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Automation of Processor Verification Using Recurrent Neural Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU130683" target="_blank" >RIV/00216305:26230/17:PU130683 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8396943" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8396943</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/MTV.2017.15" target="_blank" >10.1109/MTV.2017.15</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automation of Processor Verification Using Recurrent Neural Networks

  • Original language description

    When  considering  simulation-based  verification  of processors, the current trend is to generate stimuli using pseudo-random  generators  (PRGs),  apply  them  to  the  processor  inputs and monitor the achieved coverage of its functionality in order to determine  verification  completeness.  Stimuli  can  have  different forms, for example, they can be represented by bit vectors applied to  the  input  ports  of  the  processor  or  by  programs  that  are loaded  directly  into  the  program  memory.  In  this  paper,  we propose  a  new  technique  dynamically  altering  constraints  for PRG  via  recurrent  neural  network,  which  receives  a  coverage feedback from the simulation of design under verification. For the demonstration purposes we used processors provided by Codasip as  their  coverage  state  space  is  reasonably  big  and  differs  for various  kinds  of  processors.  Nevertheless,  techniques  presented in  this  paper  are  widely  applicable.  The  results  of  experiments show that not only the coverage closure is achieved much sooner, but we are able to isolate a small set of stimuli with high coverage that  can  be  used  for  running  regression  tests.

  • 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/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    18th International Workshop on Microprocessor and SOC Test, Security and Verification (MTV)

  • ISBN

    978-1-5386-3351-9

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    15-20

  • Publisher name

    Institute of Electrical and Electronics Engineers

  • Place of publication

    Austin, Texas

  • Event location

    Austin, Texas

  • Event date

    Dec 11, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000455129000004