Storage management in virtual tree machines

Many parallel algorithms, particularly divide-and-conquer algorithms, may be structured as dynamic trees of tasks. In general, as parallelism increases, storage requirements also increase. A sequential program keeps storage requirements small by finishing one task (or procedure invocation) before going on to another, so that the entire task tree is never in existence at any one time. This corresponds to a depth-first expansion of a tree of tasks. On the other hand, a breadth-first expansion often produces a higher degree of parallelism, but also may produce an exponential growth in storage requirements. The resources (processors and memory) of a given system can be matched by alternating between depth-first and breadth-first expansion. The author's approach is to determine how much storage would have been available to a task in a sequential system, and to ensure that at least as much storage is available to the task when it is executed in a distributed system.<
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