or Break Cloud Services

Standards

Common standards on development, deployment, and

migration/transition

Ability for businesses to move a system from one cloud to another

– No Lock In

Differentiation

Different providers with different value propositions – Big vendors,

Telcos, Hosting Providers….

Specialization and the emergence of best of breed providers in

specific areas

Competition

Price competition and eco system competition

(16)

16

Cloud Computing

From Sun

(17)

Sun’s Strategy

Develop the core technologies for

Sun's Open Cloud Platform

Offer Services through Sun's public

cloud service – the Sun Cloud

Work with service providers and

enterprises to build their own clouds

Develop open standards

(18)

Cloud Architecture – Future

Partner and Build

User Apps and Services

Internet Accessible APIs and UIs

Servers

Storage

Network

Virtualized Datacenter Management Layer

Customer Web Site

Storage

Service

Queuing

Service

JavaEE

Service

etc.

Application Catalog,

Forums, Docs

Virtual Datacenter

Management Console

Accounting, Billing and Metering

Identity

Service

Database

Service

Compute

Service

(19)

Building Robust Sun Cloud Ecosystem

(20)

Initial Public Cloud Roadmap

Internal Alpha

Storage

Compute

Early Access

Storage

Compute

Update 1

Storage, Compute

Adds Identity, Queuing, Database services

Q1 2009

H2 2009

Q2 2009

Sun Open Cloud

Platform

Work with Customers on

Product Version of

Software in Public Cloud

(21)

21

Getting Started

(22)

Adopt Models & Standards

(23)

F

oc

us

H

er

e

Faster, Better, Cheaper, Reduced Scope, or Someone Else's Problem?

(24)

Consider Adoption Strategies

Test and

Development

Functional Offload

(Batch Processes –

TimesMachine)

Functional Offload

(Storage – SmugMug)

Augmentation

(Temporary Load – Animoto)

(25)

Profile Applications & Workloads

Suitable for cloud

Time based

Very parallel (i.e. batch)

Spiky traffic

Capital intensive

(especially startup)

Proof of Concept

Low utilization

Less deployment costs

High bandwidth costs /

high real estate

Not suitable for cloud

Vertically scaled applications

Consistent load levels

Latency sensitive

applications

Insecure applications

Hardware device dependent

(e.g. fax server, SNA

gateway)

ISV unsupported

Per CPU licensed

applications

(26)

Participate in the Development of

our Open Cloud APIs

Sign up for Early Access to Sun

Cloud Services

Become a Sun Cloud Partner

Let Sun experts help you take

advantage of Cloud Computing

http://sun.com/cloud

(27)

[email protected]

sun.com/hpc

References

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