The non-von Neumann computer architecture has been widely studied to prepare us for the post-Moore era. The authors implemented this kind of architecture, which finds the lower energy state of the Ising model using circuit operations inspired by simulated annealing in SRAM-based integrated circuits. Our previous prototype was suited for the Ising model because of its simple and typical structure such as its three-dimensional lattice topology, but it could not be used in real world applications. A reconfigurable prototyping environment is needed to develop the architecture and to make it suitable for applications.Here, we describe an FPGA-based prototyping environment to develop the annealing processor's architecture for the Ising model. We implemented the new architecture using a prototyping environment. The new architecture performs approximated simulated annealing for the Ising model, and it supports a highly complex topology. It consists of units having fully-connected multiple spins. Multiple units are placed in a two-dimensional lattice topology, and neighboring units are connected to perform interactions between spins. The number of logic elements was reduced by sharing the operator among multiple spins within the unit. Furthermore, a pseudorandom number generator, which produces random pulse sequences for annealing, is also shared among all the units. As a result, the number of logic elements was reduced to less than 1/10, and the solution accuracy became comparable to that of a conventional computer's simulated annealing.
Extensive studies have highlighted a need for frequently consistent land cover information for interdisciplinary studies. This paper proposes a comprehensive framework for the automatic production of the first Vietnam-wide annual land use/land cover (LULC) data sets (VLUCDs) from 1990 to 2020, using available remotely sensed and inventory data. Classification accuracies ranged from 85.7 ± 1.3 to 92.0 ± 1.2% with the primary dominant LULC and 77.6 ± 1.2% to 84.7 ± 1.1% with the secondary dominant LULC. This confirmed the potential of the proposed framework for systematically long-term monitoring LULC in Vietnam. Results reveal that despite slight recoveries in 2000 and 2010, the net loss of forests (19,940 km2) mainly transformed to croplands over 30 years. Meanwhile, productive croplands were converted to urban areas, which increased approximately ten times. A threefold increase in aquaculture was a major driver of the wetland loss (1914 km2). The spatial–temporal changes varied, but the most dynamic regions were the western north, the southern centre, and the south. These findings can provide evidence-based information on formulating and implementing coherent land management policies. The explicitly spatio-temporal VLUCDs can be benchmarks for global LULC validation, and utilized for a variety of applications in the research of environmental changes towards the Sustainable Development Goals.
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