IoT end-nodes require extreme performance and energy efficiency coupled with high flexibility to deal with the increasing computational requirements and variety of modern near-sensor data analytics applications. Low-Bitwidth and Mixed-Precision arithmetic is emerging as a trend to address the near-sensor analytics challenge in several fields such as linear algebra, Deep Neural Networks (DNN) inference, and on-line learning. We present Dustin, a fully programmable Multiple Instruction Multiple Data (MIMD) cluster integrating 16 RISC-V cores featuring 2b-to-32b bit-precision instruction set architecture (ISA) extensions enabling fine-grain tunable mixed-precision computation, improving performance and efficiency by 3.7 x and 1.9 x over state-...