Electronic Design Article: Low-Power Play: GAP8 Weds Multicore RISC-V With Machine Learning

Machine learning (ML) on the edge often involves convolutional neural networks (CNNs). This can be done using standard processors, but there’s a cost due to performance and matching power requirements. Though specialized ML hardware can significantly reduce the amount of power, a programmable solution would provide a more flexible alternative.
GreenWaves Technologies brings a RISC-V-based solution to the table, building on the Parallel Ultra Low Power Platform (PULP). PULP is designed to support four different 32-bit, RISC-V cores, including RISCY, Zero-riscy, Micro-riscy, and Ariane. RISCY is an RV32-IMC core with a four-stage pipeline DSP, SIMD, hardware loop, bit manipulation, and post-increment extensions. Zero-riscy uses a two-stage pipeline with a RV32-IMC base, while Micro-riscy handles RV32-EC with only 16 registers and a two-stage pipeline. Ariane supports a 64-bit architecture with memory management, allowing it to run operating systems like Linux. It targets high-end applications.
To read more, please visit: http://www.electronicdesign.com/embedded-revolution/low-power-play-gap8-weds-multicore-risc-v-machine-learning