TY - GEN
T1 - Parallel Processing Design of Latent Semantic Analysis Based Essay Grading System with OpenMP
AU - Ratna, Anak Agung Putri
AU - Ibrahim, Ihsan
AU - Purnamasari, Prima Dewi
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/12/5
Y1 - 2017/12/5
N2 - In this paper, a parallel processing design for an short-answer essay grading system based on Latent Semantic Analysis (LSA) is presented. This system was developed to ease the lecturers for short-essay assessment process. With the number of documents to be assessed in an exam period, efficiency of processing and time are needed. Parallel processing is a solution for advancing the system to be implemented for wide scope of use. The design was implemented using OpenMP Application Programming Interface (API) to achieve this research purpose. Most of the system’s processes utilize the outer loop or repetitive process with data level parallelism to process the same process for different data at a time. Early experiment on SVD process has promising result for parallelization implementation compared to the serial process. With parallelization, SVD could process 50 documents in 1.773 microseconds (ms), 3 times faster than the serial process in 5.676 ms. There were 2 other experiments to obtain the optimum number of matrix size and number of threads for parallelization; the experiment showed that two threads division on SVD process is the best option for this system and more threads are appropriate for more complex implementation and larger LSA based system.
AB - In this paper, a parallel processing design for an short-answer essay grading system based on Latent Semantic Analysis (LSA) is presented. This system was developed to ease the lecturers for short-essay assessment process. With the number of documents to be assessed in an exam period, efficiency of processing and time are needed. Parallel processing is a solution for advancing the system to be implemented for wide scope of use. The design was implemented using OpenMP Application Programming Interface (API) to achieve this research purpose. Most of the system’s processes utilize the outer loop or repetitive process with data level parallelism to process the same process for different data at a time. Early experiment on SVD process has promising result for parallelization implementation compared to the serial process. With parallelization, SVD could process 50 documents in 1.773 microseconds (ms), 3 times faster than the serial process in 5.676 ms. There were 2 other experiments to obtain the optimum number of matrix size and number of threads for parallelization; the experiment showed that two threads division on SVD process is the best option for this system and more threads are appropriate for more complex implementation and larger LSA based system.
KW - Essay grading
KW - Latent semantic analysis
KW - OpenMP
KW - Parallel processing
KW - Singular value decomposition
UR - http://www.scopus.com/inward/record.url?scp=85042121603&partnerID=8YFLogxK
U2 - 10.1145/3168390.3168401
DO - 10.1145/3168390.3168401
M3 - Conference contribution
AN - SCOPUS:85042121603
T3 - ACM International Conference Proceeding Series
SP - 119
EP - 124
BT - Proceedings of 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017
PB - Association for Computing Machinery
T2 - 2017 International Conference on Computer Science and Artificial Intelligence, CSAI 2017
Y2 - 5 December 2017 through 7 December 2017
ER -