Renesas Electronics introduced the RA8P1 microcontroller (MCU) Group targeted at Artificial Intelligence (AI) and Machine Learning (ML) applications, as well as real-time analytics. Designed for running AI on device, the new MCUs establish a new performance level by combining 1GHz Arm Cortex-M85 and 250MHz Cortex-M33 CPU cores with the Arm Ethos-U55 Neural Processing Unit (NPU). This combination delivers the highest CPU performance of over 7300 CoreMarks and AI performance of 256 GOPS at 500MHz.
Available in single- and dual-core MCUs models, with embedded MRAM and dedicated peripherals optimized for vision and voice AI plus real-time analytics, the Renesas RA8P1 is optimized for edge and endpoint AI applications, using the Ethos-U55 NPU to offload the CPU for compute intensive operations in Convolutional and Recurrent Neural Networks (CNNs and RNNs). The new NPU supports most commonly used networks, including DS-CNN, ResNet, Mobilenet TinyYolo and more. Depending on the neural network used, the Ethos-U55 provides up to 35x more inferences per second than the Cortex-M85 processor on its own.
The RA8P1 MCUs are manufactured on the 22ULL (22nm ultra-low leakage) process from TSMC, enabling ultra-high performance with very low power consumption. This process also enables the use of embedded Magnetoresistive RAM (MRAM) in the new MCUs. MRAM offers faster write speeds along with higher endurance and retention compared with Flash.
“There is explosive growth in demand for high-performance edge AIoT applications. We are thrilled to introduce what we believe are the best MCUs to address this trend,” says Daryl Khoo, Vice President of Embedded Processing Marketing Division at Renesas. “The RA8P1 devices showcase our technology and market expertise and highlight the strong partnerships we have built across the industry. Customers are eager to employ these new MCUs in multiple AI applications.”
“The pace of innovation in the age of AI is faster than ever, and new edge use cases demand ever-improving performance and machine learning on-device,” says Paul Williamson, senior vice president and general manager, IoT Line of Business at Arm. “By building on the advanced AI capabilities of the Arm compute platform, Renesas’ RA8P1 MCUs meet the demands of next generation voice and vision applications, helping to scale intelligent, context-aware AI experiences.”
“It is gratifying to see Renesas harness the performance and reliability of TSMC 22ULL embedded MRAM technology to deliver outstanding results for its RA8P1 devices,” adds Chien-Hsin Lee, Senior Director of Specialty Technology Business Development at TSMC. “As TSMC continues to advance our embedded non-volatile memory (eNVM) technologies, we look forward to strengthening our long-standing collaboration with Renesas to drive innovation in future groundbreaking devices.”
Renesas has integrated dedicated peripherals, ample memory and advanced security. For vision AI, a 16-bit camera interface (CEU) is included that supports sensors up to 5 megapixels, enabling camera and demanding Vision AI applications. A separate MIPI CSI-2 interface offers a low pin-count interface with two lanes, each up to 720Mbps. In addition, multiple audio interfaces including I2S and PDM support microphone inputs for voice AI applications.
The RA8P1 offers both on-chip and external memory options for efficient, low latency neural network processing. The MCU includes 2MB SRAM for storing intermediate activations or graphics framebuffers. 1MB of on-chip MRAM is also available for application code and storage of model weights or graphics assets. High-speed external memory interfaces are available for larger models. SIP options with 4 or 8 MB of external flash in a single package are also available for more demanding AI applications.
New RUHMI Framework
Along with the RA8P1 MCUs, Renesas has introduced RUHMI (Renesas Unified Heterogenous Model Integration), a comprehensive framework for MCUs and MPUs. RUHMI offers efficient AI deployment of the latest neural network models in a framework agnostic manner. It enables model optimization, quantization, graph compilation and conversion, and generates efficient source code. RUHMI provides native support for machine-learning AI frameworks such as TensorFlow Lite, Pytorch & ONNX. It also provides the necessary tools, APIs, code-generator, and runtime needed to deploy a pre-trained neural network, including ready-to-use application examples and models optimized for RA8P1. RUHMI is integrated with Renesas’s own e2 Studio IDE to allow seamless AI development. This integration will facilitate a common development platform for MCUs and MPUs.
The RA8P1 MCUs provide leading-edge security for critical applications. The new Renesas Security IP (RSIP-E50D) includes numerous cryptographic accelerators that in concert with Arm TrustZone, provide a comprehensive and fully integrated secure element-like functionality. The new MCUs also provides strong hardware Root-of-Trust and Secure Boot with First Stage Bootloader (FSBL) in immutable storage. XSPI interfaces with decryption-on-the-fly (DOTF) allow encrypted code images to be stored in external flash and decrypted on the fly as it is securely transferred to the MCU for execution.
Renesas provides a wide range of easy-to-use tools and solutions for the RA8P1 MCUs, including the Flexible Software Package (FSP), evaluation kits and development tools. FreeRTOS and Azure RTOS are supported, as is Zephyr. Several Renesas software example projects and application notes are available to enable faster time to market.
The RA8P1 MCUs are available now. Renesas is also shipping an RA8P1 Evaluation Kit. More information is available at renesas.com/RA8P1. Samples and kits can be ordered either on the Renesas website or through distributors.
www.renesas.com/MCUs
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