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Clustering is a crucial tool for analyzing data in virtually every scientificand engineering discipline. There are more scalable solutions framed to enabletime and space clustering for the future large-scale data analyses. As aresult, hardware and software innovations that can significantly improve dataefficiency and performance of the data clustering techniques are necessary tomake the future large-scale data analysis practical. This paper proposes anovel mechanism for computing bit-serial medians. We propose a novel method,two-parameter terms that enables in computation within the data arrays

Approximating Clustering for Memory Management and request processing