The Scalable, Efficient and Accelerated Causal Reasoning Operators, Graphs and Spikes for Earth and Embedded Systems (SEA-CROGS) Center advances scalable and efficient physics-informed machine intelligence to accelerate modeling, inference, causal reasoning, etiology, and pathway discovery for Earth systems, embedded systems, mobile platforms, and others by a thousand times.
The SEA-CROGS investigators are developing higher levels of abstraction at the operator regression level that can be expressed using deep neural layers, kernels, graphs, and spiking neural networks, and implemented into the next generation of power-efficient advanced computing architectures.
The impact of SEA-CROGS will be a paradigm shift in our computational capability to analyze and predict the behavior of complex systems.
The SEA-CROGS is a collaboration between Pacific Northwest National Laboratory and Sandia National Laboratories, with academic partners at Brown University, Yale University, California Institute of Technology, New Jersey Institute of Technology, Spelman College, and Stanford University.
This work is supported by the Applied Mathematics Program within the Department of Energy Office of Advanced Scientific Computing Research.
Amanda Howard, Panos Stinis, and Nathaniel Trask are organizing the minisymposium for the 2nd IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology Conference.