grid computing for financial services
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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Grid Computing for
Financial Services
Steve Conn, Sales Development Manager at Intel
Yinal Ozkan, Financial Services Technology Leader at AWS
April 14, 2016
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Motivations for Cloud in a Simulation-Driven World
Scalability and agility
Secure global collaboration
Enterprise data governance
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Agility Is Enabled by Global Scale
Over 1 million active customers across 190 countries
800+ government agencies
3,000+ educational institutions
12 regions
33 availability zones
54 edge locations
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HPC Today
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1965-2015: 50 Years of Moore’s Law
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The Rise of the Microprocessor
† Codename Knights Landing, not drawn to scale
28MTIMES FASTER
Intel® 4004 (1971)10,000nm, 2300 Transistors
92 KOPS
Intel® Xeon
Phi™(2015)†
14nm 3D Tri-Gate, >8B Transistors
3 TFLOPS (peak DP-F.P.)
6
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Supercomputing Pulls All HPC Along
Source: Top500.org
’90 ’95 ’00 ’05 ’10 ’15 ’20 ’25
0
10
1,000,000,000
10,000,000
100,000
1,000
Top Machine
500th Machine
Sum of All
Top 500 FLOPS >50%1 CAGR For Past Decade
#500 system on Top 500 in 2005:
~1 TFLOP
10 years later…
…One 2S Xeon server today:
~1 TFLOP
Capability Waterfalls
Source: Intel
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HPC Fuels Insight and Innovation
Astrophysics
ManufacturingEnergy
Security
FinancialLife Sciences
Weather
Source: www.hpcwire.com/2014/01/02/top-supercomputing-discoveries-2013/
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HPC Today: Two (Connected) Worlds
Supercomputing
The “rest” of HPC
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Intel Cloud Edition for Lustre Software
Innovate Faster. Experiment Risk-Free • Enterprises are adopting HPC clouds…
• To increase and augment legacy infrastructure
• Aggregates capacity and I/O bandwidth
• Brings Lustre performance to dynamic cloud resources
• Instant, pay-as-you-go access to scalable clustered
storage
• Available today from Amazon Web Services
• Support directly from Lustre experts at Intel
HPC
Big Data
Cloud
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Cloud Edition for Lustre Client Cluster &
Lustre Cluster Model
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Performance
• The Intel Lustre solution is a fast,
scalable storage platform positioned to
accelerate application performance,
even with complex workloads.
• Intel Cloud Edition for Lustre software is
an ideal foundation for SAS Grid
workloads that require fast, scalable, and
cost-effective storage. 0
500
1000
1500
2000
2500
3000
3500
4000
4 OSS 8 OSS 16 OSS
OSS Write / Read Scaling
Write MB/s Read MB/s
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Grid Computing on AWS
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Our Pricing Structure
On-Premise (or “Private Cloud”)
The New Way
Use only what you need,
using on-demand, reserved, or spot
Flexible
The Old Way
High upfront capital cost,
high cost of ongoing support
Inflexible
AWS lets you pay for the grid infrastructure you need, when
you need it.
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The Old Way – Low Utilization, High Costs
Typical service utilization rates are low due to need to deploy
for peak needs…
Time
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The Old Way – Managing Utilization with Grid
Time
Higher grid utilization rates result in hidden costs, such as
longer queue wait times and delayed results.
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The High Cost of Queues for Grid Computing
Conflicting goals
• Grid users seek fastest possible time-to-results
• Grid workloads are not steady-state
• IT support teams seek highest possible utilization
Result
• The job queue becomes the capacity buffer
• Job completion times are hard to predict
• Users are frustrated and run fewer jobs
• Innovation is throttled by IT resources
?
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The World According to Central IT
Grid utilization over one week
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The World According to Business Lines
Queue wait times over one week
Business
impact!
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The Cloud Way – Scalability When Needed
Scale higher to reduce time-to-results: shorter wait times,
greater agility, and faster innovation cycles.
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
In a secure Virtual Private Cloud
Automation and Auto Scaling allows easier
grid management and monitoring
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Enables Lower TCO than On-Premise
Utilization fundamentally higher in
AWS cloud
• Aggregating non-correlated
workloads, scale, spot market
Amazon specific hardware designs
• Amazon custom servers & network
gear
• Direct purchasing of disk, memory,
& CPU
AWS Immense scale
• New data centers built each year
• 12 global regions, 33availability
zones
• Volume purchasing with highly
automated, highly optimized supply
chainTraditional
Data Center
Virtualized
Data Center
UPFRONT
COSTS
VARIABLECOSTS
VARIABLE COSTS
AWS
UPFRONT
COSTS
UPFRONT
COSTS
VARIABLE COST
Cost savings from running
internal IT more efficiently
Cost savings from moving to a
public cloud provider
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Customer Spotlight: FINRA
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Customer Spotlight: Dow Jones International
• From over 40 data centers down to 6
• Planning to migrate 3000 apps by 2015
• Saving $100M over 3 Years
1. Evaluate infrastructure
costs & architecture
VS
2. Make business case 3. Enable decision to
move to the cloud
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Multiple Consumption Models
On-Demand
Pay for compute
capacity by the hour
with no long-term
commitments
For spiky workloads,
or to define needs
Reserved
Make a low, one-time
payment and receive
a significant discount
on the hourly charge
For committed
utilization
Spot
Bid for unused
capacity, charged at a
Spot Price which
fluctuates based on
supply and demand
For time-insensitive or
transient workloads
Spot is a
game-changer
for grid
computing.
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
On
Reserved Instances
100%
On-demand
Time
Spot
Optimizing AWS Spending with RI, On-Demand,
Spot
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All-In on Spot: Advertising Technology Company
Minimal use of RI
and on-demand, for
persistent database
tiers.
Use-case is time-critical
bid-for-placement
advertising analytics.
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Spot is used by this customer for a wide range of use-cases, including
Hadoop analytics and test/dev. Customer has implemented automation to
reduce impact of Spot terminations.
Fully Optimized:
Enterprise SaaS Solutions Provider
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
On
3-Year RI
100%
On-Demand $
Time
Spot $
1-Year RI
3-Year RI
1-Year RI 1-Year RI
1-Year RI 1-Year RI 1-Year RI
Price reductions
New instance types
Time
Cost
Optimization
Performance
Optimization
Reduced Spending Over Time for Increasing
Performance
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Proactive Cost Optimization with Trusted Advisor
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS is more cost-effective than on-premises environments in both the short-term and long-
term, and at scale, for both variable and steady-state workloads, while also delivering return on
agility and enabling new experiences.
In Summary
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Thank you!
Steve Conn, Sales Development Manager at Intel
Yinal Ozkan, Financial Services Technology Leader at AWS
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