InDiGO: An Infrastructure for Optimization of Distributed Algorithms ∗

Abstract: The developers of distributed algorithms are faced with two opposing forces. One is to design generic al-gorithms that are reusable in a large number of applications. Efficiency considerations, on the other hand, force the al-gorithms to be customized to specific operational contexts. This problem is often attacked by simply re-implementing all or large portions of an algorithm. This paper proposes InDiGO, an infrastructure which allows design of generic but customizable algorithms and provides tools to cus-tomize such algorithms for specific applications. InDiGO provides the following capabilities: (a) Tools to generate intermediate representations of an application which can be leveraged for analysis, (b) Mechanisms to allow develop-ers to design customizable algorithms by exposing design knowledge in terms of configurable options, and (c) An op-timization engine to analyze an application to derive the in-formation necessary optimize the algorithms. We perform three types of optimizations: static, dynamic and physical topology-based optimization. We present experimental re-sults to demonstrate the advantages of our infrastructure.