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I'm not even sure if this is the right place to ask a question like this.

As a part of my MSc thesis, I am doing some parallel algorithm stuff. To put it simply part of the thing that I am doing is evaluating thousands of expression trees in parallel (expressions like sin(exp (x + y) * cos (z))). What I am doing right now is converting these expression trees to Prefix/Postfix expressions and evaluating them using conventional methods (stack, recursion, etc). These are the basic things that we've all been taught in Data Structures and basic Computer Science courses.

I'm wondering if there is anything else to be used instead of expression trees for dealing with expressions. I know that compilers are heavily using expression trees for parsing phase so I'm assuming there are no alternatives to expression trees (or else someone would have used it in a compiler).
Are there any alternative evaluation methods for such expressions (rather than stacks and recursion). Something more "parallel" friendly? Parsing such expression with stack is sequential and will create a bottleneck in parallel systems. (Exotic/weird/theoretic methods -if any- are also acceptable for my work)

Maghoumi
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1 Answers1

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I think that evaluating expression trees is parallelizable, you just don't convert them to the prefix or postfix form.

For example, the tree for the expression you gave would look like this:

   sin
    |
    *
   / \
 exp cos
  |   |
  +   z
 / \
x   y

When you encounter the *, you could evaluate the exp subexpression on one thread and the cos subexpression on another one. (You could use a future here to make the code simpler, assuming your programming language supports them.)

Although if your expressions really are as simple as this one and you have thousands of them, then I don't see any reason why you would need to evaluate a single expression in parallel. Parallelizing on the expressions themselves should be more than enough (e.g. with 1000 expressions and 2 cores, evaluate 500 on one core and the rest on the other core).

svick
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  • Thanks for the answer. The thing is that I over-simplified the scenario. I have anywhere from 8000 to 16000 expression trees which can have a maximum depth of 17 each of which have to be evaluated on hundreds of test cases. To make it more specific, I am solving vision problems using Genetic Programming. CUDA is my parallel platform. Do you think the model you proposed would map well to CUDA's parallel model? – Maghoumi May 23 '13 at 14:09
  • @M2X I don't know anything about CUDA, so I can't help you with that. – svick May 23 '13 at 19:24