Overview
The RZ/V2N Fast Prototyping Board (FPB‑RZV2N) is an official Renesas evaluation board for fast prototyping. This board supports a wide range of pre-trained AI applications included in the AI software development kit (AI SDK) provided by Renesas. It significantly reduces the man-hours required for AI development, allowing easy evaluation.
For more complex RZ/V2N peripheral interface evaluation and software development, the RZ/V2N-EVK is also available.
Features
- Device: RZ/V2N R9A09G056N44GBG
- Cortex-A55 × 4, Cortex-M33 × 1
- AI accelerator DRP-AI3
- BGA, 15mm × 15mm 840-pin, 0.5mm pitch
- RZ/V2N Fast Prototyping Board
- CPU: RZ/V2N
- PMIC: RAA215300A2GNP#HA7
- Clock generator: 5L35023B-616
- Main memory: LPDDR4X 8GB × 1
- External memory: microSD × 1
- High-speed interfaces:
- Gigabit Ethernet × 1 port
- USB 3.2 Gen2 × 1ch (Host only)
- USB 2.0 × 1ch (OTG)
- MIPI® CSI-2® × 1ch
- HDMI® Tx × 1ch
- Notes
- SD card is not included.
- AC adapter is not included. Please prepare a 45W or higher USB Power Delivery (PD) compliant power adapter and USB cable separately.
Products in the Design
| 5L35023 | VersaClock 3S Programmable Clock Generator |
| DA9215 | Multiphase 15A and 5A Output Current |
| ISL80111 | Ultra Low Dropout 1A Low Input Voltage NMOS LDOs |
| ISL80505 | High Performance 500mA LDO |
| RAA211250 | Integrated FET 30V, 5A Synchronous Buck Regulator with Internal Compensation and Programmable Frequency |
| RAA215300 | High-Performance 9-Channel PMIC Supporting DDR Memory, with Built-In Charger and RTC |
| SLG59M1512V | 5.5V, 80mΩ, 1A Dual Channel Load Switch with Discharge |
Sample & Buy
RZ/V2N Fast Prototyping Board
Product Comparison
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| FPB-RZV2N | RZ/V2N-EVK | |
| Description | RZ/V2N Fast Prototyping Board | RZ/V2N Quad-core Vision AI MPU Evaluation Kit |
Videos & Training
The RZ/V2N Fast Prototyping Board (FPB-RZV2N) is a compact and cost-effective evaluation board powered by the RZ/V2N, designed to help developers quickly start AI evaluation and prototyping. In this video, we provide an overview of the board's key features, hardware components, and development environment, enabling rapid development of edge AI applications.


