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Graph algorithms are increasingly used in applications that exploit large databases. However, conventional processor architectures are inadequate for handling the throughput and memory requirements of graph computation. Lincoln Laboratory's graph-processor architecture represents a rethinking of parallel architectures for graph problems. Our processor utilizes innovations that include a sparse matrix-based...
Considered the modeling of stationary physical fields with neural networks. Chosen the architecture of the neural network, developed neuroequations, proved assertions about the output values of the neurons.
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