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”

TypeCNN: CNN Development Framework With Flexible Data Types

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU132056" target="_blank" >RIV/00216305:26230/19:PU132056 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fit.vut.cz/research/publication/11854/" target="_blank" >https://www.fit.vut.cz/research/publication/11854/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.23919/DATE.2019.8714855" target="_blank" >10.23919/DATE.2019.8714855</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    TypeCNN: CNN Development Framework With Flexible Data Types

  • Original language description

    The rapid progress in artificial intelligence technologies based on deep and convolutional neural networks (CNN) has led to an enormous interest in efficient implementations of neural networks in embedded devices and hardware. We present a new software framework for the development of (approximate) convolutional neural networks in which the user can define and use various data types for forward (inference) procedure, backward (training) procedure and weights. Moreover, non-standard arithmetic operations such as approximate multipliers can easily be integrated into the CNN under design. This flexibility enables to analyze the impact of chosen data types and non-standard arithmetic operations on CNN training and inference efficiency. The framework was implemented in C++ and evaluated using several case studies. 

  • 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/GA19-10137S" target="_blank" >GA19-10137S: Designing and exploiting libraries of approximate circuits</a><br>

  • Continuities

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

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Design, Automation and Test in Europe Conference

  • ISBN

    978-3-9819263-2-3

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    292-295

  • Publisher name

    European Design and Automation Association

  • Place of publication

    Florence

  • Event location

    Florencie

  • Event date

    Mar 25, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000470666100053