Open Cloud Computing A Case for HPC CRO NGI Day Zagreb, Oct, 26th

Transcription

1 Open Cloud Computing A Case for HPC CRO NGI Day Zagreb, Oct, 26th Philippe Trautmann HPC Business Development Manager Global Research Sun Microsystems, Inc. 1

2 The Cloud HPC and Cloud: any needs? Cloud Computing from Sun Getting Started Agenda 2

3 The illusion of infinite computing resources The elimination of an up-front commitment Pay for use of computing resources The Cloud 3

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 -Oscar Wilde 4

5 Business Models Public 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 controlled way 5

6 Application Domains HPC Medical Intelligence Finance Analytics Web Domains Drive Differences in Hardware and Software Architecture 6

7 Cloud Computing Layers Software as a Service Applications offered on-demand over the network (salesforce.com) Faster time-to-market of custom PlatformReduction as a Service software Developer platform with built-in services (Google Apponly Engine) Pay for what you use as a Service Infrastructure Grow infrastructure Basic storage and compute capabilities offered with business as a service (Amazon web services) 7

8 HPC market requirements 8 8

9 HPC Market Overview IDC HPC Application/Industry Forecast Servers Application Segment University Academic Govt. Lab Bio Sciences CAE Defense EDA DCC & Distribution Geosciences & Geo Engineering Weather Economics /Financial Chemical Engineering Other Mechanical Design & Drafting Total Revenue 2009 ($K) $1,800,235 $1,425,431 $1,217,297 $952,761 $871,585 $613,729 $576,228 $529,772 $371,260 $261,750 $223,468 $182,756 $106,400 $9,132,672 Storage 2013 ($K) $2,337,419 $1,863,896 $1,781,031 $1,562,311 $1,186,212 $948,920 $835,046 $807,039 $545,329 $421,115 $260,900 $140,644 $98,205 $12,788,067 CAGR (07-13) 6.75% 6.93% 9.98% 13.16% 8.01% 11.51% 9.72% 11.10% 10.09% 12.62% 3.95% -6.34% -1.98% 4.10% 2009 ($K) % of Mkt $571, % $433, % $652, % $455, % $414, % $173, % $269, % $222, % $119, % $64, % $88, % $20, % $27, % $3,512, % IDC Server Revenue by Vendor 2008 HP IBM Dell Other Sun SUN Other HP DELL IBM IDC Estimates that for every $ spent on Servers An additional $.39 is spent on storage An additional $.25 is spent on services Server Revenue by IDC Competitive Segments Segment Supercomputer Division Department Workgroup Price Range $500K and up $250K - $500K $100k - $250K <100K 2009 TAM $B $2.58 $1.30 $3.62 $1.73 CAGR (07 13) 3.20% 1.60% 7.10% 1.90% DOWN SIDE CAGR 1.50% -0.70% -0.04% -0.06% 9

10 The Importance of HPC Organizations are Under Pressure 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 10

11 Limiting factors 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 11

12 Barriers to HPC: Data Access 2009 Time to Store Data Time to Compute Time to Load Data Exponential Data Growth 2011 Time to Compute Time to Store Data Time to Load Data You can only compute as fast as you can move the data 12

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-toend approach Is there a catch for Cloud computing here? 13

14 IDC: Cloud costs vs.datacenter In H2 2009, IDC analyzed the costs of running 100% of a typical large businesses IT infrastructure in a DC versus the cloud: 30,000, ,000, ,000, Even with 3 year refresh cycles of 30%, DC remains much cheaper Final Score DC: 15M Cloud: 26M Data Centre Cloud 15,000, ,000, After year 3, cloud costs exceeded the DC 5,000, Start Year Year Year Year Year Year Year Year Year Year up cost 14 14

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 No one dominant winner 15

16 Cloud Computing From Sun Cloud Architecture 16 16

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 Build partnerships and communities 17

18 Cloud Architecture Future User Apps and Services Customer Web Site Internet Accessible APIs and UIs Database Service Compute Service Queuing Service Identity Service Storage Service JavaEE Service etc. Virtual Datacenter Management Console Application Catalog, Forums, Docs Accounting, Billing and Metering Virtualized Datacenter Management Layer Servers Storage Network Partner and Build 18

19 Building Robust Sun Cloud Ecosystem Sun Cloud 19

20 Initial Public Cloud Roadmap Update 1 Storage, Compute Adds Identity, Queuing, Database services Early Access Storage Compute Internal Alpha Storage Compute Q Q H Sun Open Cloud Platform Work with Customers on Product Version of Software in Public Cloud 20

21 Getting Started 21 21

22 Adopt Models & Standards = 22

23 Focus Here Prepare your IT Service Management Faster, Better, Cheaper, Reduced Scope, or Someone Else's Problem? 23

24 Consider Adoption Strategies Test and Development Functional Offload (Batch Processes TimesMachine) Functional Offload (Storage SmugMug) Augmentation (Temporary Load Animoto) Web Service 24

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 25

26 Getting Started Today 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 26

27 THANK YOU! sun.com/hpc 27