Accelerating Hyperdimensional Classifier on Multiple GPUs

Among brain-inspired computing paradigms, hyperdimensional (HD) computing is based on mathematical properties of high-dimensional spaces which show remarkable agreement with brain-controlled behaviors [1] . In [2] , the authors present an HD classifier for the task of identifying the language of text samples based on letter N -grams. They describe a computing architecture in which an encoding module generates a hypervector for each text sample and a search module compares the generated vector with a set of trained hypervectors. They provide an open-source implementation of their HD classifier written in hardware description language (HDL). In addition, they implemented the classifier with the 65-nm technology library, and evaluated the efficiency and accuracy of the classifier.