An analysis on the performance of hash table-based dictionary implementations with different data usage models. (2017)

• Record Type: Journal Article
• Authors: Thenmozhi, M.; Srimathi, H.
• Is Part Of: International journal of high performance computing and networking. Volume 10:Number 1/2(2017)
• Page Start: 78
• Page End: 90
• Publication Date: 2017
• Subjects: RAM size -- cache memory size -- hash tables -- trie -- abstract data types -- dictionary ADTs -- data usage models -- unordered dictionaries; High performance computing -- Periodicals; Computer networks -- Periodicals; High performance computing; Periodicals; 004.05
• Languages: English
• ISSNs: 1740-0562

Abstract

The efficiency of in-memory computing applications depends on the choice of mechanism to store and retrieve strings. The tree and trie are the abstract data types (ADTs) that offer better efficiency for ordered dictionary. Hash table is one among the several other ADTs that provides efficient implementation for unordered dictionary. The performance of a data structure will depend on hardware capabilities of computing devices such as RAM size, cache memory size and even the speed of the physical storage media. Hence, an application which will be running on real or virtualised hardware environment certainly will have restricted access to memory and hashing is heavily used for such applications for speedy process. In this work, an analysis on the performance of six hash table based dictionary ADT implementations with different data usage models is carried out. The six different popular hash table based dictionary ADT implementations are Khash, Uthash, GoogleDenseHash, TommyHashtable, TommyHashdyn and TommyHashlin, tested under different hardware and software configurations.