Using pool-based evolutionary algorithms for
scalable and asynchronous distributed computing
J. J. Merelo, A. M. Mora, C. M. Fernandes, M. G. Arenas, Anna I. Esparcia-AlczarU. Granada + S2 Grupohttp://geneura.wordpress.com
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What are the ingredients for a massively parallel evolutionary algorithm?
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How can you use a server/backoffice that does (almost) all the work?
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Can you achieve fault-tolerance and asynchrony?
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Pool CRUD
Pools allow create, read, update and delete operations.
Pool == population
Pool == conveyor belt
Fault-tolerantScalable
Implementation matters
Object stores: RDMBSorNoSQL
File synchronization systems
Which frameworks can be used to implement pools?
- Latency+ Concurrency- Lack of control+ Locality of writes
Conclusions
Tradeoff fault-tolerance/scalability.
Difficulty of non-centralized non-asynchronous operation.
Advantages: Availability of frameworks.
Optimal CRUD operations.
Availability of clients.
Choice of languages.
Paradigm mix!
Thanks!
Any question?See you at EvoPar 2013http://goo.gl/LtTCL
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