∗ Okay, we still watch a video before starting the discussion about ‘Cloud Computing’
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What is Cloud Computing?
∗ Cloud Computing and Big Data are the definite consequence of the internet age!
∗ We start the discussion from ‘Cloud Computing’
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∗ What is Cloud Computing? ∗ We have different perspectives
from different sides ∗ According to wikipedia, "Cloud
computing is Internet-based ("Cloud") development and use of computer technology. "
Introduction to Cloud Computing
The NIST Cloud Definition Framework
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Community Cloud
Private Cloud
Public Cloud
Hybrid Clouds
Deployment Models
Service Models
Essential Characteristics
Common Characteristics
Software as a Service (SaaS)
Platform as a Service (PaaS)
Infrastructure as a Service (IaaS)
Resource Pooling
Broad Network Access Rapid Elasticity
Measured Service
On Demand Self-Service
Low Cost Software
Virtualization Service Orientation
Advanced Security
Homogeneity
Massive Scale Resilient Computing
Geographic Distribution
∗ A new business opportunity? ∗ Is it far beyond distributed/grid/cluster computing? ∗ Or, just a new term?
∗ Is it a new Holy Grail? ∗ Web 3.0, new web-scale problem?
∗ Social, Location, Mobile
What is Cloud Computing?
I don’t understand what we would do differently in the light of cloud computing other than changing the wording of some of our ads Oracle’s CEO Larry Ellison
The Rise of a New Era in IT
Mainframe
PC / Client-Server
Web Cloud
Each new era in computing brings a new application platform: for the Cloud era it is “PaaS”
COBOL
Unix Services
Application Servers
Platform as a Service
∗ Let’s turn to review the history of the IC industry ∗ Do you think why Fabless Design Houses
are so strong in the past 10+ years?
It is a new Era, but Is it a new business model?
Design Manufacturing
DFM
CHIP
HW/SW
FE TCAD
BE TCAD
Manuf. TCAD
SiVL Sigma C
DesignWare Connect. IP
VMM
Virtual Platform
CATS Proteus
Analog IP (Phys)
Test Chips
Formality
Saber SysStudio
Magellan DC Ultra SysVerilog
VCS NTB VIP
Test
Star RCXT
IC Compiler
PrimeTime
Hercules
Power
HSIM
HSPICE
NanoSim
Libraries Yield
Mgmt
PrimeYield
Systems
Today: Global IC Market Systems $1.26T Computers Communications Consumer Industrial Military…
Embedded SW $2.5B
IP $1.4B
Semiconductors $269.9B Micros, DSP Memory ASIC, ASSP Analog Discrete
Silicon Wafers $11.4B
Chips
Front-End Manufacturing $21.9B Lithography/Mask Making CMP equipment Ion Implanters Deposition Etching and Cleaning Other
Back-End Manufacturing $6.6B Assembly Equipment Assembly Inspect. Dicing Bonding Packaging Int. Assembly Sys Total Test
Foundry Wafers $20.9B
Masks* $3.3B
EDA
$4.0 B
2008 Data (*2006) Source: VLSI Research, Gartner, IC Insights, SEMI, Information Network, Synopsys Estimates
∗ Is ‘Cloud Computing’ far beyond distributed/grid/cluster computing?
∗ Is it also mature?
∗ 鑑古知今
Cloud -- Not Just a New Term?
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Technology Hierarchy 應用
Social Computing, Enterprise, ISV,…
程式語言 Web 2.0 介面, Mashups, Workflows, …
控制 Qos Neqotiation, Ddmission Control,
Pricing, SLA Management, Metering…
虛擬化 VM, VM management and Deployment
User Level
User-Level Middleware
Core Middleware
System Level
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Deployment models
Public cloud Community cloud
Hybrid cloud Private cloud
We talk about: Public Cloud - A cloud is available in pay-as- you-go to the general public
Utility Computing -- Pay as you go
∗ Hours purchased via cloud computing can be distributed non-uniformly in time
∗ Cloud computing offers economic benefits of elasticity and transference of risk
Utility Computing – the service being sold in public cloud Cloud Services = SaaS + Utility Computing
∗ No longer require the Large Capital ∗ Don’t concerned about Over-Provisioning or Under-
Provisioning for prediction ∗ 選課系統 ∗ Startup companies
∗ Companies with large batch-oriented tasks can be finish quickly ∗ More elasticity of resources
The spirit of ‘Pay as you go’
Example(Provision for peak load)
最高峰 :500servers 最低峰 :100servers 雲端需要24*300=7200(小時*伺服器) 傳統模式下需要500*24=12000(小時*伺服器)雲端可以節省約1.7倍的cost!!!
Example(Under-provision) Active user – People use the site regularly Defector – People abandon the sites Suppose 10% of active user become defector who receive poor service due to under-provision
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∗ The appearance of infinite computing resource is available to overcome load surges
∗ The elimination of an up-front commitment by cloud users ∗ The ability to pay for use of computing resources on a short
term ∗ Remember: 要喝牛奶,你不必買頭牛
Cloud can help
∗ 30,000,000 users ∗ Based on Amazon AWS ∗ Django web framework ∗ PostgreSQL database ∗ Memory cache by Redis ∗ Merged by Facebook
Famous new Companies
Quoted from http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances-dozens-of
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Cloud Cost
∗ 在矽谷每個月租server x元, 頻寬x元 在台灣每個月租server 0.5~1x元,頻寬30~40x元!! --- 翟本喬
∗ 在美國租伺服器,每台每月169~229美元,可是流量超出我的預期…最後我的信用卡額度每個月3萬美金(約90萬台幣)才夠用 --- 陳士駿
∗ 在台灣會更慘,每個月90萬美金(2700萬台幣)
∗ Is Cloud-Service really cheaper?? ∗ Depend on your age/finance situations, you rent or buy
houses
Price
∗ 1.Availability/Business Continuity
∗ Q: User/Organization worry about whether utility computing services will have adequate availability or company may even go out of business
∗ A:Multiple and different cloud computing providers
Top 10 Obstacles and Opportunities for Cloud Computing
∗ 2.Data Lock-In
∗ Q:The Storage API for cloud computing are still essentially proprietary, cannot easily extract by customers
∗ A: Standardize APIs ;Compatible SW to enable Surge of Hybird of Cloud Computing
Top 10 Obstacles and Opportunities for Cloud Computing
∗ 3.Data Confidentiality/Auditability
∗ Q: Cloud user face security threats both from outsides and insides the cloud Outside : any third-party , cloud vender
Inside : cloud user ∗ A: cloud user : virtualization ∗ cloud vender : user-level encryption ∗ any third-party : firewall
Top 10 Obstacles and Opportunities for Cloud Computing
∗ 4.Data Transfer Bottlenecks
∗ Q : The cost of data transfer is high and transfer rate ∗ is slow because data is in surprising size
∗ A: ship disks
Top 10 Obstacles and Opportunities for Cloud Computing
∗ 7.Bugs in large scale distributed systems
∗ Q:Bugs can’t appear in smaller configuration ,but appear in production data center
∗ A:Use distributed VMs
Top 10 Obstacles and Opportunities for Cloud Computing
∗ 10.Software Licensing
∗ Q : Cloud provisions pay more money
∗ A : Open source or pay-for-use license ∗ Why open source?? Cost issues in startup teams
Top 10 Obstacles and Opportunities for Cloud Computing
∗ The number of app download is more than 10 billion
Quoted from http://android-developers.blogspot.com/search/label/Android%20Market
Web-Scale Problems It is BIG DATA!
∗ Characteristics: ∗ Definitely data-intensive ∗ May also be processing
intensive ∗ Examples: ∗ Crawling, indexing,
searching, mining the Web ∗ Social Network ∗ Web 3.0 applications
∗ In 2007 the average was 5,000 tweets per day ∗ In 2008 that had grown to 300,000 ∗ In 2009 tweets per day averaged 2.5 million ∗ In 2010 that number was 35 million tweets per day ∗ In the month of March 2011 alone, 140 million tweets are
being sent on average per day.
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http://www.marketinggum.com/twitter-statistics-2011-updated-stats/
∗ Twitter is the top 8 website
50 Quoted from http://www.alexa.com/topsites
∗ Wayback Machine has 2 PB + 20 TB/month (2006) ∗ Google processes 20 PB a day (2008) ∗ “all words ever spoken by human beings” ~ 5 EB ∗ NOAA has ~1 PB climate data (2007) ∗ CERN’s LHC will generate 15 PB a year (2008)
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Web-Scale Problems It is BIG DATA!
640K ought to be enough for anybody.
http://archive.org/index.php
∗ We can capture the scale of 300GB, since we have a hard disk more than the size nowaday
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What is the scale of BigData?
∗ They cannot be solved by a set of machines ∗ Many machines? ∗ Distributed/grid/cluster computing?
∗ We need huge machines! ∗ Less-communication between computers ∗ Less-synchronization systems
For Big Data Analytics
∗ Play as a web-services to provide Relation Database functionalities
∗ Solve (2) Data Lock-In Issues
Third-party Cloud Services
∗ We have data and Computing Everywhere! ∗ New terms: M2M, Internet of Things
∗ The IT industry is growing but changing
∗ Software and Idea are more valuable than Hardware and Labor
∗ Small/Diverse/Open-Source Software is more beneficial
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They are the future
∗ Cross-discipline will be the best way to evolve with the trend
∗ Good to touch Data-Driven Sciences ∗ Data Mining
∗ Since Software is the king, welcome to join us ∗ 9:00~12:00 Thursday ∗ 4204@CSIE Building ∗ Many Talks about software or big data processing from
experts in software industries such as Google, Yahoo!, Synopsys, Trend Micro
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They are the future