Approximating Clustering for Memory Management and request processing
Databases
2023-08-23 v1
Abstract
Clustering is a crucial tool for analyzing data in virtually every scientific and engineering discipline. There are more scalable solutions framed to enable time and space clustering for the future large-scale data analyses. As a result, hardware and software innovations that can significantly improve data efficiency and performance of the data clustering techniques are necessary to make the future large-scale data analysis practical. This paper proposes a novel mechanism for computing bit-serial medians. We propose a novel method, two-parameter terms that enables in computation within the data arrays
Cite
@article{arxiv.2308.11008,
title = {Approximating Clustering for Memory Management and request processing},
author = {D. D. D. Suribabu and T. Hitendra Sarma and B. Eswar Reddy},
journal= {arXiv preprint arXiv:2308.11008},
year = {2023}
}