Open AccessDATA MINING TO IMPROVE THE EFFICIENCY OF USING THE HYBRILIT HIGH-PERFORMANCE HETEROGENEOUS COMPUTING PLATFORM
Author(s) -
E. Polegaeva,
Daria Priakhina,
O. Streltsova,
D. V. Podgainy
Publication year - 2021
Publication title -
9th international conference "distributed computing and grid technologies in science and education"
Language(s) - English
Resource type - Conference proceedings
DOI - 10.54546/mlit.2021.90.89.001
Subject(s) - computer science , workload , relevance (law) , supercomputer , data mining , data science , distributed computing , operating system , law , political science
The HybriLIT heterogeneous computing platform is part of the Multifunctional Information andComputing Complex of the Meshcheryakov Laboratory of Information Technologies of the JointInstitute for Nuclear Research. An analysis of data on the use of the HybriLIT platform is carried out:special attention is paid to the study of information about the resources used when starting tasks byvarious users and the time of their implementation. The relevance of this study lies in the ability topredict the further workload of the platform based on the analysis obtained, which will enable themore rational and efficient use of not only the available computing resources, but also the resources ofdata storage systems. This paper presents models for predicting the usage of the HybriLIT resourcesbased on data through analysis. Several machine learning methods are compared to choose a modelthat gives the best prediction accuracy.