A Special Issue of Journal of Parallel and Distributed Computing: Scalable Systems for Big Data Management and Analytics

Background and Scope The growth of datasets of massive size, diversity and rates, termed ‘‘Big Data’’, is accelerated by high-throughput scientific instruments, and mobile and online sensors embedded in our daily lives. Management and analytics of Big Data is critical for achieving scientific and engineering breakthroughs, mining for timely and pertinent information, and decision making. The potential of Big Data can be translated into reality only through development of novel algorithms, effective software platforms to navigate data, and innovative use of hardware infrastructure to scale them. Big Data applications need to be supported not just on HPC systems but also on emerging cyber-infrastructure such as Cloud platforms, and accelerators like GPGPUs, FPGAs and many-core processors. The convergence of Big Data software platforms and accelerated cyber-infrastructure is vital for transformative research. For this special issue, we invite articles on innovative research to address Big Data challenges using novel algorithms, software architectures, emerging computing platforms, and unique approaches. Submissions that pertain to Big Data analytics in any field are relevant to this special issue.