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<Paper uid="P98-2159">
  <Title>An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
$CCL, UMIST, U.K.
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes an efficient parallel system for processing Typed Feature Structures (TFSs) on shared-memory parallel machines. We call the system Parallel Substrate for TFS (PSTFS}.</Paragraph>
    <Paragraph position="1"> PSTFS is designed for parallel computing environments where a large number of agents are working and communicating with each other.</Paragraph>
    <Paragraph position="2"> Such agents use PSTFS as their low-level module for solving constraints on TFSs and sending/receiving TFSs to/from other agents in an efficient manner. From a programmers' point of view, PSTFS provides a simple and unified mechanism for building high-level parallel NLP systems. The performance and the flexibility of our PSTFS are shown through the experiments on two different types of parallel HPSG parsers.</Paragraph>
    <Paragraph position="3"> The speed-up was more than 10 times on both parsers.</Paragraph>
  </Section>
class="xml-element"></Paper>