Adaptive tuning in a dynamically changing resource environment

We present preliminary results of a project to create a tuning system that adaptively optimizes programs to the underlying execution platform. We will show initial results from two related efforts, (i) Our tuning system can efficiently select the best combination of compiler options, when translating programs to a target system, (ii) By tuning irregular applications that operate on sparse matrices, our system is able to achieve substantial performance improvements on cluster platforms. This project is part of a larger effort that aims at creating a global information sharing system, where resources, such as software applications, computer platforms, and information can be shared, discovered, and adapted to local needs.