The use of multicomputer clusters composed of cheap workstations connected by high-speed networks is common in modern high-performance computing. However, operating system research in such environments has lagged. Our research aims at enhancing the functionality of the operating system by providing management functions that allow dynamic resource sharing and performance prediction in a clustered environment supporting distributed shared memory and multithreading. Central to this approach is the development of a parametric cost model that can predict the performance ramifications of policy choices and allow applications and middleware to adapt to the computing environment and achieve better performance.
|Original language||English (US)|
|Title of host publication||Proceedings of the Heterogeneous Computing Workshop, HCW|
|Publisher||IEEE Computer Society|
|Number of pages||10|
|State||Published - 2000|
ASJC Scopus subject areas
- Computer Science(all)