Tall and skinny QR factorizations in MapReduce architectures

  title={Tall and skinny QR factorizations in MapReduce architectures},
  author={Paul G. Constantine and David F. Gleich},
  booktitle={MapReduce '11},
The QR factorization is one of the most important and useful matrix factorizations in scientific computing. A recent communication-avoiding version of the QR factorization trades flops for messages and is ideal for MapReduce, where computationally intensive processes operate locally on subsets of the data. We present an implementation of the tall and skinny QR (TSQR) factorization in the MapReduce framework, and we provide computational results for nearly terabyte-sized datasets. These tasks… 

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