POSTER: V-Seek: Optimizing LLM Reasoning on A Server-Class General-Purpose RISC-V Platform
Javier Jesus Poveda Rodrigo, Mohamed Amine Hamdi, Cyril Koenig, Alessio Burrello, Daniele Jahier Pagliari, Luca Benini · 2025
This paper addresses the problem of deployment of LLMs on RISC-V-based CPU systems by optimizing LLM inference on the Sophon SG2042.We evaluate the inference performance of two state-of-theart LLMs optimised for reasoning: DeepSeek R1 Distill Llama 8B and DeepSeek R1 Distill QWEN 14B.Thanks to our optimizations on top of the llama.cppinference library, we achieve token generation speeds of 4.32/2.29 tokens per second and prompt processing speeds of 6.54/3.68tokens per second, with a significant speedup of up to 2.9×/3.0×compared to a direct porting of the same library.