Ken Naono
Central Research Laboratory, Hitachi Ltd.

"Numerical Policy Interface for Automatic Tuning Library"

Recently, parameters for performance tuning are diverse in many matrix libraries, thus requiring automatic tuning facilities. Most of the existing researches focus on computation time reductions, while many matrix library users' requirements are becoming hybrid, due to today's high performance platforms complexity. For example, a user wants to reduce the computation time under the limitation of 10 gigabyte memory use. In this talk, recent research trends in automatic tuning technology are reviewed and a new framework
"numerical policy" is proposed to develop high-quality matrix libraries. The framework is applied to Lanczos eigensolver on an SMP platform, one node of an SR11000. The result shows that the framework effectively selects parameter values that achieve a good balance between memory requirements and computation time. The result implies that "numerical policy" framework plays an important role to solve the diversity problem in selecting the tuning parameter values in matrix libraries.