TY  - JOUR
T1  - Parallel Self-Organizing Map using MapReduce in GPUs Environment
AU - Abd Rashid, Faeez AU - Elaiza Abd Khalid, Noor AU - Firdaus Mustapha, Muhammad AU - Manaf, Mazani 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 2
SP  - 314
EP  - 320
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.314.320
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.314.320
KW  - Self-organizing map
KW  -enhanced mapreduce
KW  -incremental reduction
KW  -graphical processing units
KW  -enhancement
KW  -method
AB  - One of the drawbacks of MapReduce characteristic is overlap communication. It causes
implementation inefficiency in the GPUs environment. However, this can be overcome using incremental
reduction method. This method will enhance the communication process on GPUs environment as an alternative
to execution using CPU. This enhancement is based on Python with support of CUDA technologies which can
execute this whole process in GPUs environment. In order to achieve the good performance, this study is
proposing to design the MapReduce with incremental reduction and then to construct it and finally to test the
enhancement method to the self-organizing map with handwriting dataset.
ER  -