Automatic Linux Customization and Optimization for High-Performance Scientific Applications

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We propose to develop and empirically evaluate the software tools,analysis techniques,and compileroptimizations necessary to generate automatically a customized Linux image,and to affect the necessary ap-plication transformations that use it.Moreover,we will quantify the success of our techniques using scienti .capplications and software prototypes executing on commodity cluster platforms.We will employ parallel and.oating-point intensive codes as well as scientic database programs.We will focus on execution platformsviable at the high-end .clusters of SMP,IA32 and IA64 systems .the latter allowing us to investigaterelevance to NSF's current TeraGrid [65 ]effort.The result,we believe,will be a software system that auto-matically enables high-performance scientic computing on commodity systems through application-specificcustomization and dynamic adaptation of a low-cost,popular,and familiar Linux operating system.