Performance optimization for data intensive grid applications

摘要: The ability to effectively use computational grids for data intensive applications is becoming increasingly important. distributed, heterogeneous, shared nature of the computing resources provides a significant challenge in developing support computationally demanding applications. In this paper we describe several performance optimization techniques have developed filter-stream programming framework that designed and implemented on Grid. We present results multiple versions medical imaging application various distributed machine configurations show benefits optimizations, also provide evidence can be both efficiently utilize available Grid scalable as additional are made available.