PicsouGrid Viet-Dung DOAN. Agenda Motivation PicsouGrid’s architecture –Pricing scenarios...
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Transcript of PicsouGrid Viet-Dung DOAN. Agenda Motivation PicsouGrid’s architecture –Pricing scenarios...
PicsouGridPicsouGrid
Viet-Dung DOANViet-Dung DOAN
AgendaAgenda
• Motivation• PicsouGrid’s architecture
– Pricing scenarios
• PicsouGrid’s properties– Load balancing– Fault tolerance
• Perspectives
Motivation : Option Pricing in FinanceMotivation : Option Pricing in Finance
• “Options” = a contract where the owner has the right but not the obligation to exercise a feature of the contract on a future date
→ one of the main instrument of financial risk management
• for multidimensional underlying assets or complex payoffs : numerical simulations are required
→ in this work: Monte Carlo methods
Motivation : Option Pricing in FinanceMotivation : Option Pricing in Finance
• The underlying asset’s price is calculated as a stochastic value
S = f(N(0,1))
• The option’s price
P = E[S]
• Expectation of a stochastic values S is the sum of the probability of each possible value S (probability theory).
PicsouGrid Scenario No1 (1)PicsouGrid Scenario No1 (1)
• This scenario is used for pricing the Europeans options, their exotics forms and the portfolio's risk management (pricing the value at risk).
PicsouGrid Scenario No1 (2)PicsouGrid Scenario No1 (2)
+ reserve pool of PCs (ε%)
Client Server
SubServer
SubServer
Worker
ProActive Worker
Worker
BD
classical n-tiers architectureProActive
ProActive
ProActive
BD
JavaSpacevirtualshared
memory
(on demand)
PicsouGrid Scenario No2 (1)PicsouGrid Scenario No2 (1)
• More communication.• This scenario is used for pricing the Americans
options, their exotics forms and the Greeks values.
PicsouGrid Scenario No2 (2)PicsouGrid Scenario No2 (2)
+ reserve pool of PCs (ε%)
Client Server
SubServer
SubServer
Worker
ProActive Worker
Worker
BD
classical n-tiers architectureProActive
ProActive
ProActive
BD
JavaSpacevirtualshared
memory
(on demand)
Load Balancing (1)Load Balancing (1)
• Full static strategy (for homogeneous Grid):distribute larger tasks to worker (N/nbWorkers)
+ less communications
– not suited for heterogeneous workers
• Traditional semi-dynamic (for heterogeneous Grid):each financial computation is split into N elementary tasks statically
distributed across the SubServers
each worker consume an elementary task from its SubServer until no more tasks are available
• Dynamic aggressive (for certain algorithms):distribute more tasks than necessary, stop as soon as N results are
collected (e.g Monte Carlo method)– more communications
+ takes advantage of fastest machines
Load Balancing (2)Load Balancing (2)
• influence of tasks size:– small:
– high communications+ low recovery overhead
– big:+ few communications– recovery overhead can be as big as the task execution time
Fault ToleranceFault Tolerance
• FT mechanisms from underlying middleware:– JavaSpace:
• transactions: protection from worker process failure• activatable service and persistent space: protection from JavaSpace
process failure– ProActive:
• check-pointing protocol to restart the whole application from a previous global state in case of failure
→ protect from failure of middleware process
• PicsouGrid FT mechanisms:– hear-beat to detect failure– subservers checkpoint workers, server checkpoints subservers– redeploy failing worker on reserve PC if available– redeploy failing subserver on reserve PC if available, server or
on server otherwise
→ protect from machine failure
Performances on Sound GridPerformances on Sound Grid
• interesting speed-up up to 140 workers• subServers are bottleneck points: hierarchical
architecture leads to better scaling• overhead of long-distance communications (4
sites versus 1) is noticeable
PicsouGrid Fault Tolerance PerformancesPicsouGrid Fault Tolerance Performances
• Experiment:– test: 3 SubServers, 6 Workers per SubServer– disconnect machines right before they return a result– use reserve PCs– measured overhead:
• Conclusions:– faults are detected– workers and subServers are replaced and there is no need to restart the
computation from the beginning, subsequent computations perform without overhead
– recovery overhead is acceptable, higher for subServers than for workers
+ 11.865.52 SubServers
+ 9.663.31 SubServer
+ 15.068.76 Workers
+ 2.456.12 Workers
+ 0.454.11 Worker
-53.7no failure
Worse Overhead (s)Average Execution Time (s)
Simultaneous Failures
most likely failure casedealt with using only ξ reserve PC
Failures and Aggressive Load BalancingFailures and Aggressive Load Balancing
• → need to automatically adjust the task size
PerspectivesPerspectives• Perspectives:
– to build an abstract interface between PicsouGrid and the algorithms.
– to experiment with more tightly-coupled applications.– to allow application, PiscouGrid and underlying
middleware layers to collaborate to improve fault tolerance.
– to dynamically discover and integrate available resources (PiscouGrid).
– to allow pluggin of industrial clients and libraries (e.g. Pricing Partners toolkit).