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Driving Towards Cloud 2015:
A Technology Vision to Meet the Demands
of Cloud Computing Tomorrow
Steve Pawlowski
Intel Senior Fellow
CTO, Datacenter and Connected Systems Group
GM, Datacenter and Connected Systems Pathfinding
Cloud Computing Today
                                                              On Anything
    More Visual Content




                                                          With More Flexibility
   On the Move
     Delivered               With Unanswered
Independent of time            Questions –
     or place                     • Secure?
                           • Reliable & Available?
                             • Standards Ready?
                                                           From Some Place That
                          • If yes, who ensures it?       I Don’t Have to Manage




                                                      But Connects Me to Everything
Security and Privacy Is the
                     Biggest Obstacle
 High Risk Threats
 • Well resourced, motivated cyber warriors
                                                                                  • Do you know where
 • Aggressive and Pervasive                                                         your data is?
 • Referred to as Advanced Persistent Threat
                                                                                  • Who can see it?
 Medium Risk Threats
 • Criminals to steal identity and money                                          • Who can modify it
 • Varying technical sophistication                                                 without a trace?

                                                                                  • Who can aggregate,
 Low Risk Threats                                                                   summarize, and
 • Internet Pollution                                                               embed it for purposes
 • Threats against every user                                                       other than yours?


Threat Categorization from ISIMC Guidelines for Secure Use of Cloud Computing V0:10
Energy Efficiency Is A Big Issue

                            2006: Data Centers
                            account for 1.5% of
                            total US Energy
                            Consumption




                          US Environmental Protection Agency Report on
                       Server and Data Center Energy Efficiency – Aug 2007


Efficient Data Center Energy Use                    Power Breakdown in a Server Platform
Think About Energy Efficiency
                        Differently
                         Grid

                     Distribution                           Water /     On Site         Energy
                                                            Carbon     Generation     Storage and
                         Facility                         (WUE/ CUE)                   Recycling

        PUE         Rack and Row Level   Infrastructure
Optimization          Infrastructure       Efficiency
                                             (PUE)
                       Server Power                         Power
                          Supply                           Managed     Proportional   Autonomous
                                                           Servers/    Data Center    Power Aware
                      Fans and Cooling
                                                            Racks

                       Motherboard/VRs

                             Package
                                           Energy Efficient Compute, Network, and Storage
                                 Die
                                Gates       2010           TODAY         2015           2020
               Sizes are illustrative



               Focus All the Way From “Grid to Gate”
But Enough Factors
Indicate that
Transformation to Cloud
Computing is Inevitable
Surge In Devices, Users, and
        Social Networking
                                                                          Mobile Internet

2.5 Billion
 Connected
   Users

                                 Devices/Users
  by 2015



>10 Billion
 Connected
 Devices By
   2015




       Source: Gérald Santucci, Head of Unit European Commission DG INFSO 20 Years of ICT Revolution:
                                   The Unceasing ‘Grail Quest’ , March 2009
                                         Cisco Visual Networking Index
Surge in Storage

                                       Storage Capacity Shipped
“More video uploaded to
 YouTube in the past 2
                                                          670%
 months than if ABC, CBS
 and NBC had been airing                                  Growth
 new content 24/365 since
 1948.”


                            Exabytes
— Gartner

“Big Data last 5 years:
 800% growth; 80%
 unstructured  effective
 tiering needed.”
— Gartner
Surge in Sensors
• Downloaded Apps Require Sensors
• ~1B GPS, ~900M Accel, ~600M Compass,
  ~450M Gyros by 2014
Surge in Video Traffic

Mobile Traffic Today                                             2015 Mobile Traffic




    40%                                                             66%
                                   ~40x
    Video                                                           Video

   90 PB/month
    7M paid video
     subscribers
                                                                3600 PB/month
                                                              700M paid video subscribers


        Source: Gérald Santucci, Head of Unit European Commission DG INFSO 20 Years of ICT Revolution:
                                    The Unceasing ‘Grail Quest’ , March 2009
                                          Cisco Visual Networking Index
Along With the Cloud’s Key
      Characteristics


      Elasticity

    Self Service

  Pay As You Go
So, What are the
Key Technical Areas
to Focus On?
Creating a Strong Foundation For
            Cloud Computing
 Match WL With Platform                     Big Data            Client Aware
     and Automate                         and Analytics          Computing


       No “The” WL in the Cloud          Future Computing      Not Just Centralized
 Embrace Mixes of Different Platforms      dominated by        Computing
  specialized for different classes of        continuous
             applications                       ingest,         Adaptively distribute
                                           integration, and     functionality among
   Automate to maximize efficiency &     analytics of large,
robustness as cloud scales – across HW,                         DC, Local Servers, and
                                          growing, and live     Edge Devices
      SW, and Problem Diagnosis                  data




While Keeping A Focus On Security At All Times
Match Workload With the Platform




                                   Integrate
Embrace Heterogeneity        New Memory Technologies

 Explore & extend range of    Explore how cloud apps can
   apps for platforms by           exploit new NVM
   overcoming OS limits,         technologies such as
    memory limits, and           Restive Memories to
    scalability issues in      overcome memory scaling
  specialized platforms of              issues
   heterogeneous nodes
The Focus Areas of Automation




Resource Scheduling   Software Correctness
 & Task Placement         & Productivity     Problem Diagnosis

Devise mechanisms     Automated tools for        Explore new
  and policies to      software upgrade         techniques for
 maximize energy         management,         diagnosing problems
    efficiency,       runtime correctness    at cloud complexity
   interference          checking, and             and scale
 avoidance, data          programmer
  availability and        productivity
      locality
Develop Methods to Quantify
            and Measure Usage
100%                                              • Customer workloads vary in
 90%                                                their infrastructure
 80%                                                demands: Typically:
 70%
                                                    Memory Utilization, Storage
 60%
 50%                                                IO, Network Throughput
 40%
 30%                                              • Current measurement
 20%                                                metric for Cloud Providers –
 10%
                                                    Number of Systems and
  0%
                                                    Time Used

                                                  • The Future: HW/SW co-
                                                    designed solutions to
                                                    monitor data for better
My billing   System billing   Libraries billing
                                                    scheduling & metering
So, What Does Big Data Look Like?
  An Example: The Semantic Web
      Main Stream Web

   Links to Resource       Links to                                  Web of Data
   Resource              Resource

  Links to                  Links to
              Resource
                                                      Computers Understand the Meaning
   Resource              Resource                     of Data On the Web – See the “Big
              Links to
                                                                   Picture”
        Semantic Web
                                                         Requires Graph Databases for
Has Manual     Software      Requires                  Geospatial and Temporal Search of
   Document                Library
                                                               Semantic Stream
   Author
              Person
         Address   Image
                                                       Evolving New Topics and Linguistic
      Place           Image                            Differences Make This Challenging


        Big Data is - Diverse, No Schema, Uncurated,
             Inconsistent Syntax and Semantics1
                                        1   Amplab – Dr. Patterson
Towards Efficient Frameworks for
                Big Data
                                                    14
• Popular current big data
                                                    12




                                  Slowdown Factor
  frameworks very inefficient
                                                    10
  – 3-13x slower after
                                                    8
    optimization
                                                    6
• Bunch of reasons why                              4
  – Artifacts of implementation                     2
  – Costs for desired features                      0
  – Unexpected I/O effects                               MapReduce MapReduce   Hadoop     MapReduce   Hadoop
                                                           Grep     TeraSort   TeraSort    PetaSort   PetaSort



   Frameworks for Advanced                                    Characterization & Better
  Machine Learning Algorithms                              Programming for Big Data Apps

    Focus on selective iteration and                         Focus on areas such as processing of
  exploitation of dependencies among                           data from the web, social network
    data-items in the data set being                         interactions, malware analysis, video
                analyzed                                        image processing, and HPC apps
The Storage Challenges With Big Data

        Persistent Data
        What needs to be stored and for how long?




        Data Organization
        • Many-to-One Network Issue:
          Multiple simultaneous reads to pick up every stripe
        • Energy Efficiency Issues:
          Servers need to be powered on all the time
Clients Must Be Cloud Aware and
              Vice Versa
 • Edge devices will be directly involved in
   many “cloud” activities
     –May even form clouds of their own
 • Bridge to physical world: Edge devices bring
   sensors, actuators, “context” to the cloud

    Cloud Assisted Mobile                  Wide Area Replication,
    Client Computations                 Consistency, and Deduplication
Enable applications whose execution      Address edge connectivity issues by
 spans client devices, local servers,   creating new ways to eliminate wasted
            and the cloud                   bandwidth and reduce latency
Balancing Compute & Client
                      Side Analytics
                                                         18,000                                     3,000,000
                                                         16,000




                                       GB Transfer/Day




                                                                                                                 Monitored Cores
                                                                                                    2,500,000
                                                         14,000
                                                         12,000                                     2,000,000
                                                         10,000
                                                                                                    1,500,000
                                                           8,000
                                                           6,000                                    1,000,000
                                                           4,000
                                                                                                    500,000
                                                           2,000
                                                                0                                   0
                                                                    2011 2012 2013 2014 2015 2016

                                                         Total Devices    Daily Raw Data   Daily Data Transfer
                                                                          Transfer (GB)    w/Client Side Analytics (GB)
  Source: Intel Cloud Builders Guide




• Leveraging local resources           • Monitored Cores and monitored
  reduces the data center                data from servers in data centers
  workload and associated                increases at a steady pace
  network traffic                      • Significant analytics required to
• Increases the VDI scalability          manage, make sense, and take
  and enhanced quality of service        action
  for end users                        • Client Side Analytics – the only
                                         alternative
More Unknown Than Known Out There
          Predict – But Find a Way to Recover




Prevent        the Security & Trust Infractions Prevent


                                                          Detect

Detect        the Security & Trust Infractions   Miss
                                                                   Recover

                                                           Miss
Recover         quickly and gracefully from the Security & Trust
Infractions
The Future is a World of Many
              Clouds
• The Cloud – while still evolving – enables
  many possibilities
• Challenges in Cloud Computing has so far
  mostly kept it to social networks; Security
  and Privacy tops the list
• Three Key Focus Areas:
 1) Match WL with the Platform & Automate
 2) Big Data & Analytics
 3) Client Aware Computing
Legal Disclaimer
•   INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL PRODUCTS. NO LICENSE, EXPRESS
    OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS
    DOCUMENT. EXCEPT AS PROVIDED IN INTEL'S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL
    ASSUMES NO LIABILITY WHATSOEVER AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO
    SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A
    PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER
    INTELLECTUAL PROPERTY RIGHT.
•   UNLESS OTHERWISE AGREED IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED
    FOR ANY APPLICATION IN WHICH THE FAILURE OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE
    PERSONAL INJURY OR DEATH MAY OCCUR.
•   Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not
    rely on the absence or characteristics of any features or instructions marked "reserved" or "undefined". Intel
    reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities
    arising from future changes to them. The information here is subject to change without notice. Do not finalize a
    design with this information.
•   The products described in this document may contain design defects or errors known as errata which may cause the
    product to deviate from published specifications. Current characterized errata are available on request.
•   Contact your local Intel sales office or your distributor to obtain the latest specifications and before placing your
    product order.
•   Copies of documents which have an order number and are referenced in this document, or other Intel literature,
    may be obtained by calling 1-800-548-4725, or go to: http://www.intel.com/design/literature.htm.
•   Software and workloads used in performance tests may have been optimized for performance only on Intel
    microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer
    systems, components, software, operations and functions. Any change to any of those factors may cause the
    results to vary. You should consult other information and performance tests to assist you in fully evaluating your
    contemplated purchases, including the performance of that product when combined with other products.
•   Intel processor numbers are not a measure of performance. Processor numbers differentiate features within each
    processor family, not across different processor families. Go to: http://www.intel.com/products/processor_number.
•   Intel product plans in this presentation do not constitute Intel plan of record product roadmaps. Please contact your
    Intel representative to obtain Intel's current plan of record product roadmaps.
•   Intel, Sponsors of Tomorrow and the Intel logo are trademarks of Intel Corporation in the United States and other
    countries.
•   *Other names and brands may be claimed as the property of others.
•   Copyright ©2011 Intel Corporation.
Risk Factors
The above statements and any others in this document that refer to plans and expectations for the second quarter, the year and the
future are forward-looking statements that involve a number of risks and uncertainties. Words such as “anticipates,” “expects,”
“intends,” “plans,” “believes,” “seeks,” “estimates,” “may,” “will,” “should,” and their variations identify forward-looking statements.
Statements that refer to or are based on projections, uncertain events or assumptions also identify forward-looking statements. Many
factors could affect Intel’s actual results, and variances from Intel’s current expectations regarding such factors could cause actual
results to differ materially from those expressed in these forward-looking statements. Intel presently considers the following to be
the important factors that could cause actual results to differ materially from the company’s expectations. Demand could be different
from Intel's expectations due to factors including changes in business and economic conditions, including supply constraints and
other disruptions affecting customers; customer acceptance of Intel’s and competitors’ products; changes in customer order patterns
including order cancellations; and changes in the level of inventory at customers. Potential disruptions in the high technology supply
chain resulting from the recent disaster in Japan could cause customer demand to be different from Intel’s expectations. Intel
operates in intensely competitive industries that are characterized by a high percentage of costs that are fixed or difficult to reduce in
the short term and product demand that is highly variable and difficult to forecast. Revenue and the gross margin percentage are
affected by the timing of Intel product introductions and the demand for and market acceptance of Intel's products; actions taken by
Intel's competitors, including product offerings and introductions, marketing programs and pricing pressures and Intel’s response to
such actions; and Intel’s ability to respond quickly to technological developments and to incorporate new features into its products.
The gross margin percentage could vary significantly from expectations based on capacity utilization; variations in inventory
valuation, including variations related to the timing of qualifying products for sale; changes in revenue levels; product mix and
pricing; the timing and execution of the manufacturing ramp and associated costs; start-up costs; excess or obsolete inventory;
changes in unit costs; defects or disruptions in the supply of materials or resources; product manufacturing quality/yields; and
impairments of long-lived assets, including manufacturing, assembly/test and intangible assets. Expenses, particularly certain
marketing and compensation expenses, as well as restructuring and asset impairment charges, vary depending on the level of
demand for Intel's products and the level of revenue and profits. The majority of Intel’s non-marketable equity investment portfolio
balance is concentrated in companies in the flash memory market segment, and declines in this market segment or changes in
management’s plans with respect to Intel’s investments in this market segment could result in significant impairment charges,
impacting restructuring charges as well as gains/losses on equity investments and interest and other. Intel's results could be affected
by adverse economic, social, political and physical/infrastructure conditions in countries where Intel, its customers or its suppliers
operate, including military conflict and other security risks, natural disasters, infrastructure disruptions, health concerns and
fluctuations in currency exchange rates. Intel’s results could be affected by the timing of closing of acquisitions and divestitures.
Intel's results could be affected by adverse effects associated with product defects and errata (deviations from published
specifications), and by litigation or regulatory matters involving intellectual property, stockholder, consumer, antitrust and other
issues, such as the litigation and regulatory matters described in Intel's SEC reports. An unfavorable ruling could include monetary
damages or an injunction prohibiting us from manufacturing or selling one or more products, precluding particular business practices,
impacting Intel’s ability to design its products, or requiring other remedies such as compulsory licensing of intellectual property. A
detailed discussion of these and other factors that could affect Intel’s results is included in Intel’s SEC filings, including the report on
Form 10-Q for the quarter ended April 2, 2011.

Rev. 5/9/11

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Driving Towards Cloud 2015: A Technology Vision to Meet the Demands of Cloud Computing Tomorrow

  • 1. Driving Towards Cloud 2015: A Technology Vision to Meet the Demands of Cloud Computing Tomorrow Steve Pawlowski Intel Senior Fellow CTO, Datacenter and Connected Systems Group GM, Datacenter and Connected Systems Pathfinding
  • 2. Cloud Computing Today On Anything More Visual Content With More Flexibility On the Move Delivered With Unanswered Independent of time Questions – or place • Secure? • Reliable & Available? • Standards Ready? From Some Place That • If yes, who ensures it? I Don’t Have to Manage But Connects Me to Everything
  • 3. Security and Privacy Is the Biggest Obstacle High Risk Threats • Well resourced, motivated cyber warriors • Do you know where • Aggressive and Pervasive your data is? • Referred to as Advanced Persistent Threat • Who can see it? Medium Risk Threats • Criminals to steal identity and money • Who can modify it • Varying technical sophistication without a trace? • Who can aggregate, Low Risk Threats summarize, and • Internet Pollution embed it for purposes • Threats against every user other than yours? Threat Categorization from ISIMC Guidelines for Secure Use of Cloud Computing V0:10
  • 4. Energy Efficiency Is A Big Issue 2006: Data Centers account for 1.5% of total US Energy Consumption US Environmental Protection Agency Report on Server and Data Center Energy Efficiency – Aug 2007 Efficient Data Center Energy Use Power Breakdown in a Server Platform
  • 5. Think About Energy Efficiency Differently Grid Distribution Water / On Site Energy Carbon Generation Storage and Facility (WUE/ CUE) Recycling PUE Rack and Row Level Infrastructure Optimization Infrastructure Efficiency (PUE) Server Power Power Supply Managed Proportional Autonomous Servers/ Data Center Power Aware Fans and Cooling Racks Motherboard/VRs Package Energy Efficient Compute, Network, and Storage Die Gates 2010 TODAY 2015 2020 Sizes are illustrative Focus All the Way From “Grid to Gate”
  • 6. But Enough Factors Indicate that Transformation to Cloud Computing is Inevitable
  • 7. Surge In Devices, Users, and Social Networking Mobile Internet 2.5 Billion Connected Users Devices/Users by 2015 >10 Billion Connected Devices By 2015 Source: Gérald Santucci, Head of Unit European Commission DG INFSO 20 Years of ICT Revolution: The Unceasing ‘Grail Quest’ , March 2009 Cisco Visual Networking Index
  • 8. Surge in Storage Storage Capacity Shipped “More video uploaded to YouTube in the past 2 670% months than if ABC, CBS and NBC had been airing Growth new content 24/365 since 1948.” Exabytes — Gartner “Big Data last 5 years: 800% growth; 80% unstructured  effective tiering needed.” — Gartner
  • 9. Surge in Sensors • Downloaded Apps Require Sensors • ~1B GPS, ~900M Accel, ~600M Compass, ~450M Gyros by 2014
  • 10. Surge in Video Traffic Mobile Traffic Today 2015 Mobile Traffic 40% 66% ~40x Video Video 90 PB/month 7M paid video subscribers 3600 PB/month 700M paid video subscribers Source: Gérald Santucci, Head of Unit European Commission DG INFSO 20 Years of ICT Revolution: The Unceasing ‘Grail Quest’ , March 2009 Cisco Visual Networking Index
  • 11. Along With the Cloud’s Key Characteristics Elasticity Self Service Pay As You Go
  • 12. So, What are the Key Technical Areas to Focus On?
  • 13. Creating a Strong Foundation For Cloud Computing Match WL With Platform Big Data Client Aware and Automate and Analytics Computing  No “The” WL in the Cloud Future Computing Not Just Centralized  Embrace Mixes of Different Platforms dominated by Computing specialized for different classes of continuous applications ingest, Adaptively distribute integration, and functionality among  Automate to maximize efficiency & analytics of large, robustness as cloud scales – across HW, DC, Local Servers, and growing, and live Edge Devices SW, and Problem Diagnosis data While Keeping A Focus On Security At All Times
  • 14. Match Workload With the Platform Integrate Embrace Heterogeneity New Memory Technologies Explore & extend range of Explore how cloud apps can apps for platforms by exploit new NVM overcoming OS limits, technologies such as memory limits, and Restive Memories to scalability issues in overcome memory scaling specialized platforms of issues heterogeneous nodes
  • 15. The Focus Areas of Automation Resource Scheduling Software Correctness & Task Placement & Productivity Problem Diagnosis Devise mechanisms Automated tools for Explore new and policies to software upgrade techniques for maximize energy management, diagnosing problems efficiency, runtime correctness at cloud complexity interference checking, and and scale avoidance, data programmer availability and productivity locality
  • 16. Develop Methods to Quantify and Measure Usage 100% • Customer workloads vary in 90% their infrastructure 80% demands: Typically: 70% Memory Utilization, Storage 60% 50% IO, Network Throughput 40% 30% • Current measurement 20% metric for Cloud Providers – 10% Number of Systems and 0% Time Used • The Future: HW/SW co- designed solutions to monitor data for better My billing System billing Libraries billing scheduling & metering
  • 17. So, What Does Big Data Look Like? An Example: The Semantic Web Main Stream Web Links to Resource Links to Web of Data Resource Resource Links to Links to Resource Computers Understand the Meaning Resource Resource of Data On the Web – See the “Big Links to Picture” Semantic Web Requires Graph Databases for Has Manual Software Requires Geospatial and Temporal Search of Document Library Semantic Stream Author Person Address Image Evolving New Topics and Linguistic Place Image Differences Make This Challenging Big Data is - Diverse, No Schema, Uncurated, Inconsistent Syntax and Semantics1 1 Amplab – Dr. Patterson
  • 18. Towards Efficient Frameworks for Big Data 14 • Popular current big data 12 Slowdown Factor frameworks very inefficient 10 – 3-13x slower after 8 optimization 6 • Bunch of reasons why 4 – Artifacts of implementation 2 – Costs for desired features 0 – Unexpected I/O effects MapReduce MapReduce Hadoop MapReduce Hadoop Grep TeraSort TeraSort PetaSort PetaSort Frameworks for Advanced Characterization & Better Machine Learning Algorithms Programming for Big Data Apps Focus on selective iteration and Focus on areas such as processing of exploitation of dependencies among data from the web, social network data-items in the data set being interactions, malware analysis, video analyzed image processing, and HPC apps
  • 19. The Storage Challenges With Big Data Persistent Data What needs to be stored and for how long? Data Organization • Many-to-One Network Issue: Multiple simultaneous reads to pick up every stripe • Energy Efficiency Issues: Servers need to be powered on all the time
  • 20. Clients Must Be Cloud Aware and Vice Versa • Edge devices will be directly involved in many “cloud” activities –May even form clouds of their own • Bridge to physical world: Edge devices bring sensors, actuators, “context” to the cloud Cloud Assisted Mobile Wide Area Replication, Client Computations Consistency, and Deduplication Enable applications whose execution Address edge connectivity issues by spans client devices, local servers, creating new ways to eliminate wasted and the cloud bandwidth and reduce latency
  • 21. Balancing Compute & Client Side Analytics 18,000 3,000,000 16,000 GB Transfer/Day Monitored Cores 2,500,000 14,000 12,000 2,000,000 10,000 1,500,000 8,000 6,000 1,000,000 4,000 500,000 2,000 0 0 2011 2012 2013 2014 2015 2016 Total Devices Daily Raw Data Daily Data Transfer Transfer (GB) w/Client Side Analytics (GB) Source: Intel Cloud Builders Guide • Leveraging local resources • Monitored Cores and monitored reduces the data center data from servers in data centers workload and associated increases at a steady pace network traffic • Significant analytics required to • Increases the VDI scalability manage, make sense, and take and enhanced quality of service action for end users • Client Side Analytics – the only alternative
  • 22. More Unknown Than Known Out There Predict – But Find a Way to Recover Prevent the Security & Trust Infractions Prevent Detect Detect the Security & Trust Infractions Miss Recover Miss Recover quickly and gracefully from the Security & Trust Infractions
  • 23. The Future is a World of Many Clouds • The Cloud – while still evolving – enables many possibilities • Challenges in Cloud Computing has so far mostly kept it to social networks; Security and Privacy tops the list • Three Key Focus Areas: 1) Match WL with the Platform & Automate 2) Big Data & Analytics 3) Client Aware Computing
  • 24.
  • 25. Legal Disclaimer • INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL'S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. • UNLESS OTHERWISE AGREED IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED FOR ANY APPLICATION IN WHICH THE FAILURE OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE PERSONAL INJURY OR DEATH MAY OCCUR. • Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions marked "reserved" or "undefined". Intel reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities arising from future changes to them. The information here is subject to change without notice. Do not finalize a design with this information. • The products described in this document may contain design defects or errors known as errata which may cause the product to deviate from published specifications. Current characterized errata are available on request. • Contact your local Intel sales office or your distributor to obtain the latest specifications and before placing your product order. • Copies of documents which have an order number and are referenced in this document, or other Intel literature, may be obtained by calling 1-800-548-4725, or go to: http://www.intel.com/design/literature.htm. • Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. • Intel processor numbers are not a measure of performance. Processor numbers differentiate features within each processor family, not across different processor families. Go to: http://www.intel.com/products/processor_number. • Intel product plans in this presentation do not constitute Intel plan of record product roadmaps. Please contact your Intel representative to obtain Intel's current plan of record product roadmaps. • Intel, Sponsors of Tomorrow and the Intel logo are trademarks of Intel Corporation in the United States and other countries. • *Other names and brands may be claimed as the property of others. • Copyright ©2011 Intel Corporation.
  • 26. Risk Factors The above statements and any others in this document that refer to plans and expectations for the second quarter, the year and the future are forward-looking statements that involve a number of risks and uncertainties. Words such as “anticipates,” “expects,” “intends,” “plans,” “believes,” “seeks,” “estimates,” “may,” “will,” “should,” and their variations identify forward-looking statements. Statements that refer to or are based on projections, uncertain events or assumptions also identify forward-looking statements. Many factors could affect Intel’s actual results, and variances from Intel’s current expectations regarding such factors could cause actual results to differ materially from those expressed in these forward-looking statements. Intel presently considers the following to be the important factors that could cause actual results to differ materially from the company’s expectations. Demand could be different from Intel's expectations due to factors including changes in business and economic conditions, including supply constraints and other disruptions affecting customers; customer acceptance of Intel’s and competitors’ products; changes in customer order patterns including order cancellations; and changes in the level of inventory at customers. Potential disruptions in the high technology supply chain resulting from the recent disaster in Japan could cause customer demand to be different from Intel’s expectations. Intel operates in intensely competitive industries that are characterized by a high percentage of costs that are fixed or difficult to reduce in the short term and product demand that is highly variable and difficult to forecast. Revenue and the gross margin percentage are affected by the timing of Intel product introductions and the demand for and market acceptance of Intel's products; actions taken by Intel's competitors, including product offerings and introductions, marketing programs and pricing pressures and Intel’s response to such actions; and Intel’s ability to respond quickly to technological developments and to incorporate new features into its products. The gross margin percentage could vary significantly from expectations based on capacity utilization; variations in inventory valuation, including variations related to the timing of qualifying products for sale; changes in revenue levels; product mix and pricing; the timing and execution of the manufacturing ramp and associated costs; start-up costs; excess or obsolete inventory; changes in unit costs; defects or disruptions in the supply of materials or resources; product manufacturing quality/yields; and impairments of long-lived assets, including manufacturing, assembly/test and intangible assets. Expenses, particularly certain marketing and compensation expenses, as well as restructuring and asset impairment charges, vary depending on the level of demand for Intel's products and the level of revenue and profits. The majority of Intel’s non-marketable equity investment portfolio balance is concentrated in companies in the flash memory market segment, and declines in this market segment or changes in management’s plans with respect to Intel’s investments in this market segment could result in significant impairment charges, impacting restructuring charges as well as gains/losses on equity investments and interest and other. Intel's results could be affected by adverse economic, social, political and physical/infrastructure conditions in countries where Intel, its customers or its suppliers operate, including military conflict and other security risks, natural disasters, infrastructure disruptions, health concerns and fluctuations in currency exchange rates. Intel’s results could be affected by the timing of closing of acquisitions and divestitures. Intel's results could be affected by adverse effects associated with product defects and errata (deviations from published specifications), and by litigation or regulatory matters involving intellectual property, stockholder, consumer, antitrust and other issues, such as the litigation and regulatory matters described in Intel's SEC reports. An unfavorable ruling could include monetary damages or an injunction prohibiting us from manufacturing or selling one or more products, precluding particular business practices, impacting Intel’s ability to design its products, or requiring other remedies such as compulsory licensing of intellectual property. A detailed discussion of these and other factors that could affect Intel’s results is included in Intel’s SEC filings, including the report on Form 10-Q for the quarter ended April 2, 2011. Rev. 5/9/11