Massively Parallel OS SSS { CORE

We propose two resource management methods; a scheduling policy that re ects resource consumption states and a memory-replacement strategy based on page classi cation under distributed shared memory architecture. The performances of the two mechanisms are evaluated by a probabilistic simulation. An instruction-level simulator simulates variety of process sets with nite resources on proposed resource-management methods. The results show the superiority of the proposed resource management mechanisms.