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A new integrated computational model reduces uncertainty in climate predictions by bridging Earth systems with energy and economic models and large-scale human impact data. Co-developed by Oak Ridge National Laboratory, the novel integrated Earth system model, or iESM, leverages the power of supercomputers, including ORNL’s Titan, to couple biospheric feedbacks from oceans, atmosphere and land with human activity, such as fossil fuel emissions, agriculture and land use.
In a first for deep learning, an Oak Ridge National Laboratory-led team is bringing together quantum, high-performance and neuromorphic computing architectures to address complex issues that, if resolved, could clear the way for more flexible, efficient technologies in intelligent computing.