scala/akka/stm design for large shared state?

I am new to Scala and Akka and am considering using it to solve a problem. Suppose I have a calculation engine (that searches for a solution). I'd like to parallelize that search both across cpus and across nodes by giving each cpu on each node its own engine instance.

The engine inputs consist of a small number of scalar inputs and a very large hash table. Each engine instance would use its scalar inputs to make some small local change to the hash table, calculate a goodness, then discard its changes (they do not need to be committed/seen by any other engine instance). The goodness value would be returned to some coordinator that would choose among the results.

I was reading some about the STM TransactionalMap as a vehicle for shared state. This seems ideal, but I don't really see any complete examples using it as shared state.

Questions:

• Does the actor/stm model seem right for this problem?
• Can you show a specific example of how to distribute the shared state? (is it Ref[TransactionalMap[,]] as a message?
• Is there anything different about distributing the s开发者_运维问答hared state within a node as opposed to across different nodes?

Inquiring Minds Want to Know,

Allan

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In terms of handling shared memory it doesn't sound like STM would be the right fit here because you don't want the changes made in engine instances to commit to the shared copy of the hash table.

Instead, an immutable HashMap might be a better fit. The elements that do not change in the map can be shared by the engine instances with only the differences in each map taking additional memory space.

The actor model would fit very well what you want to do. Set up one actor for each engine instance you want and pass it a message with the scalar values and the hashmap. Then have it return the results to the coordinator.