In data-science parlance, graphs are structures of nodes and connecting lines that are used to map scores of complex data relationships. Analyzing graphs is useful for a broad range of applications, such as ranking webpages, analyzing social networks for political insights, or plotting neuron structures in the brain.
Consisting of billions of nodes and lines, however, large graphs can reach terabytes in size. The graph data are typically processed in expensive dynamic random access memory (DRAM) across multiple power-hungry servers.
Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have now designed a device that uses the cheap flash …
MIT News – Electrical engineering and computer science (EECS) – Computer science and technology
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