Industrial AI Product of the Year
Company Name: Renesas Electronics
Product Name: Renesas RZ/G3E – 64-bit MPU with NPU for High-Performance HMI Systems Requiring AI Acceleration and Edge Computing
Supporting Statement:
The 64-bit RZ/G3E microprocessor (MPU) is a general-purpose device optimized for high-performance Human Machine Interface (HMI) applications. Combining a quad-core Arm® Cortex®-A55 running at up to 1.8GHz with a Neural Processing Unit (NPU), the RZ/G3E brings high-performance edge computing with AI inference for faster, more efficient local processing. With Full HD graphics support and high-speed connectivity, the MPU targets HMI systems for industrial and consumer segments including factory equipment, medical monitors, retail terminals and building automation.
High-Performance Edge Computing and HMI Capabilities
At the heart of the RZ/G3E is a quad-core Arm Cortex-A55, a Cortex-M33 core, and the Ethos™-U55 NPU for AI tasks. This architecture efficiently runs AI applications such as image classification, object recognition, voice recognition and anomaly detection while minimizing CPU load. Designed for HMI applications, it delivers smooth Full HD (1920×1080) video at 60fps on two independent displays, with output interfaces including LVDS (dual-link), MIPI-DSI, and parallel RGB. A MIPI-CSI camera interface is also available for video input and sensing applications.
“The RZ/G3E builds on the proven performance of the RZ/G series with the addition of an NPU to support AI processing,” said Yasushi Iwase, Senior Manager of Embedded Processing at Renesas. “By using the same Ethos-U55 NPU as our recently announced RA8P1 microcontroller, we’re expanding our AI embedded processor portfolio and offering a scalable path forward for AI development. These advancements address the demands of next-generation HMI applications across vision, voice and real-time analytics with powerful AI capabilities.”
The RZ/G3E is equipped with a range of high-speed communication interfaces essential for edge devices. These include PCI Express 3.0 (2 lanes) for up to 8Gbps, USB 3.2 Gen2 for fast 10Gbps data transfer, and dual-channel Gigabit Ethernet for seamless connectivity with cloud services, storage, and 5G modules.
Low-Power Standby with Fast Linux Resume
Starting with the third-generation RZ/G3S, the RZ/G series includes advanced power management features to significantly reduce standby power. The RZ/G3E maintains sub-CPU operation and peripheral functions while achieving low power consumption around 50mW and around 1mW in deep standby mode. It supports DDR self-refresh mode to retain memory data, enabling quick wake-up from deep standby for running Linux applications.
Key Features of RZ/G3E
• CPU: Quad-core Cortex-A55 (up to 1.8GHz), Cortex-M33
• NPU: Ethos-U55 (512 GOPS)
• HMI: Dual Full HD output, MIPI-DSI / Dual-link LVDS / Parallel RGB, 3D graphics, H.264/H.265 codec
• Memory Interface: 32-bit LPDDR4/LPDDR4X with ECC
• Connectivity for 5G Communication: PCIe 3.0 (2 lanes), USB 3.2 Gen2, USB 2.0 x2, Gigabit Ethernet x2, CAN-FD
• Operating Temperature: -40°C to 125°C
• Package Options: 15mm square 529-pin FCBGA, 21mm square 625-pin FCBGA
• Product Longevity: 15-year supply under Product Longevity Program (PLP)
Summary
RZ/G3E is a microprocessor (MPU) integrated with quad CPU and NPU in one chip, improving power efficiency, reliability, and security for human machine interface (HMI) applications. The RZ/G3E offers rich HMI functions including graphics engine (GPU), video codec, multi-screen full HD output, and Neural Processing Unit (NPU) for edge computing functions. In addition to the Cortex-A55 quad core delivering a powerful 1.8GHz to run both HMI and edge computing functions, RZ/G3E also features a Cortex-M33 core to enable low power operation. The combination of two different cores enables users to build products with both high performance and low power consumption.
More information at: https://www.renesas.com/rzg3e
Entry ID: 7533
Supporting Documents
REN_RZG3E-Datasheet_r01ds0477ej0115-rzg3e.pdf, REN2520_RZG3E_pressphoto.jpg
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