October 2000
Intermediate to advanced
288 pages
9h 22m
English
book
Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
by Albert Y. Zomaya, Fikret Ercal, Stephan Olariu
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6.2 PROBLEM DESCRIPTIONS
6.2.1 Static Matching and Scheduling of Subtasks
There are many open research problems in the HC field [36, 46]. To isolate and focus on the mapping problem, researchers typically make assumptions about other components of an overall HC system (e.g., [45, 48]). This subsection considers the assumptions made in [58] for the static mapping of subtasks.
It is assumed that the application task is written in some machine-independent language (e.g., [59]). It is also assumed that an application task is decomposed into multiple subtasks and the data dependencies among them are known and are represented by a directed acyclic graph (DAG). If intermachine data transfers are data dependent, then some set of expected data transfers must be assumed. The estimated expected execution time for each subtask on each machine is assumed to be known a priori. Finding the estimated expected execution times for subtasks is another research problem, which is beyond the scope of this chapter. Approaches based on task profiling and analytical benchmarking are surveyed in [32, 46, 47]. The HC system is assumed to have operating system support for executing each subtask on the machine it is assigned and for performing intermachine data transfers as scheduled by this genetic-algorithm-based approach.
In the type of HC system considered here, an application task is decomposed into a set of subtasks S. Define |S| to be the number of subtasks in the set, and si to be the ith subtask 0 ...
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