RMI Approach to Cluster Based Cache Oblivious Peano Curves

Abstract

There are number of problems that are so complex/large that it becomes impractical or even in some cases impossible to solve these problems on a single machine. As compared to the serial computation, parallel computation is much result oriented for understanding, simulating of number of complex and real world physical process. The cache oblivious(CO) model helps us in designing the algorithms which are cache alert. Moreover these algorithms will be independent of the given system's cache size. A matrix multiplication based upon the Peano curves helps in designing of the cache oblivious algorithms. The distributed environment is being developed using RMI (Remote Method Invocation). In this setup the Master system will decompose a large size matrix into the smaller (ones depending upon the system available). The slave systems will perform the computations as per the equations based upon space filling Peano curves which are cache oblivious in nature. As a result we are able to reuse the matrix elements again and again which leads to decrease in number of cache misses and increasing the overall execution time of whole cluster. At the master system actual partitioning is done to generate submatrix and the virtual partitioning into size of 3x3 is being done at the slave systems for implementing multiplication based upon Peano curves(PC). PC algorithmic approach provides spatial locality which is a basic requirement for increasing the overall system efficiency.