CLUSTER DETECTION USING GA-KNN CONJUNCTION APPROACH | Abstract

ISSN: 2229-371X

Research Article Open Access

CLUSTER DETECTION USING GA-KNN CONJUNCTION APPROACH

Abstract

The market of embedded systems is spreading faster than that of information technology. Mostly, the segments of embedded systems are consumer markets, with very short product lifetimes and short market windows. Hence, time-to-market is an important factor. Cutting down the time to market for products that became more and more complex is possible through “re-use”. Another important characteristics of the embedded system market is the ease of incorporating late design changes, i.e. flexibility of the target technology, This led to the use of processors in embedded systems. This in turn led to the use of embedded software. Traditional compiler technologies were not adequate for applications and architectures of embedded systems; this led to the development of “retargetable compilers”. A compiler is said to be retargetable, if it can be applied to a range of different target processors, by re-using most of the code. This means that target model cannot be an implicit part, but must be specified explicitly. In this paper, we have described the development of a retargetable compiler. The developed methodology has been used to generate and validate codes for MIPS and ARM processors. The objective of this research is to develop a retargetable compiler that can generate efficient code in terms of code size, cycle count and retargetability efforts for a wide rnge of processors

Manoj Kumar Rawat and Dr. D.C.Upadhyay

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