Aleem Akhtar

Aleem Akhtar

With the increase in amount of Big Data being generated each year, tools and technologies developed and used for the purpose of storing, processing and analyzing Big Data has also improved. Open-Source software has been an important factor in the success and innovation in the field of Big Data while Apache Software Foundation (ASF) has played a crucial role in this success and innovation by providing a number of state-of-the-art projects, free and open to the public. ASF has classified its project in different categories. In this report, projects listed under Big Data category are deeply analyzed and discussed with reference to one-of-the seven sub-categories defined. Our investigation has shown that many of the Apache Big Data projects are autonomous but some are built based on other Apache projects and some work in conjunction with other projects to improve and ease development in Big Data space.

Aleem Akhtar, Aamir Shafi, Mohsan Jameel

MPJ Express is a messaging system that allows computational scientists to write and execute parallel Java applications on High Performance Computing (HPC) hardware. Despite its successful adoption in the Java HPC community, the MPJ Express software currently does not provide any support for debugging and profiling parallel applications and hence forces its users to rely on manual and tedious debugging/profiling methods. Support for such tools is essential to help application developers increase their overall productivity. To address this we have developed debugging and profiling tools for MPJ Express, which are the main topic of this paper. Key design goals for these tools include: 1) maintain compatibility with existing logging, debugging, and visualizing tools, 2) build these tools by extending existing debugging/profiling tools instead of reinventing the wheel. The first tool, named MPJDebug, builds on the open-source Eclipse Integrated Development Environment (IDE). It provides an Eclipse-based plugin developed using the Eclipse Plugin Development Environment (PDE). The default Eclipse debugger currently does not support debugging parallel applications running on a compute cluster. The second tool, named MPJProf, is a utility based on Tuning and Analysis Utility (TAU)-an open-source performance evaluation tool. Our goal here is to exploit TAU to profile Java applications parallelized using MPJ Express by generating profiles and traces, which can later be visualized using existing tools like paraprof and Jumpshot. Towards the end of the paper, we quantify the overhead of using MPJProf, which we found to be negligible in the profiling stage of parallel application development.

Aleem Akhtar

Ant Colony Optimization (ACO) is a metaheuristic proposed by Marco Dorigo in 1991 based on behavior of biological ants. Pheromone laying and selection of shortest route with the help of pheromone inspired development of first ACO algorithm. Since, presentation of first such algorithm, many researchers have worked and published their research in this field. Though initial results were not so promising but recent developments have made this metaheuristic a significant algorithm in Swarm Intelligence. This research presents a brief overview of recent developments carried out in ACO algorithms in terms of both applications and algorithmic developments. For application developments, multi-objective optimization, continuous optimization and time-varying NP-hard problems have been presented. While to review articles based on algorithmic development, hybridization and parallel architectures have been investigated.