Performance Tuning of Streaming Applications Via Search-Space Decomposition
High-performance streaming applications are typically pipelined and deployed on architecturally diverse (hybrid) systems. Developers of such applications are interested in customizing components used, so as to benefit application performance. The authors present an efficient and automatic technique for design-space exploration of applications in this problem domain. They solve performance tuning as an optimization problem by formulating cost functions using results from queueing theory. This results in a mixed-integer nonlinear optimization problem which is NP-hard. They reduce the search complexity by decomposing the search space.