Resource estimation for heterogeneous computing

  • Authors:
  • Mary M. Eshaghian;Ying-Chieh Wu

  • Affiliations:
  • -;-

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 1997

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Abstract

Code-profiling is the process of determining the types of codes found in a given heterogeneous task. Once this information is available, it is desirable to know how many processors are needed for each of the code types. In this paper, we propose two methods for estimating the minimum number of processors required for each of these code types. The first method involves making use of task compatibility graphs. We show that a task compatibility graph can be generated by analyzing certain compatible relations between task module pairs of a given task flow graph. We define the resource (processor) minimization problem therefore to be equivalent to finding the minimal number of cliques that cover the task compatibility graph, or to finding the minimal number of colors that color the vertices of its complement graph, called task conflict graph. We solve this problem using a greedy approach in O(|V|log|V||E|) time, where |V| and |E| are the number of vertices and edges of the task compatibility graph. We further show that for three special types of task compatibility graphs, optimal solution can be obtained in polynomial time. The second method studied in this paper uses the Cluster-M methodology for estimating the minimum number of processors. Examples are shown to compare the estimated results obtained using different techniques.