Abstract. Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).
Spelling mistakes of words in writing Rejang words are often found so it is difficult to understand. The method used in correcting word errors (spelling checkers) has been carried out by several researchers. In this research, words were improved in Rejang words based on the morphology
of the Reajang language using the N-gram and Euclidean Distance methods. The process begins with forming the word practice with the N-gram method in cutting a number of words. In the testing process, the pre-process stages are carried out first and the training words are checked based on the
existing dictionary. Words that are assumed to be wrong are corrected by looking for words similar to Euclidean Distance. The results of the lowest word resemblance are adjusted to the word training, if it is not appropriate then the word with the highest similarity is considered the correct
word to be improved. In this study the experimental results of the words tested produce similarity levels of 20 words and the smallest 3. The results from the calculation of similarity can be directly to correct the wrong word. The results of the study can be seen that word improvement is
very dependent on the dictionary word unigram and existing training words. This shows that the N-gram and Euclidean Distance methods are good in spelling checker Rejang language.
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