扶贫不能排排坐分果果（话说新农村）

Transcript

1. IMPACT The of Cloud Computing a presentation by DR. MATT

   WOOD

2. THANK YOU Hello, and

3. INTRO WHY CLOUD COMPUTING? LIFE SCIENCES IN THE CLOUD IMPACT

   ON LIFE SCIENCES

4. SEVEN years young

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6. SERVICES to support virtually any workload Broad and deep

7. 2007 2008 2009 2010 2011 2012 159 82 61 48

   24 9

8. SECURITY capabilities to support virtually any workload Comprehensive

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11. EVERY DAY to power amazon.com in 2003 Add enough server

    capacity

12. UTILITY Computing delivered as a

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15. ECONOMIES of scale to lower prices Take advantage of the

16. Q4 2006 Q1 2007 Q2 2007 Q3 2007 Q4 2007

    Q1 2008 Q2 2008 Q3 2008 Q4 2008 Q1 2009 Q2 2009 Q3 2009 Q4 2009 Q1 2010 Q2 2010 Q3 2010 Q4 2010 Q1 2011 Q2 2011 Q3 2011 Q4 2011 Q1 2012 Q2 2012 Q3 2012 Q4 2012 Q1 2013 2 TRILLION OBJECTS

17. 5/22/2010 6/12/2010 7/3/2010 7/24/2010 8/14/2010 9/4/2010 9/25/2010 10/16/2010 11/6/2010 11/27/2010

    12/18/2010 1/8/2011 1/29/2011 2/19/2011 3/12/2011 4/2/2011 4/23/2011 5/14/2011 6/4/2011 6/25/2011 7/16/2011 8/6/2011 8/27/2011 9/17/2011 10/8/2011 10/29/2011 11/19/2011 12/10/2011 12/31/2011 1/21/2012 2/11/2012 3/3/2012 3/24/2012 4/14/2012 5/5/2012 5/26/2012 6/16/2012 7/7/2012 7/28/2012 8/18/2012 9/8/2012 9/29/2012 10/20/2012 11/10/2012 12/01/2012 12/22/2012 1/12/2013 2/2/2013 2/23/2013 3/16/2013 4/6/2013 5.5 MILLION HADOOP CLUSTERS

18. FLEXIBILITY in using these resources Provide

19. Free steak campaign Facebook page Mars exploration ops Consumer social

    app Ticket pricing optimization SAP & Sharepoint Securities Trading Data Archiving Marketing web site Interactive TV apps Financial markets analytics Consumer social app Big data analytics Web site & media sharing Disaster recovery Media streaming Web and mobile apps Streaming webcasts Facebook app Consumer social app Business line of sight Mobile analytics IT operations Digital media Core IT and media Ground campaign

20. ADOPTING cloud computing? Why are customers

21. CAPITAL EXPENSE for variable expense Trade

22. $0 vs TO GET STARTED

23. VARIABLE EXPENSE than companies can do themselves Lower

24. On-premises AWS $3.01M $0.90M Source: IDC Whitepaper, sponsored by Amazon,

    “The Business Value of Amazon Web Services Accelerates Over Time.” July 2012 70% LOWER 5 YEAR TCO PER APP

25. GUESS capacity You don’t need to

26. TIME DEMAND

27. TIME PREDICTED DEMAND

28. DEMAND TIME ACTUAL PREDICTED

29. TIME WASTE ACTUAL DEMAND PREDICTED

30. TIME WASTE OPPORTUNITY COST ACTUAL DEMAND PREDICTED

31. TIME ACTUAL DEMAND AWS

32. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Weekly traffic to

    amazon.com

33. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Weekly traffic to

    amazon.com

34. Sunday Monday Tuesday Wednesday Thursday Friday Saturday 39% 61% Weekly

    traffic to amazon.com

35. November traffic to amazon.com

36. 76% 24% November traffic to amazon.com

37. SPEED and agility Dramatically increase

38. WEEKS MINUTES to

39. EXPERIMENTATION is fast and low risk Increase innovation when

40. UNDIFFERENTIATED heavy lifting Stop spending money on

41. data centers power cooling cabling networking racks servers storage labor

42. GLOBAL in minutes Go

43. OPEX Replace CapEx with COST Lower overall AGILITY Speed and

    CAPACITY Don’t guess FOCUS Enhance GLOBAL Go

44. LIFE SCIENCES in the cloud? What are the drivers for

45. DATA generation Decreasing cost of

46. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

47. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

    Lower costs, higher throughput

48. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

    Lower costs, higher throughput Highly constrained

49. 1990 2000 2010 2020 The Data Analysis Gap Enterprise Data

    Data in Warehouse Generated data Available for analysis Data volume Gartner: User Survey Analysis: Key Trends Shaping the Future of Data Center Infrastructure Through 2011 IDC: Worldwide Business Analytics Software 2012–2016 Forecast and 2011 Vendor Shares

50. REMOVES resource constraints Utility computing

51. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

    Lower costs, higher throughput Highly constrained

52. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

53. Average daily number of cells that moved out from the

    communal sections. Linus Bengtsson et al. PLoS Medicine, 2011

54. You Are What You Tweet: Analyzing Twitter for Public Health.

    M. J. Paul and M. Dredze, 2011 Tweeting about Flu

55. Tweeting about Food

56. Tweets about the price of rice Official food price inflation

    Tweeting about Food
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59. Chromosome 11 : ACTN3 : rs1815739

60. Chromosome X : rs6625163

61. Chromosome 19 : FUT2 : rs601338

62. Chromosome 2 : rs10427255

63. TYPE II Chromosome 10 : rs7903146

64. +0.25 Chromosome 15 : rs2472297

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66. GENERATION COLLECTION & STORAGE ANALYTICS & COMPUTATION COLLABORATION & SHARING

67. RATE LIMITING Data generation is no longer

68. ANALYTICS Unconstrained and computation

69. 12.5 3 years hours

70. 12.5 3 $20M $4k years hours

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72. $1k Less than today

73. 1,000,000+ core hours

74. WAREHOUSING Petabyte scale, managed with high performance

75. WAREHOUSING Petabyte scale, managed with high performance aws.amazon.com/redshift

76. $1000 Less than per terabyte, per year

77. ARCHIVAL High durability

78. 99.999999999% $0.01 durability per gigabyte, per month

79. As our company moves into the clinical space, we face

    a legal requirement to archive patient data for years that would drastically raise the cost of storage. Thanks to Amazon Glacier’s secure and scalable solution, we will be able to provide cost-effective, long-term storage and thereby eliminate a barrier to providing whole genome sequencing for medical treatment of cancer and other genetic diseases. ” “

80. MANAGEMENT and computation challenges Beyond the data

81. SHARING and integration Enable data

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83. AVAILABLE at no cost Public datasets

84. COMPLIANCE for security and privacy Regulatory

85. SHARED responsibility An environment of

86. HIPAA 21 CFR Part 11 CLIA, GxP and others...

87. CLOUD COMPUTING on life sciences? What is the impact of

88. RESEARCH Accelerating

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91. Apps Public Genomic Databases Users EMR Support & Engineering Instruments

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94. CLINICAL IMPACT Improving

95. Speeding server provisioning for R&D apps Extending capacity for internal

    grid environments Slowing internally hosted compute infrastructure growth On-boarding security, validation services and compliance Hosting research data Reducing cost while extending capabilities Challenges

96. Clinical pharmacology and pharmacometrics Molecular dynamics Computational genomics Research portfolio

    Primary uses

97. 98% time saved for clinical trial simulations Internal System AWS

    Individual Clinical Trial Simulation Run Time (Min) 56 56 Total Number of Clinical Trial Simulations 2000 2000 No. Servers 2 256 No. CPU’s 32 2048 Total Analysis Run Time (hr) 60 1.2 Cost ?? $336

98. Reduced burden on pediatric subjects Traditional Design Design Optimized Using

    Clinical Trial Simulation # of subjects 60 40 # of blood samples per subject 12 5 Length of stay per subject 72 hours 26 hours Length of study 2.5 years 1.7 years Total study cost $700K $250K Length and cost projected based on historical data in pediatric subjects

99. WHAT’S NEXT Thinking about for cloud computing

100. DON’T CHANGE Focus on things that

101. LOWER PRICES Continue to

102. EXPANSION Continued geographic

103. BIG DATA Evolution of the landscape

104. SECURITY Retain laser-sharp focus on and encryption

105. MOBILE Interconnected data and devices

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107. INTRO WHY CLOUD COMPUTING? LIFE SCIENCES IN THE CLOUD IMPACT

     ON LIFE SCIENCES

108. THANK YOU

109. [email protected] aws.amazon.com