Selection of Optimal Computing Platforms through the Suitability Measure

Selection of spaceborne computing platforms requires balance among several competing factors. Traditional performance analysis techniques are ill-suited for this purpose due to their overriding concern with runtime. The suitability measure is a new approach that quantifies the match between a computing platform and a program. It analyzes a program at the opcode and control flow levels, and compares this to a machine's capability to support the unique characteristics of the program. In this paper we develop the suitability measure and a series of program analysis methods. Experimental results confirm that machines that provide a better match to the program yield a higher suitability score. We prove that loops provide the only contribution to the suitability value, and also that the number of loop iterations is irrelevant, leading to the conclusion that a single pass through a loop is sufficient to derive a suitability value.