A balanced layered allocation scheme for hypercube based dataflow systems

The authors propose a method called the balanced layered allocation scheme (BLAS) which utilizes heuristic rules, to find a balance between computation and communication costs in hypercube based dataflow systems. The central idea of this method is to arrange the nodes of a dataflow graph into layers that have a one-to-one correspondence with processors in a hypercube. During the allocation, CP (critical path) and LDP (longest directed path) heuristics determine the set of nodes which are to be assigned to processors. Each set of nodes is assigned in an iterative fashion to every possible layer. In this manner the effects of execution times and communication costs can be weighted against each other for every possible layer assignment. Sets of nodes are then assigned to the layer that yields the earliest completion time of the program. Simulation studies indicate that the proposed allocation scheme is effective in reducing communication overhead and thus the overall execution time of a program distribution on a hypercube dataflow computer. Overall, the BLAS showed promising improvements over the VL (vertically layered) allocation scheme