RISC-V and Artificial Intelligence Applications

Abstract

This article analyzes the current state and development prospects of the open-source RISC-V architecture, which by 2026 had evolved from an academic project into a global industrial force, becoming the third major architecture alongside x86 and ARM. Key factors behind RISC-V's popularity are discussed: openness, modularity, and community focus. Particular attention is paid to the platform's technical maturity, including the implementation of the RVA23 profile and vector extensions (RVV), which have enabled RISC-V support in enterprise operating systems and Android. The application of RISC-V in artificial intelligence (AI) systems is analyzed in detail. Using Google's open-source Coral NPU platform as an example, the article demonstrates the implementation of the "AI-Native" concept: the use of specialized instructions, vector extensions, and multiply-accumulate (MAC) mechanisms to accelerate neural network inference on edge devices. A separate section is devoted to the activities of the Russian RISC-V Alliance, aimed at ensuring technological sovereignty and creating domestic solutions based on the open architecture.