Energy-efficient Sparse Matrix Auto-tuning with CSX

This whitepaper describes the programming techniques used to develop an auto-tuning compression scheme for sparse matrices with respect to accelerating matrix-vector multiplication and minimizing its energy footprint, as well as a method for extracting a power profile from a corresponding implementation of the conjugate gradient method. Using two example systems, we show how these techniques can be leveraged to automatically detect a non-trivial local optimum in the execution parameter space, suggesting that it is feasible to integrate the energy efficiency evaluation of the automatic adaptation with the automatic tuning process.