Neurxcore introduces NPU product line for AI inference applications

Neurxcore introduces NPU product line for AI inference applications Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.


Neurxcore, a provider of cutting-edge Artificial Intelligence (AI) solutions, has launched its Neural Processor Unit (NPU) product line for AI inference applications.

It is built on an enhanced and extended version of the open-source NVIDIA’s Deep Learning Accelerator (Open NVDLA) technology, combined with patented in-house architectures. The SNVDLA IP series from Neurxcore sets a new standard for energy efficiency, performance, and capability, with a primary focus on image processing, including classification and object detection. SNVDLA also offers versatility for generative AI applications and has already been silicon-proven, operating on a 22nm TSMC platform, and showcased on a demonstration board running a variety of applications.

The innovative IP package also includes the Heracium SDK (Software Development Kit) built by Neurxcore upon the open-source Apache TVM (Tensor-Virtual Machine) framework to configure, optimize and compile neural network applications on SNVDLA products. Neurxcore’s product line caters to a wide range of industries and applications, spanning from ultra-low power to high-performance scenarios, including sensors and IoT, wearables, smartphones, smart homes, surveillance, Set-Top Box and Digital TV (STB/DTV), smart TV, robotics, edge computing, AR/VR, ADAS, servers and more.

In addition to this groundbreaking product, Neurxcore offers a complete package allowing the development of customized NPU solutions, including new operators, AI-enabled optimised subsystem design, and optimized model development, covering training and quantization.

Virgile Javerliac, founder and CEO of Neurxcore, said: “80% of AI computational tasks involve inference. Achieving energy and cost reduction while maintaining performance is crucial.”

He expressed gratitude to the dedicated team that developed this groundbreaking product and emphasized Neurxcore’s commitment to serving customers and exploring collaborative opportunities.

The inference stage, which involves using AI models to make predictions or generate content, is a pivotal aspect of AI. Neurxcore’s innovative solutions address this phase efficiently, making it ideal for various applications, even when serving multiple users simultaneously.

The SNVDLA product line exhibits substantial improvements in energy efficiency, performance, and feature set compared to the original NVIDIA version, while also benefiting from NVIDIA’s industrial-grade development. The product line’s fine-grain tunable capabilities, such as the number of cores and multiply-accumulate (MAC) operations per core, allow for versatile applications across diverse markets. It stands out for its exceptional energy and cost efficiency, making it one of the best in its class. Furthermore, competitive pricing, combined with an open-source software environment thanks to Apache TVM, ensures accessible and adaptable AI solutions.

According to Gartner’s 2023 AI Semiconductors report, titled Forecast: AI Semiconductors, Worldwide, 2021-2027the use of artificial intelligence techniques in data centers, edge computing and endpoint devices requires the deployment of optimised semiconductor devices. Revenue from these AI semiconductors is forecast to be $111.6 billion by 2027, growing by a five-year CAGR of 20%.

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