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We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit
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Document Date: 2016-06-23 15:50:48
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We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit