A rapid and flexible parallel approach for viewshed computation on large digital elevation models is presented. Our work is focused on the implementation of a derivate of the R2 viewshed algorithm. Emphasis has been placed on input/output (IO) efficiency that can be achieved by memory segmentation and coalesced memory access. An implementation of the parallel viewshed algorithm on the Compute Unified Device Architecture (CUDA), which exploits the high parallelism of the graphics processing unit, is presented. This version is referred to as r.cuda.visibility. The accuracy of our algorithm is compared to the r.los R3 algorithm (integrated into the open-source Geographic Resources Analysis Support System geographic information system environment) and other IO-efficient algorithms. Our results demonstrate that the proposed implementation of the R2 algorithm is faster and more IO efficient than previously presented IO-efficient algorithms, and that it achieves moderate calculation precision compared to the R3 algorithm. Thus, to the best of our knowledge, the algorithm presented here is the most efficient viewshed approach, in terms of computational speed, for large data sets.
The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.
The fronthaul for 5 th generation mobile systems (and beyond) has evolved with new splits for the radio access network functions defined, and the transport for these split interfaces having very different requirements. Testing of the transport for such split interfaces is reported, and it is shown that an Ethernet fronthaul transport network, which is capable of bringing efficiency gains through statistical multiplexing, can meet stringent latency and latency variation requirements, assuming buffering and playout of the radio waveforms and that timing/synchronization signals are prioritized. An aggregation technique for a 100 Gb/s Ethernet trunk which provides for such timing signals is demonstrated. Real-time monitoring of the Ethernet fronthaul for software-defined networking control and performance optimization is also shown.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.