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© Platform Computing Inc. 20044
Grid is … SLASLA
Service wait timeService wait time
Run time per service
Run time per service
© Platform Computing Inc. 20045
Grid is …
If you ask me to give you a very clear and simplistic definition of grid
I would say grid computing is distributed computing involving
multiple sites to integrate and support applications and support
collaboration.
© Platform Computing Inc. 20046
Vision:
A single (virtual) computer to run your business
How?
By delivering products that support all types of workloads, applications, standards, resources and computing environments with global enterprise-level scalability and with a common, virtualized infrastructure
How to complete this vision ?
© Platform Computing Inc. 20047
Data
Demand
Compute
Demand
Retail Banking –
Data Mining
(Fast Interconnect ,
Data aware scheduling)
Exotics –
Risk Management
(Load balancing)
Front Office -
Pricing & Hedging
(Low latency task
distribution)
Grid
Sweetspot
Credit Risk
(Fast Interconnect - InfiniBand,
Scalable I/O storage
Data-aware scheduling)
Crossing the Finance Application Chasm
© Platform Computing Inc. 20048
Differences between Grid Computing and Distributed Computing
Power without control is nothing. Grid power of 1000 machines needs to be managed and steered towards business objectives in a systematic, deterministic and predictable fashion
Grid Computing = Distributed Computing + resource and workload management in terms of:
Resource virtualization Resource ownership and sharing Dynamic resource allocation Resource monitoring, control, failover, and troubleshooting Guaranteed SLA (Service Level Agreement) management Workload scheduling and prioritization Load balance High reliability and availability, robustness, resilience, and failover Performance and scalability in a large grid Workload execution monitoring, control, and troubleshooting Resource and workload usage collection, reporting, and accounting
© Platform Computing Inc. 20049
What are the supportive concepts & technologies
A Virtualized IT environment
Grid Virtualization Strengths
Pool (Virtualize) heterogeneous resources
Allocate and manage resources based on Policy
Server Virtualization Strengths
Partition server into virtual servers that provide a secure “container” for applications.
Data virtualization Strenghts
Data access transparency
.NET Application Virtualization Strengths
Rapid development
Improved operation & maintanability
Agile architecture
© Platform Computing Inc. 200410
Solaris Windows
zLinux
LinuxAIX Windows
Oracle DB2 SQL
Application BApplication A Application C
Legacy Stovepipes
Avg. Utilizatio
n Rate
40%
Avg. Utilizatio
n Rate
40%
Avg. Utilizatio
n Rate
2-5%
Avg. Utilizatio
n Rate
2-5%
Avg. Utilizatio
n Rate
10%
Avg. Utilizatio
n Rate
10%
Avg. Utilization
Rate
10%
Avg. Utilization
Rate
10%
Avg. Utilization
Rate
52%
Avg. Utilization
Rate
52%
Avg. Utilization
Rate
60%
Avg. Utilization
Rate
60%
Avg. Utilization
Rate
10%
Avg. Utilization
Rate
10%
15 Hours15 Hours 8 Hours8 Hours 2 Hours2 Hours
Grid Computing is about virtualizing and sharing resources
Decoupling applications from infrastructure
© Platform Computing Inc. 200411
Grid Computing is about virtualizing and sharing resources
Decoupling applications from infrastructure
Solaris Windows
zLinux
LinuxAIX Windows
Results returnedand integrated into
application(s)
Scheduler distributes application
workload(s) to CPUs
Oracle DB2 SQL
Application BApplication A Application C
© Platform Computing Inc. 200412
Scheduler distributes application
workload(s) to CPUs
Grid Computing is about virtualizing and sharing resources
Decoupling applications from infrastructure
Solaris Windows
zLinux
LinuxAIX Windows
Results returnedand integrated into
application(s)
Scheduler distributes application
workload(s) to CPUs
Oracle DB2 SQL
Application BApplication A Application C
Collaboration& Resiliency
© Platform Computing Inc. 200413
Enterprise Grid Context
WorkloadManagers
Applications
Users
EnterpriseResources
BI .NET DB’s ERP CRM VM’s
ApplicationManagers
BatchProcess
FlowSOAParallel
HPC MDA EDA CAE Risk
“Acceleration” Applications
Business Applications
Grid Management Console Windows 2003 Server Resource Pool
© Platform Computing Inc. 200414
Is this a Myth ?
Shared application interface, scheduling system, and virtual resource pool
Enables sharing and reuse of knowledge, data, resources, and analytics engines
Shared resource pool is dynamically partitioned into “virtual clusters”
Application interface and scheduling system are now commercially supported, fully documented software
Low-cost off-the-shelf hardware replaces expensive SMP boxes
Multi-asset models can now be run by one user, able to access any analytics engines and resources needed, governed by priority-driven policies
© Platform Computing Inc. 200415
Policy Evolution – Supporting the spectrum of ownership vs.sharing
Model 1: Limits
Put hard limits around each consumer
Virtualize the resources instead of dedicating fixed resources
Guaranteed capacity in event of failures
A B
C
A B
CA
B
Silo Model Enterprise Sharing Model Utility Computing Model
C
Model 2: Borrow/Lend
Each consumer has “owned” capacity
Each consumer can specify lend and borrowing limits around that owned capacity
Model 3:Fairshare
Consumer has % of capacity at each level relative to others
“Owned” capacity is 0 for consumer
Capacity allocated based on need and constrained by shares
Model 4: Economic
Consumers specify budget $
Resource usage has cost ($/cpu-hr, $KB/hr)
System optimizes budget allocations & resource usage driven by application SLA (determined in WLM)
100% ownership of resources by
Consumers
Capped SLA guarantees when peak
reached
- Some minimum ownership of resources
- Ability to share from pool or others
- 0% ownership of resources by
consumer.
- All owned by service provider (IB
- Consumer Pay for usage only
- SLAs guaranteed in exchange for
resource ownership
© Platform Computing Inc. 200417
Platform Symphony – Road to Grid and Beyond
Today
Start Small (1 or 2 apps)
Grow the grid and measure ROI
Tomorrow
As you grow, throw more apps or complex jobs at the grid
Platform Symphony is designed to grow with you
Supporting all workload and enterprise-class Scalability
Ultimately future proofing your IT investments via a heterogeneous, standards-based, single, common
infrastructure solution - The Virtual Execution Machine (VEM)
© Platform Computing Inc. 200418
Today FSI
Policy Evolution – Supporting the spectrum of ownership vs.sharing
Model 1: Limits
Put hard limits around each consumer
Virtualize the resources instead of dedicating fixed resources
Guaranteed capacity in event of failures
A B
C
A B
CA
B
Silo Model Enterprise Sharing Model Utility Computing Model
C
Model 2: Borrow/Lend
Each consumer has “owned” capacity
Each consumer can specify lend and borrowing limits around that owned capacity
Model 3:Fairshare
Consumer has % of capacity at each level relative to others
“Owned” capacity is 0 for consumer
Capacity allocated based on need and constrained by shares
Model 4: Economic
Consumers specify budget $
Resource usage has cost ($/cpu-hr, $KB/hr)
System optimizes budget allocations & resource usage driven by application SLA (determined in WLM)
100% ownership of resources by
Consumers
Capped SLA guarantees when peak
reached
- Some minimum ownership of resources
- Ability to share from pool or others
- 0% ownership of resources by
consumer.
- All owned by service provider (IB
- Consumer Pay for usage only
- SLAs guaranteed in exchange for
resource ownership
TodayEDA,IM
© Platform Computing Inc. 200419
Summit VaR Cluster 148 BladesSym 2.1.3
Summit VaR Cluster 248 Blades
Summit VaR Cluster 144 CPUsLognes
Sym 2.1.3
Summit VaRSymphony 2.1.3
Sophis PricingSymphony 2.1.3
Sophis PortfolioSymphony 2.1.3
Compute nodes
Windows 2000
Compute nodes
Windows 2000
Site CSite BSite A
Customer A Architecture
© Platform Computing Inc. 200420
Summit VaR Sym 2.1.3
HybridsSymphony 2.1.3
Compute nodes
Windows 2003
Site DSite CSite B
Customer B Architecture
HybridsSymphony 2.1.3
Compute nodes
Windows 2003
UATProduction
Summit VaR Sym 2.1.3 Summit VaR
Sym 2.1.3
Summit VaR Sym 2.1.3
Site A
WLMWLM WLM
WLM
© Platform Computing Inc. 200421
Customer B – Application focus
Market Data
Work
Web Sphere
Job Server
Job Arrives, contains list of deals
Excel
Job Serverdecomposes
deals into tasks
Excel gets market dataAfter new task arrives
Symphony
Job Server isSymphony Client
Tasks sent to Symphony
Symphony starts ExcelService which starts Excel,. Each task contains the deal string used for the calculation. ExcelService calls the relevant Excel method to start the computation.
Excel Excel Excel
Results returned to client
Tasks distributed to available compute hosts and results returned to Symphony
© Platform Computing Inc. 200422
Summit VaR BATCH Partition
Summit VaRSUMMIT_VaR_H
Sophis PricingSOPHIS_PRICING
Sophis PortfolioSOPHIS_PORTFOLIO
Compute nodesApplication Client
Platform Symphony 2.2.1
Brokerage of ressources
1 Dedicated Service Partition per Application
SLA per application with Lending and Borrowing ENABLED
Contingency SiteCustomer A target (End of June)
Windows machines resource pool
© Platform Computing Inc. 200423
Customer C Architecture
Project A
Windows 2000/2003 Compute Nodes
Exotic Derivatives Pricers
C++
100s CPUs actives today
1000s CPUs by Q1CY2005
Project B
Windows 2000/2003 Compute Nodes
.NET
100 CPUs actives
Project C
Windows 2000/2003 Compute Nodes
.NET
600-800 CPUs by Q1CY2005
Compute farms
© Platform Computing Inc. 200424
Customer C – Desktop Support
SSMMapping FS
FS
WLMMapping FS
Mapping FSCompute Node
Dedicated Workstation
Running Symphony
Mapping FS
DR Site with dedicated positions
© Platform Computing Inc. 200425
Customer C
Grid A
Grid ManagementConsole
Platform Policy Engine and Scheduler
Shared Storage
. . . VMwareDesktop Farm
In Disaster Recovery
Platform Grid
Virtual Machines
. . . Grid B
Grid C
Triggered actions
Compute farms
© Platform Computing Inc. 200426
Customer C - Step4
SSMMapping FS
FS
WLMMapping FS
Mapping FSCompute Node
Dedicated Workstation
Running Symphony
NO FS Dependency
CORE Building workstations
© Platform Computing Inc. 200427
Customer C – Final Step
Pool Compute farm
A B C
Disaster Recovery Desktop
Opportunistic CPU stealing
© Platform Computing Inc. 200428
JPMorgan Chase
Silos of resources and applications supporting different risk management apps
No sharing or collaboration of knowledge, data, resources, or analytics engines
Over-provisioning of hardware for peak in each silo
Unstable and poorly documented home-grown distribution software and application interfaces
Expensive SMP servers needed to support spikes in workload
Multi-asset (cross-silo) models had to be run and assembled manually
© Platform Computing Inc. 200431
Four Stages of Enterprise Grid
LEVEL TWOConnected, Multi-Domains
There is an agreement between domains to share compute resources according to owner controlled policies. Charge-back manager tracks usage and allocates costs
LEVEL ONESingle or Isolated Domains
Each ”Domain” – project, work group or LoB, etc. controls – its own processes, data and compute resources within an enterprise, behind the firewall.
LEVEL THREECross-enterprise, Compute Backbone”
• Each project, work group or LoB controls its own processes, data and compute resources, behind the firewall• Compute resources are share according to owner controlled policies• For maximum speed and efficiency all domains are linked together• Sophisticated charge-back manager tracks usage and allocates costs.
Value
TIME
© Platform Computing Inc. 200432
LEVEL FOURInternal Utility/Enterprise Utility
• Domains own no or almost compute resources of their own but pay for the use of any that they require.
• IT is charged with buying sufficient compute resources to meet demand from all parties.
• Domains establish priority requirements and are charged only for actual use.
•Sophisticated charge-back manager tracks usage and allocates costs.
• Sophisticated modeling analysis predicts volume/time requirements
Value
Time
Four Stages of Enterprise Grid
© Platform Computing Inc. 200433
Partner Grid - beyond the firewall
Value
Time
LEVEL FIVEInter-Enterprise
Each project, work group or LoB controls its own processes, data and compute resources within an enterprise, behind the firewall and interacts with other base “domains”
But, there is an agreement to share computer resources with partners in other enterprises beyond the firewall.
© Platform Computing Inc. 200434
LEVEL SIXUtility Grid Computing
Business owners own little or no hardware. Buy from utility on an as needed basis. Utility serves many customers; efficiencies drive down costs and drive up scale
Utility Grid