Improving Performance of Distributed Shared Memory (DSM) on Multiprocessor Framework with Software Approach

Objectives: To design Distributed Shared Memory (DSM) for the multiprocessor distributed framework using a different software parametric approach that provides significant performance improvement against convention software based architectures. Methods/Statistical Analysis: Software distributed shared memory can be architected by using a different concept of an operating system, by utilizing a programming library and by extending underlying virtual address space architecture. It incorporates various design options like granularity, consistency model, implementation level, data organization, algorithms, protocols, etc. We have proposed few software parameter choices and impact which gives significant performance improvement compared to past designs to manage software distributed shared memory. This paper also discusses various issues that exist while moving toward software distributed shared memory implementation. Findings: There are two methodologies by which it is possible to achieve distributed shared memory design are first in hardware like cache coherence circuits and network interfaces and the second is software. Here the proposed system architecture makes major impact on programming, performance, design and cost. An algorithm is designed such a unique manner which resides in memory controller and make efficient global virtual memories. It is using variable as granularity which are shared that is more flexible for complex data structure and large database. It is defined using unique identifier which makes its mapping and retrieval more manageable using proposed consistency mechanism. Application/Improvements: Distributed shared memory optimization is a most important area of improving distributed system performance. By taking care of good choice on underlying issues and according to system’s design requirement, it possible to gain advantages of improved architecture which can be more used for various distributed applications where shared data plays a major role.