  To exploit both memory locality and the full performance potential of highly
tuned kernels, dense linear algebra libraries such as LAPACK commonly implement
operations as blocked algorithms. However, to achieve next-to-optimal
performance with such algorithms, significant tuning is required. On the other
hand, recursive algorithms are virtually tuning free, and yet attain similar
performance. In this paper, we first analyze and compare blocked and recursive
algorithms in terms of performance, and then introduce ReLAPACK, an open-source
library of recursive algorithms to seamlessly replace most of LAPACK's blocked
algorithms. In many scenarios, ReLAPACK clearly outperforms reference LAPACK,
and even improves upon the performance of optimizes libraries.
