<?xml version="1.0" encoding="UTF-8"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
  <responseDate>2026-07-25T03:04:59Z</responseDate>
  <request identifier="23589" metadataPrefix="oai_dc" verb="GetRecord">https://drops.dagstuhl.de/oai</request>
  <GetRecord>
    <record>
      <header>
        <identifier>oai:drops-oai.dagstuhl.de:23589</identifier>
        <datestamp>2025-10-27T10:21:49Z</datestamp>
        <setSpec>ddc:004</setSpec>
        <setSpec>open_access</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Bounding the WCET of a GPU Thread Block with a Multi-Phase Representation of Warps Execution</dc:title>
          <dc:creator>Jeanmougin, Louison</dc:creator>
          <dc:creator>Carle, Thomas</dc:creator>
          <dc:creator>Rochange, Christine</dc:creator>
          <dc:subject>GPU</dc:subject>
          <dc:subject>WCET analysis</dc:subject>
          <dc:description>This paper proposes to model the Worst-Case Execution Time (WCET) of a GPU thread block as the Worst-Case Response Time (WCRT) of the warps composing the block. Inspired by the WCRT analyzes for classical CPU tasks, the response time of a warp is modeled as its execution time in isolation added to an interference term that accounts for the execution of higher priority warps. We provide an algorithm to build a representation of the execution of each warp of a thread block that distinguishes phases of execution on the functional units and phases of idleness due to operations latency. A simple formula relying on this model is then proposed to safely upper bound the WCRT of warps scheduled under greedy policies such as Greedy-Then-Oldest (GTO) or Loose Round-Robin (LRR). We experimented our approach using simulations of kernels from a GPU benchmark suite on the Accel-Sim simulator. We also evaluated the model on a GPU program that is likely to be found in safety critical systems : SGEMM (Single-precision GEneral Matrix Multiplication). This work constitutes a promising first building block of an analysis pipeline for enabling static WCET computation on GPUs.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Louison Jeanmougin and Thomas Carle and Christine Rochange</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.ECRTS.2025.11</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-235898</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.11</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
  </GetRecord>
</OAI-PMH>
