Please use this identifier to cite or link to this item:
doi:10.22028/D291-25175
Title: | The RAWAM : relfun-adapted WAM emulation in C |
Author(s): | Perling, Markus |
Language: | English |
Year of Publication: | 1998 |
OPUS Source: | Kaiserslautern ; Saarbrücken : DFKI, 1998 |
SWD key words: | Künstliche Intelligenz |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | This work describes the C implementation of the Relfun-Adapted WAM (RAWAM). The RAWAM is an abstract machine tailored to the relational-functional language Relfun, designed and implemented on the basis of the Warren Abstract Machine (WAM). Its goal is to replace an older LISP-implemented Relfun WAM by delivering comparable functionality at higher speed. The RAWAM implementation is introduced by reference to Hassan Ai:tKaci's book "Warren's Abstract Machine: A Tutorial Reconstruction'; , and the present work will emphasize the differences and extensions w.r.t. this book. These include an assembler, an optimizer, a rudimentary module system, a more flexible realization of the standard WAM memory layout, as well as Relfun-specific extensions for functional and relational builtins, sorts, generalised indexing, and a simple higher-order facility. The implementation of the RAWAM will be described in terms of pseudo code and schematic patterns for the data structures. A relational-functional benchmark revealed a speed-up factor of 20-30 of the RAWAM compared to the older WAM. |
Link to this record: | urn:nbn:de:bsz:291-scidok-41619 hdl:20.500.11880/25231 http://dx.doi.org/10.22028/D291-25175 |
Series name: | Technical memo / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-0071] |
Series volume: | 98-07 |
Date of registration: | 5-Sep-2011 |
Faculty: | SE - Sonstige Einrichtungen |
Department: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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TM_98_07.pdf | 15,64 MB | Adobe PDF | View/Open |
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