All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00354524" target="_blank" >RIV/68407700:21230/21:00354524 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-030-85665-6_36" target="_blank" >https://doi.org/10.1007/978-3-030-85665-6_36</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-85665-6_36" target="_blank" >10.1007/978-3-030-85665-6_36</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis

  • Original language description

    Hierarchical clustering is a common tool for simplifica- tion, exploration, and analysis of datasets in many areas of research. For data originating in flow cytometry, a specific variant of agglom- erative clustering based Mahalanobis-average linkage has been shown to produce results better than the common linkages. However, the high complexity of computing the distance limits the applicability of the algorithm to datasets obtained from current equipment. We pro- pose an optimized, GPU-accelerated open-source implementation of the Mahalanobis-average hierarchical clustering that improves the algorithm performance by over two orders of magnitude, thus allowing it to scale to the large datasets. We provide a detailed analysis of the optimiza- tions and collected experimental results that are also portable to other hierarchical clustering algorithms; and demonstrate the use on realistic high-dimensional datasets.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/NV18-08-00385" target="_blank" >NV18-08-00385: Integrative analysis of high-throughput genomics and multiparameter flow cytometry to improve diagnosis and monitoring of childhood acute leukemia</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Euro-Par 2021: Parallel Processing

  • ISBN

    978-3-030-85664-9

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    16

  • Pages from-to

    580-595

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Lisabon

  • Event date

    Aug 30, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article