High Performance Geo-SimulationsSaulo Henrique Cabral Silva

Tiago Garcia de Senna Carneiro*

TerraLAB – Laboratory for Earh System Modeling and SimulationComputer Science Department

Federal University of Ouro Preto

GeoInfo 2013

Challenges• Modelers have few programming expertise

– Problem partition into several processes?– Processes communication?– Processes synchronization?

• What is the design goal: Scalability or Performance?– Global scheduling scalabitity– Local scheduling high performance

• How to parallelize/distribute workload?– Model architecture can be defined by:

• Application domain area (the phenomenon being modeled)• Chosen modeling paradigm: CA, multiagente, DEVS, etc

– Which load balancing strategy to use?• Agents clusters• Dynamic and adaptative

• How to verify models with no influence of concurrency control rules?

function execAgentPred(i) predatores[i]:execute() end

function execAgentPrey(i) preys[i]:execute()

end

for i = 1, #predatores do --HPA PARALLEL

execAgentPred(i) end --HPA JOINALL for i = 1, #preys do

--HPA PARALLEL execAgentPrey(i) end --HPA JOINALL

Annotations - API:

HPA PARALLEL HPA JOIN function_name HPA JOINALL HPA ACQUIRE resource_name HPA RELEASE resource_name

Flexibility through annotation: Prey-predator model

Scalability through load balance: Bag of Tasks

Discussion• TerraME HPA scales well when the modeler designs efficient

parallel solutions

– 90% of linear speedup with 8 processors (prey predator model)

– 35% of linear speedup with 8 processors (TROLL model)

EXP1: Spatially-explicit prey predator model

• Species compete, evolve and disperse, in order to seek resources to support their struggle for their existence

• Each cell has a population of prey and a population of predators

• Model executes in two steps:– First, predators are simulated in parallel– Then, prey are simulated in parallel

Distributed (Dmason) versus Parallel (TerraME)

Agents Clusters versus Load Balancing

EXP2: 3D tropical rain forest growth model - TROLL

• TROLL model simulates a 3D environment where:– Individual trees compete for light– Seed dispersal by wind– Trees interacts falling over others and forming gaps– …

• Adopted partitioning strategy: each layer (h, h-1, h-2, …) is simulated in parallel

• Higher layers are simulated before lower layers