E1M-X V2N
The E1M-X V2N is a high-performance Edge AI module powered by the Renesas RZ/V2N processor, combining quad Cortex-A55 application cores with a dedicated DRP-AI3 accelerator for real-time vision and inference workloads.
Overview
| Parameter | Value |
|---|---|
| Application Core | Quad Arm Cortex-A55 @ 1.8 GHz |
| Real-Time Core | Arm Cortex-M33 |
| AI Accelerator | Renesas DRP-AI3 |
| AI Performance | 4 TOPS (dense) |
| Module Dimensions | 65 x 45 x 5 mm |
| Form Factor | E1M SODIMM |
| Price | $89 |
Key Features
- Quad Cortex-A55 @ 1.8 GHz for Linux-capable application processing
- Cortex-M33 real-time subsystem for low-latency sensor fusion and motor control
- DRP-AI3 at 4 TOPS (dense) for efficient on-device neural network inference
- Compact 65 x 45 x 5 mm footprint for space-constrained designs
- E1M SODIMM connector for plug-in integration with carrier boards
Block Diagram
Processor Details
Application Cores (Cortex-A55)
The four Cortex-A55 cores run at up to 1.8 GHz and support a full Linux distribution. They handle application logic, networking, display output, and pre/post-processing for AI pipelines.
Real-Time Core (Cortex-M33)
The Cortex-M33 subsystem operates independently and can run bare-metal or RTOS firmware via the ALP SDK. It is ideal for:
- Sensor data acquisition
- PWM and motor control
- Safety-critical deterministic tasks
DRP-AI3 Accelerator
The DRP-AI3 engine provides 4 TOPS of dense inference performance and supports common neural network operators. Model conversion is handled through the Renesas DRP-AI Translator toolchain.
Getting Started
- Connect the E1M-X V2N to a compatible carrier board via the SODIMM connector.
- Flash the Linux BSP to the application cores.
- Install the ALP SDK for Cortex-M33 development.
- Follow the Quick Start guide to deploy your first AI model.