Showing posts from 2014

How to install OpenMPI-Java

I have been trying out message passing frameworks for Java that can be used in HPC clusters. In this blog, I’m trying to provide installation instructions to quickly setup and try out Open MPI Java in a Linux environment. Pre-Requests: Build essentials gcc Installation Steps: Download OpenMPI 1.8   $wget Create a directory which you want to install openmpi             $mkdir /home/ charith /software/ openmpi -build     3. Extract downloaded gzipped file and change into the extracted directory              $tar -xvvzf openmpi-1.8.1.tar.gz            $cd openmpi -1.8.1     4. Configure the build environment with java enabled, using the following command           $ . /configure --enable-mpi- java --with- jdk -bindir="path to java bin directory " - -wi th- jdk -headers="path to the java directroy which have jni . h" --prefix="Pat

GoFFish : A Sub-Graph Centric Framework For Large Scale Graph Processing

It's been a long time since my last blog post. I wanted to write this blog for some time, but never got a chance to compete. Last year I was a part of a team worked on building a platform to perform  large scale distributed graph processing: GoFFish . In this blog, I am trying to give a small overview about GoFFish and its programming model. After the Google MapReduce paper and induction of Hadoop there was a search for simple programming models and analytics tools for big data processing. Graph structured data takes over a significant portion of large scale data we are seeing present day. I would say any big data problem worth looking at are graph related. :) Map Reduce model only works well with data with minimal interdependencies. Where graph structured data occupies the complete opposite end of spectrum .   Google pregel paper introduced a new simple programming model for graph processing, addressing this shortcomings of Hadoop. It's generally known a