VeriSilicon’s Ultra-Low Energy NPU Provides Over 40 TOPS for On-Device LLM Inference in Mobile Applications

The energy-efficient architecturescales acrossAI-enabled devices, including AI phones and AI PCs

VeriSilicon (688521.SH) today announced that its ultra-low energy and high-performance Neural Network Processing Unit (NPU) IP now supports on-device inference of large language models (LLMs) with AI computing performance scaling beyond 40 TOPS. This energy-efficient NPU architecture is specifically designed to meet the increasing demand for generative AI capabilities on mobile platforms. It not only delivers powerful computing performance for AI PCs and other end devices, but is also optimized to meet the increasingly stringent energy efficiency challenges of AI phones and other mobile platforms.

Built on a highly configurable and scalable architecture, VeriSilicon’s ultra-low energy NPU IP supports mixed-precision computation, advanced sparsity optimization, and parallel processing. Its design incorporates efficient memory management and sparsity-aware acceleration, which reduce computational overhead and latency, ensuring smooth and responsive AI processing. It supports hundreds of AI algorithms including AI-NR and AI-SR, and leading AI models such as Stable Diffusion and LLaMA-7B. Moreover, it can be seamlessly integrated with VeriSilicon’s other processing IPs to enable heterogeneous computing, empowering SoC designers to develop comprehensive AI solutions that meet diverse application needs.

VeriSilicon’s ultra-low energy NPU IP also supports popular AI frameworks such as TensorFlow Lite, ONNX, and PyTorch, thereby accelerating deployment and simplifying integration for customers across various AI use cases.

“Mobile devices, such as smartphones, are evolving into personal AI servers. With the rapid advancement of AIGC and multi-modal LLM technologies, the demand for AI computing is growing exponentially and becoming a key differentiator in mobile products,” said Weijin Dai, Chief Strategy Officer, Executive Vice President, and General Manager of the IP Division at VeriSilicon. “One of the most critical challenges in supporting such high AI computing workloads is energy consumption control. VeriSilicon has been continuously investing in ultra-low energy NPU development for AI phones and AI PCs. Through close collaboration with leading SoC partners, we are excited to see that our technology has been realized in silicon for next-generation AI phones and AI PCs.”

About VeriSilicon

VeriSilicon is committed to providing customers with platform-based, all-around, one-stop custom silicon services and semiconductor IP licensing services leveraging its in-house semiconductor IP. For more information, please visit: www.verisilicon.com

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