Parallel computing is widely adotped in scientific and engineering applications to enhance the efficiency. Moreover, there are increasing research interests focusing on utilizing distributed networked computers for parallel computing. The Message Passing Interface (MPI) standard was designed to support portability and platform independence of a developed parallel program. However, the procedure to start an MPI-based parallel computation among distributed computers lacks autonomicity and flexibility. This article presents an autonomic dynamic parallel computing framework that provides autonomicity and flexibility that are important and necessary to some parallel computing applications involving resource constrained and heterogeneous platforms. In this framework, an MPI parallel computing environment consisting of multiple computing entities is dynamically established through inter-agent communications using the IEEE Foundation for Intelligent Physical Agents (FIPA) compliant Agent Communication Language (ACL) messages. For each computing entity in the MPI parallel computing environment, a load-balanced MPI program C source code along with the MPI environment configuration statements are dynamically composed as a mobile agent code. A mobile agent wrapping the mobile agent code is created and sent to the computing entity where the mobile agent code is retrieved and interpretively executed. An example of autonomic parallel matrix multiplication is given to demonstrate the self-configuration and self-optimization properties of the presented framework.

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