Collection of Hyperdimensional Computing Projects
Here, we aim to provide a comprehensive collection of projects using hyperdimensional computing. Please let us know if you have any related project.
The way the brain works suggests that rather than working with numbers that we are used to, computing with hyperdimensional (HD) vectors, referred to as “hypervectors,” is more efficient. Computing with hypervectors, offers a general and scalable model of computing as well as well-defined set of arithmetic operations that can enable fast and one-shot learning (no need of backpropagation). Furthermore it is memory-centric with embarrassingly parallel operations and is extremely robust against most failure mechanisms and noise. Hypervectors are high-dimensional (e.g., 10,000 bits), (pseudo)random with independent identically distributed components leading to holographic representation (i.e., not microcoded). Hypervectors can use various coding: dense or sparse, bipolar, binary, real, complex. They can be combined using arithmetic operations such as multiplication, addition, and permutation, and be compared for similarity using distance metrics.