Edge AI refers to the deployment of AI computing and AI inference models directly on local edge devices such as sensors or Internet of Things (IoT) devices, which enables real-time data processing without constant reliance on cloud servers. Its advantages include low latency, high privacy, offline operation capabilities, bandwidth savings, and reduced transmission costs. Examples range from Internet of Things (IoT) devices like smart homes, smartphones, autonomous vehicles or Advanced Driver-Assistance Systems (ADAS), robotic arms, sensors, industrial PCs (IPCs), drones, robots, wearable devices (such as smartwatches), and AI PCs

However, Edge AI heavily relies on hardware support that provides high bandwidth, low latency, and low power consumption. This article introduces one of the high-speed data transmission interfaces: DDR/LPDDR, which plays a crucial role.
Edge AI computing, especially deep learning inference, is a data-intensive task involving massive model parameters and vast amounts of training data. If memory signals are unstable, timing error, or capacity is insufficient, even powerful AI computing chips will idle, leading to poor inference efficiency. DDR/LPDDR, with its characteristics of high bandwidth, low latency, and large capacity, acts as a "high-speed temporary workbench." It is a critical technology that enables computing chips to quickly access data and instructions. Among these, DDR is primarily used in traditional computing equipment like desktops and laptops, servers, switch and emerging applications such as AI/ML. LPDDR, on the other hand, is a low-power version specifically designed for mobile devices.

DDR Test Items
As a leading high-speed signal testing lab in the industry, iPasslabs provides the most rigorous DDR/LPDDR validation and debugging services for your products and follow the specification of JEDEC. :

1. Signal Integrity, SI

• Eye Diagram Analysis
• Overshoot/Undershoot
• Slew Rate
• Jitter
• Voltage Levels

2. Timing Parameters

• Clock:
• Write/Read
• Command/Address