1. Parallel algorithms for expression evaluation Simultaneous substitution method (SimSub)

2. Simultaneous Substitutions Method (SimSub) x = Expression(y) and y = Expression1 a variable y can be substituted by its expression or by its value if it is known (if Expression1 is a constant) assume we have a sequence of expressions defining variables, each expression is of a constant size variables are numbered and i-th expression depends only on variables with numbers smaller than i e.g. x1=4 x2=x1+5 x3=x1+x2*7 x4=x2*x3

3. One parallel step: for each expression substitute its variables by their expression if it is safe; safe means that corresponding expression has at most one variable Example: summing the numbers 2, 1, 3, 2, 1, 3, 2, 1 we can write a sequential program x1 = 2; x2 = x1+1; x3 = x2+3; x4 = x3+2; x5 = x4+1; x6 = x5+3; x7 = x6+2 after parallel step 1 x1 = 2; x2 = 3; x3 = x1+4; x4 = x2+5; x5 = x3+3; x6 = x4+4; x7 = x5+5 after parallel step 2 x1 = 2; x2 = 3; x3 = 6; x4 = 8; x5 = x1+7; x6 = x2+9; x7 = x3+8 after parallel step 2 x1 = 2; x2 = 3; x3 = 6; x4 = 8; x5 = 9; x6 = 12; x7 = 14 output = sum = x7 In this way we can sum 1024 numbers in 10 rounds

4. Tree-contraction ======================================== Parallel algorithms related to expression evaluation correspond to parallel algorithmic technique called tree-contraction =============================================== Tree-contraction is used in parallel expression evaluation Since the structure of a expression is a tree there are different tree-contraction techniques Basic operations are: - redirecting edges of the tree - removing nodes marking (pebbling) nodes - creating additional edges the final aim is to guarantee that logarithmic number of contractions is sufficient

5. Tree-contraction related to SimSub algorithm

6. Example Substitutions method works in O(log n) time. In each iteration the active tree is reduced by 1/3 at least. The active tree consists of nodes relevant to the output computation, The root is the output variable (the last one).

7. F n is the smallest tree which needs n iterations in tree contraction related to SimSub algorithm

8. How the SimSub algorithm works for general graphs ? sometimes very poor  (e.g. when computing Fibonacci numbers) generally with n processors we need n-1 iterations -only one processor really works each time, so the same can be done with a single processor

9. SimSub will terminate after O(log (tree-size(graph)) iterations for the dependency graph of Fibonacci numbers tree-size (number of paths) is exponential. There is alternative parallel method SimSub’, see dynamic dependency graphs. programming problems, when we can deal effectively with such types of

10. Other tree contraction method: parallel pebble game (PPG) Parallel pebble game (PPG) works for full binary trees, full means each father has exactly 2 sons