April 01,2016
Singapore.
The continued evolution of computing hardware and infrastructure imposes new challenges and bottlenecks to big data management. Over the last few years there has been a renewed interest in the area of (big) data systems on emerging hardware. The opportunities and challenges from emerging computing systems have been raised different scales, from a single machine to thousands of machines. The need for effectively utilizing computing resources creates new technologies and research directions: from conventional ones (e.g., cluster computing, in-memory computing), to more recent ones (e.g., GPGPU, many-core processors, and NVRAM). In addition to performance, many other system features are important for big data applications, like energy consumption and total ownership costs. For a specific application domain such as graph processing and deep learning, the design and development of novel systems on emerging hardware will create the insight into new solution approaches of the application domain and even further. Thus, there is a need to fundamentally address all the above-mentioned issues in big data systems. IEEE Transaction on Big Data (TBD) seeks original manuscripts for a Special Issue on the theme - Big Data Systems on Emerging Architectures scheduled to appear in an issue of 2017.
Original articles must be submitted via IEEE TBD Manuscript Central at https://mc.manuscriptcentral.com/tbd-cs. Submitted articles must not have been previously published or currently submitted for journal publication elsewhere. Authors must adhere to IEEE TBD submission guidelines (http://www.computer.org/web/tbd/author). For more information, please contact the Guest Editor at he.bingsheng(at)gmail(dot)com.
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