The hydrodynamic approach to modeling astrophysics problems has several disadvantages in terms of the implementation of a parallel computing code. One of the main drawbacks is the low arithmetic intensity of the methods that implement the computational problem. This peculiarity produces the performance limitation associated with the performance limitations of the DRAM memory of high-performance computing systems. One of the solutions to this problem is data structuring based on the characteristics of processors and memory of a computer system on which supercomputer simulation is to be carried out. In this work, the authors use the specialized Intel SDLT library, which allows you to organize data in a special way that can help the compiler to vectorize a computational code for Intel server processors. The use of this library made it possible to speed up the computational code by fifty times, and for the first time bring the performance of some code functions to the performance limits of server processors on vector FMA instructions.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subtitle of host publicationbook
EditorsV. Voevodin, S. Sobolev, M. Yakobovskiy, R. Shagaliev
PublisherSpringer
ChapterChapter 21
Pages271-284
Number of pages14
Volume14388 LNCS
ISBN (Print)978-303149431-4
DOIs
Publication statusPublished - 5 Jan 2024

Publication series

NameSupercomputing
Volume14388
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

    ASJC Scopus subject areas

  • General Computer Science
  • Theoretical Computer Science

ID: 51655911