Energy Efficient Calculations of Text Similarity Measure on FPGA-Accelerated Computing Platforms

This paper presents an impact of the customized hardware accelerator on the overall performance of the text similarity computing system. The hardware processing module that is presented in the paper is a building block of the processing engine in the search system of related documents. The engine is used in the phase of preliminary retrieval of similar documents. The TF-IDF weighting scheme and cosine similarity metric are used by the module. Evaluation boards equipped with Xilinx’s Field Programmable Gate Array (FPGA) were utilized as a hardware platforms for implementation of the selected time-consuming operations. The series of tests was conducted, and the results of the hardware-accelerated solutions were compared against the standard software implementation. The two different FPGA-enabled platforms were employed in the experiments. The low-power and the high-performance platform were used to compare the metrics of different hardware solutions. We provide the adequate results and conclusions that present that the energy and speed metrics of the text similarity calculations can be improved thanks to the hardware accelerator. Consequently, the cluster of FPGA-enabled nodes is proposed for the large scale processing.

[1]  Maciej Wielgosz,et al.  Implementation of a System for Fast Text Search and Document Comparison , 2014, Intelligent Tools for Building a Scientific Information Platform.

[2]  Dejan Markovic,et al.  A scalable sparse matrix-vector multiplication kernel for energy-efficient sparse-blas on FPGAs , 2014, FPGA.

[3]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[4]  Stephen Clark,et al.  A Systematic Study of Semantic Vector Space Model Parameters , 2014, CVSC@EACL.

[5]  Kazimierz Wiatr,et al.  The Regular Expression Matching Algorithm for the Energy Efficient Reconfigurable SoC , 2013, PPAM.

[6]  Wenqiang Wang,et al.  A universal FPGA-based floating-point matrix processor for mobile systems , 2014, 2014 International Conference on Field-Programmable Technology (FPT).

[7]  Ernest Jamro,et al.  The Algorithms for FPGA Implementation of Sparse Matrices Multiplication , 2014, Comput. Informatics.

[8]  Kin Fun Li,et al.  Parallel Computation of Similarity Measures Using an FPGA-Based Processor Array , 2008, 22nd International Conference on Advanced Information Networking and Applications (aina 2008).