Parallel Hardware for Faster Morphological Analysis

TL;DR

This paper demonstrates that parallel hardware and algorithms significantly improve the speed and accuracy of Arabic morphological analysis, especially for verb root extraction, using FPGA and multi-core systems.

Contribution

It introduces novel parallel hardware implementations, including pipelined processors, for Arabic morphological analysis, achieving high speedups and accuracy improvements.

Findings

Pipelined processor achieved a speedup of 5571.4x over software.

The stemmer attained 87% and 90.7% accuracy on Quranic texts.

Hardware implementations outperformed software in speed and efficiency.

Abstract

Morphological analysis in the Arabic language is computationally intensive, has numerous forms and rules, and is intrinsically parallel. The investigation presented in this paper confirms that the effective development of parallel algorithms and the derivation of corresponding processors in hardware enable implementations with appealing performance characteristics. The presented developments of parallel hardware comprise the application of a variety of algorithm modelling techniques, strategies for concurrent processing, and the creation of pioneering hardware implementations that target modern programmable devices. The investigation includes the creation of a linguistic-based stemmer for Arabic verb root extraction with extended infix processing to attain high-levels of accuracy. The implementations comprise three versions, namely, software, non-pipelined processor, and pipelined processor with high throughput. The targeted systems are high-performance multi-core processors for software implementations and high-end Field Programmable Gate Array systems for hardware implementations. The investigation includes a thorough evaluation of the methodology, and performance and accuracy analyses of the developed software and hardware implementations. The pipelined processor achieved a significant speedup of 5571.4 over the software implementation. The developed stemmer for verb root extraction with infix processing attained accuracies of 87% and 90.7% for analyzing the texts of the Holy Quran and its Chapter 29 - Surat Al-Ankabut.