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This algorithm's MPI communication overhead and execution time were evaluated on an HPC cluster, using randomly generated sparse matrices with dimensions up to one million by one million. The results showed a reduction of inter-process communication overhead for matrices with larger dimensions compared to another one dimensional parallel algorithm that takes  run-time complexity for accumulating the results.<\/p>","DOI":"10.4018\/ijghpc.2017070104","type":"journal-article","created":{"date-parts":[[2017,7,11]],"date-time":"2017-07-11T12:20:40Z","timestamp":1499775640000},"page":"46-59","source":"Crossref","is-referenced-by-count":2,"title":["Reducing Inter-Process Communication Overhead in Parallel Sparse Matrix-Matrix Multiplication"],"prefix":"10.4018","volume":"9","author":[{"given":"Md Salman","family":"Ahmed","sequence":"first","affiliation":[{"name":"East Tennessee State University, Johnson City, TN, USA"}]},{"given":"Jennifer","family":"Houser","sequence":"additional","affiliation":[{"name":"East Tennessee State University, Johnson City, TN, USA"}]},{"given":"Mohammad A.","family":"Hoque","sequence":"additional","affiliation":[{"name":"East Tennessee State University, Johnson City, TN, USA"}]},{"given":"Rezaul","family":"Raju","sequence":"additional","affiliation":[{"name":"University of Houston, Houston, TX, USA"}]},{"given":"Phil","family":"Pfeiffer","sequence":"additional","affiliation":[{"name":"East Tennessee State University, Johnson City, TN, USA"}]}],"member":"2432","reference":[{"key":"IJGHPC.2017070104-0","doi-asserted-by":"publisher","DOI":"10.1145\/2486159.2486196"},{"key":"IJGHPC.2017070104-1","doi-asserted-by":"publisher","DOI":"10.1145\/2312005.2312044"},{"key":"IJGHPC.2017070104-2","doi-asserted-by":"publisher","DOI":"10.1145\/2755573.2755613"},{"key":"IJGHPC.2017070104-3","doi-asserted-by":"crossref","unstructured":"Briggs, W. 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