1. Azure HPC
Solution pitch deck

2. 500+ million core hours running HPC on Azure
High Performance Computing
500+ million core hours running HPC on Azure
Download the commercial story and ambition stories at

3. Evolution of HPC on Azure
Engineering Insight
Timeline
Cloud Computing,
2012
Windows HPC
on Azure, 2014
GPU on Azure, August 2016
(private preview)
New HPC instances soon
Linux RDMA (infiniband)
on Azure, July 2015
Enhanced networking
to support any MPI
Very large tenant sizes

4. Hyperscale infrastructure
30+ regions worldwide—huge capacity around the world—growing every year
UK East
UK West
North Central US
Illinois
West Europe
Netherlands
North Europe
Ireland
Canada Central
Toronto
Central US
Iowa
Canada East
Quebec City
Germany West 
Germany East 
China North *
Beijing
US Gov
Iowa
Japan East
Saitama
China South *
Shanghai
West US
California
East US
Virginia
India Central
Pune
Japan West
Osaka
East US 2
Virginia
South Central US
Texas
India South
Chennai
US Gov
Virginia
India West
Mumbai
East Asia
Hong Kong
Why this Slide:
This is SUCH a big investment – it’s a game for only very few. It’s not new for us – we have been doing this for our own services and our consumer/web properties for 20+ years
Key Points:
Where are we – EVERYWHERE…!
How big is this - $15+ B and counting – this is serious, we continue to bet big and you can count on us
Talk about DC innovation – DC Efficiency and Gen 5 data centers.
Scale – at this scale you do get efficiencies – the main one being POWER
Remember our “strategy” – we will be in the major places, but not everywhere – we have Azure Stack/Hosters for that.
Transition to NEXT Slide: This is the physical infrastructure that Azure sits on, now lets talk about Azure the PLATFORM
SE Asia
Singapore
100+ datacenters
2x of Amazon, 6x of Google
$15 billion investment
Australia East
New South Wales
Australia South East
Victoria
Brazil South
Sao Paulo
Operational
Announced
* Operated by 21Vianet
 Operated by Deutsche Telekom

5. Customers are moving their HPC workloads to Azure
Maturity
Advanced security and cost competitive
Current and high-end GPUs for deep learning, compute, and visualization
Dedicated HPC VMs - close to bare metal clusters
Agility and scale
Quick time to market for any workload
Scale at hand and flexibility on demand
Cost
No infrastructure investments
Pay only for what you use

6. Value proposition for HPC in the Cloud
Single system
Most time
Value:
Achieve more
Faster time to value!
Value:
Reduce time
On premises clusters are:
High CAPEX
High OPEX
Resources limited by space and allocations
Azure provides:
Zero CAPEX
Low and competitive OPEX
On Demand capacity when you need it
Pay as you go usage model
Cost of 1,000 cores for 10 hours = cost of 10,000 cores for 1 hour
Calculation time
Time to result is a real constrain in Big Compute/HPC, with Azure customers can provision as many core as they need in order to have a fast results.
=> With Azure you are billed per minutes, so If our customers need cores to get result fast, the Azure cost will be the same as waiting 10hrs with 1000 cores
Computers/Nodes
Multi-system
Least time

7. DYNAMIC CONFIGURATION
Value proposition for HPC in the Cloud
Azure Instances
Best value for your investment!
HPC apps profiles:
Parallel
Distributed
IO Intensive
Varying needs:
Cores and Memory
Networking and Storage
Azure provides:
On Demand capacity
Different configuration capabilities
InfiniBand
Investment = Application investments
As customer can deploy the right configuration they need, they will have the best ROI
FIXED CONFIGURATION
DYNAMIC CONFIGURATION

8. Microsoft HPC value proposition
10/23/2017 5:36 AM
Linux and Windows machines tuned for HPC
Provision thousand of cores in few minutes around the world
Latest GPUs in the cloud
Building blocks to deploy HPC clusters that meet your specific needs
Big Data platform services to gain insight from HPC jobs
Pay only for what you use by the minute
Today, most organizations have on-premises high- performance computing infrastructure. We see everything from a set of servers under someone’s desk to large datacenter environments, and everywhere in between, depending on what the company is trying to accomplish.
While on-premises HPC is a good option for many scenarios, it also comes with inherent constraints.
Generally speaking, an HPC infrastructure involves millions of dollars of capital cost (or expense, if it’s leased infrastructure), given the significant infrastructure required.
<Speaker Guidance: you may not need to elaborate on what this capital investment includes – below is optional reference if needed>
This investment includes:
X86 servers with the latest chip sets and high-speed, low- latency interconnects
Expensive application licensing
Sophisticated scheduling software to ensure clusters are fully utilized
High-speed storage or parallel file system to access single name space from multiple servers
In some cases, remote visualization solutions are also involved
And these massive investments are hard to keep current – hardware often goes out of date before it can be refreshed.
Operational costs like power, cooling and maintenance also add up, and it’s common to run into constraints, especially with power and capacity.
All of this assumes that there is physical space for more compute infrastructure. We’ve heard of firms taking over parking lots and other facilities in order to build out their HPC infrastructure, but that’s not always an option. Dedicating more space to infrastructure also comes with its own costs and hassles.
An even greater issue is constraints on engineers’ work efforts. When we talk to engineers, they often tell us about long wait times for shared capacity.
When an engineer needs a job run, they are in ‘wait mode’ while their jobs sit in a queue, waiting to be run
This can be a multi-day day wait until they get to the front of the line, impacting productivity
When you consider the allocation challenges of balancing small jobs with massive ones, the problem gets even trickier.
As a result, engineers are constrained to using HPC to validate design choices. Using HPC for innovative purposes, like experimenting with design direction, isn’t even an option due to the capacity constraints.
This type of environment is also inflexible – it’s not designed to scale up and down as needed
In many firms, there are peaks and valleys of hardware utilization – for example, there might be large projects or seasonal work where your hardware is running at maximum capacity and still can’t keep up.
At some organizations, it can take months to open a purchase order and add service, so if there are unexpected peaks in demand, there’s no way to quickly cope
And there is also inflexibility when workloads are reduced – but you are still paying for the downtime. The hardware is often running and available whether you use it or not, and must be maintained.
Finding space for HPC infrastructure, investing in it, keeping it current, and maintaining ends up being time- consuming and extremely complex. And efficiently meeting demand is often not possible. Engineers are limited to using HPC for design validation, rather than using it for strategic purposes.
Transition: Microsoft Azure provides an alternative approach to on-premises infrastructure.
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9. Azure value proposition
Azure features
Enterprise-ready
Large-scale on-demand
Infrastructure and Hardware built and operated for HPC
RDMA for fast MPI performance
Parallel file systems
Support for Intel Lustre and Red Hat GlusterFS
Azure Marketplace
Azure Marketplace offers variety of vendor certified solutions and a robust HPC ecosystem
MPI support
Intel MPI, Platform MPI (IBM) in Beta
Core differentiators
Hybrid HPC mode
Microsoft offers hybrid “Burst to Azure”
HPC-as-a-service
Azure offers HPC-as-a-service through Azure Batch
Multi-OS support
Azure supports both Windows and Linux OS options in HPC Clusters and Batch
Better engineering
Advanced engineering, faster infrastructure and competitive pricing

10. The Microsoft Azure HPC ecosystem
Hardware & Software Infrastructure
Big Compute Marketplace
Certified Applications

11. The soft bits Solvers OS support Schedulers MPI support
SLES 12, CENT OS 7.1
Windows Server 2012 R2
Schedulers
PBS-PRO/COMPUTE MANAGER
IBM Platform LSF & Symfoni
Tibco Data Synapse
Microsoft HPC_PACK
MPI support
Intel MPI
Platform MPI (in prototype phase)
MS MPI on Windows
Parallel file systems
Intel Lustre
Red Hat GlusterFS
Solvers
Intersect (Schlumberger)
NAMD
LS-DYNA
FLUENT
STAR-CCM
RADIOSS
ACU-SOLVE
OPENFOAM
PAM-CRASH
LANDMARK (Halliburton)
ABAQUS
MSC NASTRAN
OPTISTRUCT

12. Deployment options for every scenario
10/23/2017 5:36 AM
Deployment options for every scenario
All in cloud
No compromise “all in cloud” deployments, using the dedicated Azure HPC components with your preferred application and middleware.
Hybrid—Burst to cloud
Address changing capacity needs. Extend your HPC jobs to Azure for on-demand scale and flexibility.
There are two key scenarios that we would like to explore for a minute. First, is our enterprise scale scenario, where you leverage Azure for additional capacity or new workloads.
Second, is Azure burst, allowing you to burst to the cloud for more capacity.
Both scenarios are truly pay as you go without any upfront cost of infrastructure.
Transition: Let’s look at our enterprise scale model.
As a service
Easy planning, deployment and orchestration of your HPC jobs. Batch is a fully automated “as a service” engine for HPC type workloads— ISV or end user.
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

13. Batch (HPC as a service)
Rich-client experience for users
Use resources depending on workload needs
Burst only when required
Leverage existing applications and algorithms
Manage “pools” of VMs for different type of users
Get clear insights into application and service usage
Azure Batch VM Pool
RETURN RESULTS
Azure BLAST Portal
App EXE
App EXE
App EXE
VMs
SUBMIT JOB
UPLOAD DATA

14. Azure Batch and Compute Stack
Service/Solution
Get and Manage VMs
Task failure?
Task frozen?
Install Task Applications
Manage and Authenticate Users
Azure Batch
VM Management and Job Scheduling
Start the tasks
Batch processing platform
Avoid building infrastructure
Queue tasks
Move task input and output
Scale up and down
PaaS
Cloud Services
IaaS
VM/VMSS
Hardware

15. Solutions

16. Finance and Capital Markets
Compliance
Regulations and legislation
Products get more complex
Run on regular basis (quarterly, daily)
Risk management and analytics
Risk Compute Grids
Modeling & Analytics
Tests of new algorithm at scale
Home made applications
Operations
Disaster Recovery
Optimal TCO
Flexibility for business line
Compliance:
Insurance = Solvency 2
Bank = BASEL 2/3/4
Risk Management:
Use case are Counterparty Risk management , CVA (Credit Valuation Adjustment), VaR (Value At Risk), Stress testing, tes & dev for Quants, Algorithmc models
For Solvency 2:
Leader applications are TOWER WATSON Moses, SUNGARD Prophet, MILIMAN Mg Alpha
All can run in Azure
FLEXIBLE = when customer need compliance run (quaterly, daily) or react on a market event (for instance black swan event with the Swiss Franc in January 2015)
SECURE = Secured storage and disks, secure network connections.
TCO = pay only when you deploy ressources
Microsoft Azure based solution enables Financial Institutions deploy and manage grids for risk management and related compute needs in a flexible, secure, and controlled manner for optimal TCO.

17. Improving operational insights
Top Japanese bank in the UK gained advanced analytics through the cloud
Challenge
Gain flexibility to analyze advanced capital scenarios.
Decrease risk and build greater confidence across the business.
Batch
Implemented a bursting scenario using Microsoft HPC Server with Azure
Moved 2,000 cores per day to the cloud
Results
Avoided the additional capital expenditure for a new datacenter
Obtained consistent, reliable core deployments on demand
Gained business agility for better competitiveness
Key points:
Customer profile: This customer is the European capital markets hub of one of the largest financial institutions in the world. Headquartered in London, this bank is active throughout the international capital markets, focusing on debt, equity, derivatives and structured products.
Business goal: The risk group needed their information ready to go each morning but there was not enough time to complete these more advanced models overnight, given the already taxed production environment. Further, the risk department could not confidently predict precise capacity required as markets are increasingly volatile. The bank did not have the capacity on their own grid and they wanted to avoid capital expenditures from a large datacenter purchase for expansion.
Tactics: To meet these expansion demands and to speed up the time to delivery for the business, the bank selected a Microsoft HPC Server and Azure solution. Their goal was to move at least 2,000 cores per day to the cloud, used in concert with on-premises datacenters allowing maximum flexibility.
Results: By avoiding the capital expenditure of a new datacenter, the bank was able to meet growth expectations and align their costs to their business strategy. They are now running Azure daily and can obtain consistent, reliable core deployments on demand. The solution has provided the bank with the business agility it needs to be competitive today and in the future.
Hybrid solution
Consuming 2K cores per day

18. New financial modeling software
10/23/2017 5:36 AM
Tower Watson Risk Agility FM
Challenge
Designed for Actuaries to develop and run models
Projection system to model asset and liability cash flows over the term of policies
Batch
Auto-scale to meet demand
Lightweight REST interface and API libraries in various programming languages
Results
Reduced costs and administration.
Large scale deployments without infrastructure
Opens up grid computing to smaller clients
Increased business agility
they have a application called Risk Agility FM which is traditionally a cluster application and is essentially designed for Actuaries to develop and run
models to manage risk and safegaurd solvency and its primary focus is on life insurance. Their software allows them to deploy sophisticated analytical calaculations based on realistic economic principles. One of their biggest motivations is that this service opens up a host of new opportunities for their smaller clients who can't afford to build on premise clusters and can now use Risk Agility FM as a service. It also helps that Towers watson is providing and concentrating on business value which is their analysis and now spending cost and time on managing infrastructure. They also went through the evolution of running on premise, then going hybrid and then finally evolving to the SaaS model.
What would you do with 100,000 cores?
Big compute at global scale
Manage risk and safeguard solvency 2 Azure Batch
© 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

19. Manufacturing Engineering design Applications Operations
Drive design of products
Design, Simulate, Analyze results
Simulated problems are complex
Applications
ISV applications
Linux
Specialized hardware
Operations
Disaster Recovery
Optimal TCO
Flexibility for business line
FLEXIBLE = when customer have a new and important project or an unexpected simulation to be done
POWERFUL = Azure provide HPC instance (Infinband, GPU, high end core)
TCO = pay only when you deploy ressources
Microsoft Azure based solutions enable Manufacturing Companies to deploy and manage clusters for physical simulation in a flexible, powerful and controlled manner for optimal TCO

20. Simulation and analytics in Azure
Business transformation in Motorsports
Challenge
Make better decisions on car setup and race strategy through simulation and data analysis
Desktop to garage to racetrack
Batch
CFD in Azure to model airflow
Azure Machine Learning and Cortana Analytics for race strategy
Results
CFD results in half the time
Highly accurate models for fuel and tires
Tools for the simulator and at race day

21. Oil and Gas Seismic data processing Reservoir simulation Operations
Exploration of new oil field
Process large amount of data
Complex problem
Reservoir simulation
Development of new fields
Developed fields for oil forecasts
ISV applications
Linux
Specialized hardware
Operations
Disaster Recovery
Optimal TCO
Flexibility for business line
Microsoft Azure based solution enables Oil and Gas company to deploy and manage clusters in a flexible, powerful and controlled fashion for optimal TCO

22. High resolution reservoir simulator in the cloud
By the largest oilfield services company in the world
Challenge
Find the right cloud solution
Models keep getting larger
Ever-growing demand for more and faster compute resources
Difficulty of having access to the right type of resources
Strategy
Accessibility and scalability
True HPC capabilities on Azure
Results
Schlumberger’s customers can now submit simulations to the cloud directly from Petrel
Capabilities are available on a subscription-based model
Schlumberger:
Schlumberger is the largest oilfield services company in the world. It employs 115,000 people in more than 85 countries. Their products and services span from exploration through production. It supplies technology, integrated project management and information solutions to customers working in the oil and gas industry worldwide.
This is Schlumberger’s first fully commercial software as a service (SaaS) solution for cloud, and they decided that Azure is the right cloud platform to host it on for the initial launch in North America and Europe.
Challenge:
INTERSECT is their high-resolution reservoir simulator for large and complex engineering models.
These models have not been traditionally possible in the cloud (at least not efficiently) because they require specialized hardware and an array of different technologies that are not part of a “normal” cloud offering. But, at the same time, these models are starting to outgrow the on-premises resources that companies and service providers have at their disposal
So, in essence, SLB & his customers are confronted with is a combination of an ever-growing demand for more and faster compute resources (driven by the ever-growing characteristic of the simulations), paired with the difficulty of having access to the right type of resources. Fortunately, this is just the kind of challenge that we have been working hard to solve in Azure.
Strategy:
The accessibility and scalability offered by cloud computing should be the answer to the challenges mentioned earlier, but before this is true, the backend infrastructure must have the right technology to enable the simulator to really perform.  This is where Schlumberger and Microsoft working together have created and delivered the most appropriate technology solution
Results:
Thanks to the availability of this service, Schlumberger’s customers can now submit simulations to the cloud directly from Petrel, the industry leading reservoir modelling tool and the simulation environment that Schlumberger provides for generating the models, as well as for visualizing the results. This means that a reservoir engineer never leaves the environment that she or he is familiar with. The engineer just needs to select where the simulation should run: locally, on an on-premises cluster, or on the cloud. After the simulation has run, the engineer can analyze the results back in Petrel, as usual.
But perhaps what is most exciting about this solution is that these capabilities are available on a subscription-based model, making it possible for companies of all sizes, on all parts of the world—including those customers who are unable to afford their own HPC environment—to have access to high science, on an enterprise-class simulation solution like INTERSECT. This, in particular, is one of the greatest advantages of a cloud solution.
Learn more
To learn more about Big Compute solutions on Azure, see:
To learn more about Schlumberger INTERSECT Simulator in the Cloud, see:
To learn more about Schlumberger INTERSECT, see:
Azure Batch

23. Media and Entertainment
Rendering
3D production
Movies and gaming industry
HD Images
Need many cores
Applications
Software ISV
Rendering ISV
Linux/Windows
Operations
Disaster Recovery
Optimal TCO
Flexibility for business line
Major Software ISVs :
Autodesk: 3DS max, Maya,
Lightwave
OSS : Blender
Major Rendering ISVs:
RenderMan – Pixar
Arnold – Solid Angle
V-Ray – Chaos Group
Maxwell – Next Limit
CINEMA 4D – Cinema4D
Modo, Katana, Nuke – The Foundry
Mental Ray – NVIDIA
FLEXIBLE : Ramp up & down quickly for a lumpy, unpredictable and potentially long running Workloads
SECURED : Data/models are secured
TCO = Pay only when you deploy ressources
Microsoft Azure based solution enables Media Companies to deploy and manage clusters for physical simulation in a flexible, secure and controlled fashion for optimal TCO

24. Animated feature film rendering
PROAN Entertainment leverages Azure Batch for rendering in the cloud for full length 3D animation feature
Challenge
90 minute 3D animated feature film
Would have taken over 13 years to render using existing on-premises cluster
Find the best rendering program within the budget
Strategy
Blender to Azure batch plugin
Close relationship with customer
Azure compute
Results
1,600 cores at peaks
4 months of production and 3 months in post-production
Rendered entirely in Azure using Blender in about 3 months
PROAN Entertainment, a division of Grupo PROAN and a leading digital studio based in Mexico
‘Pepito – La Película’

25. Other verticals Bio/genetics Academics Other
Exploration of new drugs
Gene exploration
Linux
Academics
Research in any topics
Linux
Other
Need compute power
Solving many problems
Solving complex problems
Microsoft Azure based solution enable access to unlimited power in a flexible, secured manner, at your terms with optimal TCO

26. Molecular modeling in Microsoft Azure
By one of the largest chemical companies in the world
Challenge
Reduce compute costs while continuing growth
Custom application written by DuPont Scientist on molecular modeling
Strategy
Opportunity found by CSA during Azure briefing
Engage Azure black- belt + engineering early in the sales cycle
Results
Mid-Atlantic district is going to use this success and apply learnings to other accounts
This project facilitated Azure HPC deep dive for their R&D scientist which will drive more workloads
DuPont
Customer: One of the largest chemical companies in the world
US based, $35 billion in annual revenue, 65,000 employees across 90 countries
Team: Louis Berman CSA, Steve Roach Big Compute TSP Black belt, John Fitch ATS
Workload
Custom application written by DuPont Scientist on molecular modeling
Customer willingly recompiled application to Intel MPI on Azure
Using ARM templates spun up 2 clusters 100 A9 instances each (1600 cores)
One MPI job/application running across 1600 cores for weeks
3,215,708 compute core hours
i.e. $241,178 dollars consumption in less than 3 months

27. Conclusion and additional resources
10/23/2017 5:36 AM
On VMs DIY
Customers setting up separate cloud environment for additional capacity and new workloads
Burst
Burst to cloud for more capacity
Utilize existing scheduler to burst to Azure and use compute on demand
SaaS
ISVs and Managed service providers launch their own SaaS solutions. Pay for compute and application software per hour
Marketplace
Utilize the scale of Azure Applications and compute capacity sold through Azure marketplace
All above scenarios are truly pay as you go without any upfront cost of infrastructure.
Resources
Azure Big Compute
Azure Batch Overview
Azure Batch Technical Overview
HPC Pack for Linux
Azure compute-intensive instances - A8, A9, A10 and A11 specs
Microsoft MPI (Message Passing Interface)
Documentation resources for HPC & Batch
Azure HPC and Batch Blog
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

28. Big Compute case studies
10/23/2017 5:36 AM
Milliman (actuarial and financial risk modeling using Batch):
Towers Watson (actuarial and financial risk modeling using Batch):
ANEO (SI for financial services using HPC Pack IaaS on Azure):
d3VIEW (SI for engineering simulations providing SaaS with A8/A9 VMs):
Schlumberger (ISV for oil & gas engineering modeling providing SaaS with A8/A9 VMs):
Microsoft Research FaST-LMM project (genetics research using HPC Pack IaaS on Azure):
Ludwig Institute of Cancer Research (genetics research using HPC Pack on premises):
Check for new ones by going here:
Search for “HPC”:
Search for “Big Compute”: compute”
Search for “HPC Pack”: Pack”
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

29. 10/23/2017 5:36 AM
© 2016 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market
conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.
MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
© 2016 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.