Investigating Autonomic Runtime Management Strategies for SAMR Applications

Dynamic structured adaptive mesh refinement (SAMR) techniques along with the emer-gence of the computational Grid offer the potential for realistic scientific and engi-neering simulations of complex physical phenomena. However, the inherent dynamic nature of SAMR applications coupled with the heterogeneity and dynamism of the un-derlying Grid environment present significant research challenges. This paper presents application/system sensitive reactive and proactive partitioning strategies that form a part of the GridARM autonomic runtime management framework. An evaluation using different SAMR kernels and system workloads is presented to demonstrate the improve-ment in overall application performance. KEY WORDS: GridARM autonomic runtime management framework; structured adap-tive mesh refinement; application/system sensitive reactive and proactive partitioning