eMMC: The Embedded Storage Powering On-Device AI

In today’s world of increasingly intelligent devices, efficient and reliable storage is paramount. Embedded MultiMediaCard (eMMC) has emerged as a crucial component that acts as the internal solid-state non-volatile storage for a wide range of devices handling on-device AI processing. Think of it as a compact, high-performing internal drive built directly into your phone, smart camera, or other embedded systems. This blog explores what makes eMMC such a valuable solution, especially for AI applications.

What is eMMC? The embedded solution

eMMC is essentially a system-on-a-chip, integrating NAND flash memory (the storage medium) and a controller within a single, space-saving package. This close integration offers several advantages:

• Compact form factor: Soldered directly onto the circuit board, eMMC takes up minimal space, making it ideal for portable and embedded devices where board real estate is precious.
• Enhanced performance: The integrated controller optimizes data transfer and management, resulting in generally faster performance compared to discrete components.
• Robust performance: High data speeds, often exceeding 200 MB/s, enable quicker boot times, faster application loading, and smoother overall system responsiveness.
• Low-cost: eMMC technology has been around for a long time, allowing vendors to perfect the yield on underlying memory, making it a relatively cost-effective option for on-device memory storage.
• Wide application: Commonly used in mobile devices (smartphones, tablets), IoT devices (smart home appliances, sensors), embedded systems (industrial controllers, automotive systems), and increasingly in edge computing devices.

eMMC’s role in AI applications

The demands of modern AI algorithms are significant, requiring fast data access and processing capabilities at the edge. eMMC’s high speeds make it well-suited for handling the large datasets and complex computations involved in real-time AI tasks. Examples include:

• Object detection: Quickly processing image or video data to identify and classify objects.
• Facial recognition: Analyzing facial features for identification and verification.
• Real-time analytics: Quickly processing and analyzing data streams from sensors or other sources.
• Video processing: Getting real time insights from video recording on the eMMC cards like traffic monitoring, navigation, and infotainment.

The future: Hybrid storage solutions

As AI algorithms continue to advance and require even greater performance, expect to see the rise of hybrid storage solutions that combine the strengths of different technologies. Combining eMMC for fast, on-device processing and another storage like Universal Flash Storage (UFS) for higher bandwidth applications will become more common, providing an optimal balance of speed, capacity, and cost-effectiveness. This shift will be essential to meet the increasing demands of the rapidly evolving AI industry.

Cadence MMAV VIPs support eMMC with comprehensive timing and protocol checks to catch design bugs.

Multiple predefined configurations from versions 4.4 to JESD84-B51A are available that can be plugged into the Verilog, SV and UVM verification environment. The ability to configure parameters, allow backdoor operations, and error injection enables simulation of a real time scenario. More information on Cadence Flash models is available at Cadence VIP Memory Models Website.