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Tomorrow's immersive applications will leverage Mixed Reality interfaces accessing a multitude of services from distributed clouds. They will face extreme latency constraints, massive datasets, spontaneous collaboration, and constant service churn. This paper outlines our experience evolving an application designed to support collaborative work in Urban Design (UD) practices. The application, UD Co-Spaces,...
Machine learning can be the key to saving the world from losing football field-sized forest areas each second. As deforestation in the Amazon basin causes devastating effects both on the ecosystem and the environment, there is urgent need to better understand and manage its changing landscape. A competition was recently conducted to develop algorithms to analyze satellite images of the Amazon. Successful...
Container-based Software-as-a-Service (SaaS) systems are rapidly emerging as a dominate cloud deployment paradigm, as supported via Docker, etc. This has opened new research avenues as lighter-weight containers replace heavier-weight virtual machines (VMs) as atomic cloud deployment units. Advancing such research requires sufficiently rich, container-aware cloud simulation frameworks so as to explore...
Due to the painful time consuming of cycle-accurate simulations, analytical modeling of DRAM systems has been becoming an effective alternative to give guidance for architecture optimizations. Some analytical models forecast the DRAM performance by obtaining the proportions of different DRAM command appearances from memory trace profiling. However, existing works require too many cases composed by...
The exponential growth of complex, heterogeneous, dynamic, and unbounded data, generated by a variety of fields including health, genomics, physics, climatology, and social networks pose significant challenges in data processing and desired speed-performance. Existing processor-based software-only algorithms are incapable of analyzing and processing this enormous amount of data, efficiently and effectively...
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