IBM System Blue Gene

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IBM System Blue Gene

• Ultrascaling and Power Efficiency for
  Computational Advantage in Financial Services

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IBM Systems AgendaA strategic design for
delivering innovative technology, resources and
skills
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IBM System Blue Gene
Optimized for scalability, bandwidth, and massive
data handling while consuming a fraction of the
power and floor space required by todays high
performance systems

• Highest performance supercomputer! (Top500 Nov.
  2005)
• Ultra scalable performance
• Ultra performance per kW of power
• Ultra floor space density
• Innovative architecture and system design
• Familiar programmer/user environments

Available on demand!
Networks
3D Torus for point-to-point communications
Global Collective Network for oneto-all
communications
Gigabit Ethernet for file I/O, host interface,
control and monitoring

• Up to 131,072 PowerPC CPUs
• Up to 360 peak TeraFLOPS

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Example Value at Risk in near real-timeUsing
Monte Carlo simulation including data
pre-staging, computation, and data post-staging
Value at Risk is a measure of the maximum
potential change in the valueof a financial
portfolio with a given probability over a given
time period

• Value at Risk Calculation
• Generate a set of simulated Market scenariosfrom
  the joint distribution of market changes.
• Price the portfolio for all scenarios in
  thissimulated set.
• Estimate the VaR from the empirical
  profit-lossdistribution.

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Highly parallelized and efficient I/O-intensive
data file broadcasts
GPFS or Database
Two-phase algorithm for collective I/O
Data File for Broadcast Sequential Read
Phase I A subset of access nodes read
non-overlapping sections of the required file
segment
Access nodes - The number and location of
these compute nodes is customized to maximize
parallelism and avoid I/O contention
Phase II Collective communication distributes
data to remaining compute nodes A2A All to All
exchangeMBC Multiple broadcasts
Blue Gene Torus Network
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Example Variable Annuities Capital Reserve
calculation Using Nested Stochastics for 360 time
steps
Each Blue Gene node performs Simulation Service
for Nested Stochastics

• Receive Time t state.
• Calculate optional flows to horizon along
  simulation.
• Return result.

• Valuations feed Hedging model for portfolio cash
  flows across time and scenarios
• Value at Risk for cash flows feeds regulatory
  capital model

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Services Implementation
client
scatter

• Initialize
• Broadcast VA data
• Prime each BG node w/ one simulation
• Broadcast Market data
• Calculate Greeks
• single scatter-gather per outer timestep
• simulation services by node
• gather and store greeks by outer timestep

• VA Porfolio
• Market States

gather

• VA Greeks by timestep

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Optimized Analytics Infrastructure

• - Client adapter requests Service
• - Service Mgr starts/stops/queries Service
  Instance
• Service Instance connects to Client App

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IBM System Blue Gene - Floor Space Efficiency
Advantage vs. Commodity Linux Cluster
Equivalent TFLOPs ¼ floor space ¼ power
consumption
Blue Gene 2 Rack System 11.4 Peak TFLOPs 76.5 sq.
ft. 56 KW Peak Power Consumption
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IBM System Blue Gene Solution - Conclusions

• Blue Gene represents an innovative way to scale
  to multi-teraflops capability
• Leadership performance and price/performance
• Massive scalability
• Efficient packaging drives low power, cooling and
  floor space requirements
• Unique in the market for its balance between
  massive scale-out capacity and preservation of
  familiar programming environments
• Blue Gene is applicable to a wide range of
  computationally intensive workloads such as
  financial instruments pricing, risk analytics,
  monte carlo simulations, etc.
• Programs are in place to ensure Blue Gene
  technology is easily accessible, including
  availability in IBMs Deep Computing Capacity on
  Demand center
• Ongoing Blue Gene RD ensures the vitality of the
  offering

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IBM Virtualization Engine Platform

• IBM portfolio of differentiating virtualization
  capabilities
• Unifying framework for building and managing a
  heterogeneous environment
• Does not require rip and replace hardware and
  software upgrades
• Built to be
• Comprehensive
• Open
• Heterogeneous
• Common skills

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Grid Computing Enabling an On Demand IT
Infrastructure
After Grid
Before Grid
Before Grid

• Siloed Architecture
• Higher (capital operational) costs through
  limited pooling of IT assets across silos
• Challenging cross organization collaboration
• Limited responsiveness due to more manual
  scheduling and provisioning

• Virtualized Infrastructure
• Creates a virtual application operating, storage
  collaboration environment
• Virtualizes application services execution
• Dynamically fulfills requests over a virtual pool
  of system resources
• Offers an adaptive, self-managed, high
  availability operating environment

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MetaCluster Dynamic, application-centric
workload management
Using IBM DirectorsPredictive Failure Analysis

• Optimization of resource usage
• Servers can be consolidated dynamically based on
  usage criteria
• Optimization of performance
• Applications can be scaled up (moved to a more
  potent server)
• Optimization of service availability
• Workloads can be moved pro-actively to a healthy
  resource, upon detection of degradation of system
  resources

PFA
monitoring
app
app
app
app
App
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Why Linux is important to customers

• Linux is an excellent path to On Demand Business
• Integration
• Linux can run alongside the existing operating
  system
• Linux enables the same application to run on many
  different platforms
• Virtualization
• Linux supports one-to-many virtualization
  software and microcode
• Linux supports many-to-one virtualization -
  Clusters, Grids
• Automation - Linux delivers a robust, manageable
  distributed platform
• Linux is about choice and flexibility
• Linux is secure
• Linux is reliable
• Linux drives business goals
• Reduce costs
• Simplification
• Improve application service levels
• Promotes innovation

Source IDC Directions 2005
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IBM Systems AgendaA strategic design for
delivering innovative technology, resources and
skills