Impact of Big Data growth On Transparent Computing

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1 Impact of Big Data growth On Transparent Computing Michael A. Greene Intel Vice President, Software and Services Group, General Manager, System Technologies and Optimization 1

2 Transparent Computing (TC) TC is a user controlled cloud computing. Prof. Zhang Yaoxue 2

3 Transparent Computing Vision User can get any info, any application or any Operating System from any devices transparently. 3

4 Transparent Computing (TC) is facing Data growth challenges in cloud Data Data is the Key driver behind TC services 4

5 Transparent Computing (TC) Challenges TC Data challenges comes from 4 areas Data Collection Data Storage Data Data Process Data Access 5

6 Billions connected users sharing 663M SKYPE 273M YAHOO 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL 6

7 Billions connected users sharing 663M SKYPE 273M YAHOO 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL 7

8 663M SKYPE Billions connected users sharing 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL >1500 Exabytes of cloud traffic 273M YAHOO 8

9 663M SKYPE Billions connected users sharing 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL >1500 Exabytes of cloud traf c 273M YAHOO 9

10 663M SKYPE Billions connected users sharing 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL of cloud traf c 1400 Exabytes >1500 Exabytes of new integrated systems data 273M YAHOO 10

11 663M SKYPE Billions connected users sharing 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL of cloud traf c 1400 Exabytes >1500 Exabytes of new integrated systems data 273M YAHOO 11

12 663M SKYPE Billions connected users sharing 273M YAHOO 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL >1500 Exabytes 1400 Exabytes of new integrated systems data of cloud traf c 690% Growth in storage capacity by 2015 Volume Big Sensed Data Big Corp Data Unstructured Data Big Web Data Corporate Data Structured Data Time 12

13 663M SKYPE Billions connected users sharing 273M YAHOO 5.3B CELL PHONES 629M FACEBOOK 364M HOTMAIL >1500 Exabytes of cloud traf c Volume 1400 Exabytes of new integrated systems data 690% Growth in storage capacity by 2015 Big Sensed Data Big Corp Data Unstructured Data Big Web Data Corporate Data Structured Data Time 13

14 663M SKYPE Billions connected users sharing 273M YAHOO 5.3B CELL PHONES 629M FACEBOOK >1500 Exabytes of cloud traf c 1400 Exabytes of new integrated systems data Volume 690% Growth in storage capacity by 2015 Big Sensed Data Big Corp Data 364M Big Web Data HOTMAIL Corporate Data HOW ARE YOU APPROACHING What insights can we derive? COMPLEXITY REPORTING ANALYSIS MONITORING BUSINESS VALUE PREDICTION THE OPPORTUNITY? Unstructured Data Structured Data Are you looking at Big Data? Yes 75% No 5% No, but on radar 20% Time 14

15 The Big Data Platform Data Big Data Technology can solve TC Data Challenges 15

16 Intel Role in Big Data Distribute analytics to the edge sensors/devices and drive a standards based connected, managed and secure architecture Accelerate big data analytics through faster and more effective CPU, storage, I/O and network architectures Drive innovation in big data applications by providing optimized software stacks and services Foster the growth of big data through partner collaboration, focused on usage model examples and reference deployment architectures Invest in solution research and academia collaboration 16

17 Intel Intelligent Systems Framework: Simplifying the Internet of Things Data Collection DRIVING SECURE INTEROPERABILITY UNLOCKING EDGE DATA FILTERING DATA Billions of devices that need to share data with each other and the cloud Edge systems need to react to streaming data in real time Data volume outpacing network and storage efficiency 17

18 Platform and Software Optimizations for Hadoop Data Process Integrated PCI Express* 3.0 Up to 40 lanes per socket Up to four channels DDR MHz memory Up to eight cores Up to 20 MB cache 18 Up to 80% Performance Boost vs. Prior Generation Intel AVX - Reduce Compute Time Intel Turbo Boost Hadoop Optimizations Built on Open Source Releases Custom Tuning for Data Types and Scaling Approaches 1 Performance comparison using best submitted/published 2-socket server results on the SPECfp*_rate_base2006 benchmark as of 6 March Source: Intel internal measurements of average time for an I/O device read to local system memory under idle conditions comparing Intel Xeon processor E product family (230 ns) vs.. Intel Xeon processor 5500 series (340 ns). See notes in backup for configuration details * Other names and brands may be claimed as the property of others

19 Intel & Cloudera Strategic Partnership Data Process Promote CDH as the Hadoop Distribution of choice CDH to be Performance-optimized for Intel Architecture Largest strategic shareholder in Cloudera Support for Intel CPUs, Ethernet, SSD, security & future technologies 19

20 In Memory analytics are Game Changing $/TB Running time (s) Data Process Architecting for In Memory Model HANA VOLTDB 20 node VoltDB system can do what a 1000 node Hadoop cluster can do Michael Stonebreaker, Objectivity GraphDB + + TimesTen In- Memory Database Business Intelligence Enterprise Edition SolidDB $50,000 $40, SAP HANA* Scalability Customer Workload $30,000 Ideal $20,000 $10,000 20x Reduction 500 8S Glueless 20 $0 Q (DRAM) Q (DRAM) Low Cost Memory Technology 2016 (CR) Near Real-time Insight Enabled by In-Memory Solutions Socket Count Near-perfect scaling on Intel Xeon processor E7 family 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. Source:

21 Intelligent Storage Pays Off Data Storage De-duplication Real Time Compression BEFORE DE-DUPLICATIONAFTER 95% smaller backup 1 Intelligent Tiering Up to 80% data reduction 2 Thin Provisioning APPLI 3 APPLI 2 APPLI 1 TRADITIONAL ALLOCATION ALLOCATED BUT FREE USED ALLOCATED BUT FREE USED ALLOCATED BUT FREE USED THIN PROVISIONING SYSTEM-WIDE CAPACITY RESERVED APPLI 3 APPLI 2 APPLI 1 21 Up to 80% reduction in disk expenses 3 1 IBM storage simulcast, November 9, BM storage simulcast, November 9, Dell Fluid Data Storage: Driving Flexibility in the Data Center, February Intel IT study Solving Intel IT s Data Storage Growth Challenges Up to 25% reduction in storage CapEx growth 4

22 Visibly Mobile Performance Data Access Responsiveness Insight & Productivity Work Station Performance For Right Deep Model Generation for Analytics Processes Collaboration Secure Media, Data,& Assets Visibly Mobile Data Productivity Flexible End Point Solutions with client application support that allow fast and efficient data modeling, scoring and direct data access from any location Intel Virtualization Technology requires a computer system with an enabled Intel processor, BIOS, virtual machine monitor (VMM) and, for some uses, certain computer system software enabled for it.

23 Traditional New & or Open New, Open looking to disrupt Traditional Data Management Analytics 23

24 Intel s contribution to Open Source Enable open source operating environments to run best on Intel architecture UPSTREAM Code Capital Foster open source ecosystems and develop new markets for Intel and its partners DOWNSTREAM Alliances Foundations OEM Service Provider Enterprise 24

25 Big Data Use Cases Operational Efficiency Consumer Behavior Security & Risk Management Traffic Optimization Smart Energy Grid Location Aware Ad Placement Buyer Protection Program Personalized Preventive Care Claim Fraud Reduction 25

26 26 Collaboration with CSU on TC and Big Data

27 Summary Big Data helps to solve the data challenges for Transparent Computing Intel is well positioned from software stack and platform basis Intel is committed to collaborate with partners in new technology to address more demanding requirements of the future 27

28 Thank You

29

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