Exascale Computing and Big Data

Question: Discuss about the Exascale Computing and Big Data. Answer: Introduction The paper illustrates the importance of advanced computing in context with Exascale Computing and Big Data. Big data is defined as processes which are utilized in traditional data mining system whereas Exascle computing assists in various computing systems which are generally capable of one exaFLOPS (Loghin et al., 2015). Discussion Advanced computing is defined as a system, which helps in embodying various software, hardware as well as algorithm for providing highest capability at any time. It is divided into two sections, which include Scientific Computing and Data analytics (Lucas et al., 2014). The advanced computing also faces number of challenges, which includes the research as well as development in context with Exscale computing, and big data is quite expensive (Riedel, 2015). The challenges are also present in the field of power consumption, power failures unreliability and many more. There are different types of hardware as well as architectural challenges, which include post demand scaling as well as energy efficient and resilience at scale. Other challenges are due to improper energy management as well as thermal dissipation. Various examples help in illustrating the opportunities (Wang Raicu, 2014). Advanced computing helps in diagnosing various types of human disease, it is helpful in achieving different processes as well as exchange mechanism. Conclusion It can be concluded that high data analytics as well as Exascale computing are very much important element for an integrated computing. It has been identified that research as well as development are used in different applications of advanced computing. References Loghin, D., Tudor, B. M., Zhang, H., Ooi, B. C., Teo, Y. M. (2015).A performance study of big data on small nodes.Proceedings of the VLDB Endowment,8(7), 762-773. Lucas, R., Ang, J., Bergman, K., Borkar, S., Carlson, W., Carrington, L., ... Geist, A. (2014).DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges. USDOE Office of Science (SC)(United States). Riedel, M. (2015).Big Data in HPC, Hadoop, and HDFS-Part Two.InCy-Tera/LinkSCEEM HPC Administrator Workshop(No.FZJ-2015-00934).Jlich Supercomputing Center. Wang, K., Raicu, I. (2014).Scheduling data-intensive many-task computing applications in the cloud. In the NSFCloud Workshop on Experimental Support for Cloud Computing.