EcoFlex-HDP: High-Speed and Low-Power and Programmable Hyperdimensional-Computing Platform with CPU Co-Processing
Yuya Isaka, Nau Sakaguchi, Michiko Inoue, Michihiro Shintani · 2024
Hyperdimensional computing (HDC) can efficiently perform various cognitive tasks efficiently by mapping data to hyperdimensional vectors with thousands to tens of thousands of dimensions. However, the primary operations of HDC—Bind, Permutation, and Bound—need to be executed more efficiently on a standard CPU platform. This study introduces a novel computational platform, EcoFlex-HDP, specifically designed for HDC. EcoFlex-HDP exploits the parallelism and high memory access efficiency of HDC operations to achieve low computation time and energy consumption, outperforming the CPU. Furthermore, it can work cooperatively with a CPU, enabling integration with existing software, providing flexibility to apply new algorithms, and contributing to the development of an HDC ecosystem. Through experimental evaluations with a Cortex-A9 processor, HDC operations were shown to be accelerated by a maximum of 169 times. Furthermore, EcoFlex-HDP was confirmed to improve the energy-delay product by up to 13,469 times when training an image recognition task. All source codes for our platform and experiments are available at https://github.com/yuya-isaka/EcoFlex-HDP.