Associative parallel lexing

Author

Asthagiri, Chandra R. ; Potter, Jerry L.

Author_Institution

Dept. of Comput. & Inf. Sci., Cleveland State Univ., OH, USA

fYear

1992

fDate

23-26 Mar 1992

Firstpage

466

Lastpage

469

Abstract

Presents near constant time associative parallel lexing (APL) algorithms. The best time complexity thus far claimed is O(log n) (n denotes the number of input characters for the parallel prefix lexing (PPL) algorithm. The linear state recording step in the PPL algorithm, which needs to be done only once for each grammar has been ignored in claiming the log n time complexity for the PPL algorithm. Furthermore, the PPL algorithm does not consider recording line numbers for the tokens and distinguishing identifier tokens as keywords or user-identifiers. The APL algorithms perform all of these functions. Thus, without considering the efforts spent on these functions, the APL algorithm takes constant time since every step depends on the length of the tokens, not on the length of the input. Generalizing and including these extra functions, the APL algorithm takes near constant time

Keywords

computational complexity; grammars; parallel algorithms; parallel programming; associative parallel lexing algorithms; best time complexity; grammar; linear state recording step; parallel prefix lexing algorithm; Algorithm design and analysis; Associative memory; Computational Intelligence Society; Computer aided instruction; Computer science; Concurrent computing; Lakes; Performance analysis; Process control; Vector processors;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel Processing Symposium, 1992. Proceedings., Sixth International

Conference_Location

Beverly Hills, CA

Print_ISBN

0-8186-2672-0

Type

conf

DOI

10.1109/IPPS.1992.223001

Filename

223001