Designed to outperform even RISC-V chips with the recently-ratified vector extensions, ztachip can boost performance by up to 50x.
Embedded developer Vuong Nguyen has released an open source RISC-V accelerator designed to boost the performance of edge AI and computer vision tasks up to 50 times — and you can try it out yourself by loading it onto a field-programmable gate array (FPGA).
“Ztachip is a RISC-V accelerator for vision and AI edge applications running on low-end FPGA devices or custom ASIC [Application Specific Integrated Circuit],” Nguyen explains. “An innovative tensor processor hardware is implemented to accelerate a wide range of different tasks from many common vision tasks such as edge-detection, optical-flow, motion-detection, color-conversion to executing TensorFlow AI models.”