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IBM System Blue Gene® . Ultrascaling and Power Efficiency for Computational Advantage in Financial Services . Collaborative Innovation. Collaborative Innovation. Better integrate business processes with IT. Introduce new applications and systems into existing IT infrastructure more easily.

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ibm system blue gene

IBM System Blue Gene®

Ultrascaling and Power Efficiency for Computational Advantage in Financial Services

ibm systems agenda a strategic design for delivering innovative technology resources and skills

Collaborative

Innovation

Collaborative

Innovation

Better integrate business processes with IT

Introduce new applications and systems into existing IT infrastructure more easily

Openness

Openness

Maintain a flexible infrastructure to improve IT systems utilization and productivity

Virtualization

Virtualization

Provide better access to information

Reduce or mitigate business operations risk

Technology

Innovation

that Matters

Technology

Innovation

that Matters

IBM Systems AgendaA strategic design for delivering innovative technology, resources and skills
ibm system blue gene3

System

64 Racks, 64x32x32

Rack

32 Node Cards, 8x8x16

Node Card

(32 Chips, 4x4x2)

16 compute, 0-2 I/O cards

180/360 TF/s

32 TB

Dual PowerPC®

System-on-Chip

Compute Card

2 Chips, 1x2x1

2.8/5.6 TF/s

512 GB

Chip

2 processors

90/180 GF/s

16 GB

5.6/11.2 GF/s

1.0 GB

2.8/5.6 GF/s

4 MB

IBM System Blue Gene®

Optimized for scalability, bandwidth, and massive data handling while consuming a fraction of the power and floor space required by today’s 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 one–to-all communications

Gigabit Ethernet for file I/O,

host interface, control and

monitoring

Up to 131,072 PowerPC® CPUs

Up to 360 peak TeraFLOPS

slide4

Technique: Monte Carlo simulation

  • Window Tolerance: 4-5 hours
  • Previous SMP implementation:
  • 100,000 scenarios
  • ~5,700 min. = 95 hours (data + compute)
  • IBM Blue Gene Result
  • (128 compute nodes)
  • 100,000 scenarios
  • ~23 min. (15 min. data, 8 min. compute)

Smoothed Expected

Profit-Loss distributionover time horizon

95 hours

Current Portfolio value

Expected Portfolio meanover time horizon

VaR Quantileover time horizon

~23 min

Value at Risk

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.
highly parallelized and efficient i o intensive data file broadcasts
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

example variable annuities capital reserve calculation using nested stochastics for 360 time steps

Time t

BG 1

BG 1

BG 1

BG 2

BG 2

BG 2

BG 3

BG 3

BG 3

BG 4

BG 4

BG 4

  • Calculate Approx. Risk Neutral value of VA portfolio
    • Monte Carlo simulation of asset valuations to horizon
    • VA cash flows contingent on account valuation and market returns

Time t+1

Time t+2

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
services implementation

BG

BG

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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
optimized analytics infrastructure
Optimized Analytics Infrastructure
  • - Client adapter requests Service
  • - Service Mgr starts/stops/queries Service Instance
  • Service Instance connects to Client App
ibm system blue gene floor space efficiency advantage vs commodity linux cluster

Intel Xeon

Intel Xeon

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42 Nodes

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570

GFlops

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Intel® Xeon®

20 Rack System

11.4 Peak TFLOPs

315 sq. ft.

210 KW Peak Power Consumption

Intel Xeon

Twenty Rack System

11.4 Peak

TFlops

315 Square Feet

210 KW Peak Power Consumption

Intel Xeon

Intel Xeon

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Grid Setting: 0.05x0.05; Scale: 1.0" / grid unit

Grid Setting: 0.05x0.05; Scale: 1.0" / grid unit

IBM System Blue Gene® - Floor Space Efficiency Advantagevs. 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

ibm system blue gene solution conclusions
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 IBM’s Deep Computing Capacity on Demand center
  • Ongoing Blue Gene R&D ensures the vitality of the offering
ibm virtualization engine platform

Standards and Open Interfaces

Virtual Access

Virtual Management

Servers

Networks

Storage

Service Oriented Infrastructure

Leveraging Open Standards and Partners

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
grid computing enabling an on demand it infrastructure

Grid Middleware

Grid Computing: Enabling an On Demand IT Infrastructure

Before Grid

After 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
metacluster dynamic application centric workload management

PFA

monitoring

Migrate!

app

MetaCluster Dynamic, application-centric workload management
  • 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

Using IBM Director’sPredictive Failure Analysis

PFA

monitoring

app

app

app

app

App

why linux is important to customers

IBM Global Services

xSeries

zSeries/z9

pSeries/p5

BladeCenter

iSeries/i5

OpenPower

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

ibm systems agenda a strategic design for delivering innovative technology resources and skills15

Collaborative

Innovation

Collaborative

Innovation

Cell

– specific solutions for industries with high performance requirements.

Linux, Apache, Globus

-- engaging with the open-source community to deliver leading-edge business solutions.

Openness

Openness

OAI, MetaCluster, Xen

–robust, reliable, flexible computing environments to respond to changing needs.

Virtualization

Virtualization

GPFS -- parallel filesystems for fastest IO

Blue Gene – supercomputer technologies for real business needs

Technology

Innovation

that Matters

Technology

Innovation

that Matters

IBM Systems AgendaA strategic design for delivering innovative technology, resources and skills
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