Partners PRs

Andes Technology, a leading supplier of high-performance, low-power 32/64-bit RISC-V processor cores and AI acceleration solutions, proudly announces the launch of AndesAIRE™ AnDLA™ I370, its latest Deep Learning Accelerator (DLA), engineered to bring advanced neural network performance to cost-sensitive edge and endpoint AI applications. Building on the success of its predecessor AnDLA™ I350, the new AnDLA™ I370 significantly broadens AI inference capabilities by adding support for Audio/Voice AI applications, RNN models, INT16 data type, and configurable bus widths. Tailored for performance, scalability, and power efficiency, the AnDLA™ I370 is designed to meet the rapidly growing demands for on-device intelligence in edge computing, IoT, and embedded vision applications.

The AndesAIRE™ AnDLA™ I370 supports industry-standard deep learning frameworks including TensorFlow Lite, PyTorch, and ONNX, making it easier for developers to deploy AI workloads across platforms. Capable of executing complex neural network operations such as convolution, fully connected, elementwise, pooling, activation, channel padding, upsampling, and more, the I370 integrates internal DMA and local memory and boosts execution efficiency through operator and layer fusion.

Key features include:

• Up to 2 TOPS (Tera Operations Per Second)/GHz
• Configurable MAC count and local memory size for usage flexibility
• Expanded model support for recurrent neural networks (RNNs)
• Enhanced INT16 and INT8 precision support for optimal performance-efficiency balance

Alongside the new accelerator, Andes offers the AndesAIRE™ NN SDK, a comprehensive toolkit for end-to-end neural network development. Built to accelerate deployment on AnDLA™ and AndesCore™ RISC-V platforms, the SDK includes:

• AndesAIRE™ NNPilot™ – Model analysis, pruning, quantization, and deployment tool suite
• LiteRT / LiteRT for Microcontrollers (formerly TFL/TFLM) –Inference frameworks optimized for various host environments
• AnDLA™ Driver and Runtime – Auto-generated code for efficient integration with applications
• AndesAIRE™ XNNPACK – Andes-optimized high-performance AI compute library based on open source

NNPilot™ streamlines the process from models to deployment by automatically converting models into optimized command images, completing with sample host code for easy integration in bare-metal or embedded environments.

With the AnDLA™ I370 and the new AndesAIRE™ NN SDK, Andes continues to pave the way for flexible, high-efficiency AI acceleration at the edge. Whether powering smart cameras, intelligent sensors, industrial automation, wearable AI, true wireless stereo (TWS), or hearing air earbuds, AndesAIRE™ makes it possible for “AI Runs Everywhere” —smarter, faster, and more efficiently than ever before.

“AI at the edge demands compact yet powerful computing solutions,” said Dr. Charlie Su, CTO and President of Andes Technology. “The AnDLA™ I370 delivers flexibility, high throughput, and seamless integration with popular frameworks, empowering developers to bring intelligence to a broader range of devices.”

“What sets Andes apart is the seamless fusion of our leading AndesCore™ RISC-V processors with our purpose-built AnDLA™ deep learning accelerators,” said Simon TC Wang, Senior Technical Marketing Manager of Andes Technology. “RISC-V processors and NN Library secure the flexibility and future-proof for the rapid growth of the AI/ML applications while the accelerator guarantees the high performance and the compute density. This tight integration leverages the best of both worlds to enable a highly efficient, scalable, and configurable AI/ML platform that is uniquely positioned to meet the demands of edge and endpoint intelligence.”

For more information, visit www.andestech.com or contact sales@andestech.com.

If you would like to learn more about AndesAIRE™ AnDLA™ I370, we warmly invite you to join the annual Andes RISC-V CON Hsinchu! The event will take place on June 10, from 1:30 PM to 5:00 PM at the Sheraton Hsinchu Hotel. We sincerely look forward to seeing you there!