Renesas Electronics Corporation, a supplier of advanced semiconductor solutions, has introduced the RZ/V series of microprocessors (MPUs), which feature Dynamically Reconfigurable Processor (DRP-AI). This is Renesas’ exclusive vision-optimized artificial intelligence (AI) accelerator.
The first product in the series, the RZ/V2M is designed to deliver a combination of real-time AI inference and advanced power efficiency in embedded devices. The demand to have real-time, AI-based person and object recognition functionality in applications — such as surveillance cameras for industrial and infrastructure, as well as product scanners and POS terminal cameras has been growing rapidly.
However, the higher power consumption and heat generation required for AI processing are introducing new challenges for embedded developers. The RZ/V2M leverages the DRP-AI’s excellent power efficiency to realize power consumption as low as 4W (typ.). This eliminates the need for heat sinks and cooling fans, and greatly simplifyies heat dissipation measures. This enables RZ/V2M to be used in compact devices or help to minimize equipment sizes, expanding the opportunities to incorporate AI in embedded devices. It also helps to reduce bill-of-materials (BOM) costs.
“The new RZ/V Series delivers both high performance and low power consumption, the two key issues that are keeping Vision AI processing from achieving a higher level of real-time performance,” said Hiroto Nitta, senior VP, Head of SoC Business, IoT and Infrastructure Business Unit at Renesas. “The RZ/V Series will dramatically expand the range of AI applications in embedded devices through object recognition, for example cameras in smart shopping cart systems that automatically calculate totals based on the cart items, robots in factories that can safely work together with humans, and medical cameras that assist doctors in making diagnoses.”
In addition to the DRP-AI, the RZ/V2M features an imaging signal processor (ISP) capable of processing high-resolution 4K pixels at 30 frames per second. The ISP employs high-dynamic range (HDR) functionality capable of handling images with large differences between brightness and darkness, noise reduction functionality, and distortion correction functionality to substantially boost precision in AI recognition. This ensures the ability to produce clear images regardless of factors, such as the weather, the time of day, and the installation location.
With these integrated features, the RZ/V2M delivers a major innovation capable of bringing highly accurate AI and low power consumption to a wide range of embedded devices. The DRP-AI vision-optimized AI accelerator is an intellectual property (IP) evolved from the DRP built into the RZ/A2M, designed for tasks such as reading 2D barcodes and iris recognition. To magnify operation processing capabilities, the DRP functionality is combined with an AI-MAC (multiply and accumulate) circuit, making it ideal for applications utilizing AI inference. The new IP core is capable of AI processing with approximately 10 times the power efficiency of the DRP, achieving the 1 TOPS/W class.
Also, since the DRP can dynamically change the configuration of its operation circuits every clock cycle, the DRP-AI adds the ability to flexibly support ever-evolving and advancing AI algorithms. Renesas also plans to offer the DRP-AI Translator, a tool dedicated for DRP-AI based development that simplifies the implementation of users’ learned AI models into embedded devices.
- CPU with dual Arm Cortex-A53 cores with an operating frequency of 1 GHz
- DRP-AI vision-optimized AI accelerator (1 TOPS/W class)
- ISP supporting 4K/30 FPS
- Image processing engine for a variety of functions, including face detection
- H.265/H.264 encoder/decoder Support for CMOS sensor interfaces (SLVS-EC and MIPI-CSI) that enable simultaneous input from two cameras
- Support for high-speed interfaces (USB3.1, PCI-Express and Gigabit-Ethernet)
- Support for display interfaces (MIPI-DSI and HDMI) Power consumption as low as 4 W (typ.) 15 mm × 15 mm FCBGA package
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