unit (MCU) with a built-in AI accelerator.
The pretested nature of these modules
ensures compatibility between the
hardware and software stack, reducing
integration issues and accelerating
development cycles.
Additionally, these building blocks often
provide flexibility in terms of power
and performance scaling. Designers
can choose modules with different
performance tiers, from ultra-low-power
MCUs with integrated AI accelerators
for battery-operated devices to high-
performance SoCs with dedicated
NPUs for more compute-intensive edge
applications. This scalability allows for
easier product line expansions and
adaptations to different use cases
without completely redesigning the
hardware platform.
By leveraging these pretested and
validated building blocks, designers
can focus on optimizing their specific
AI models and applications rather than
getting bogged down in low-level hardware
design and integration challenges.
Micron simplifies the design process
and reduces time to market for edge AI
customers by partnering with leading
SoM producers to
• Offer pretested building blocks and
validated system solutions optimized
for edge AI applications
• Deliver a suite of software development
kits and tools tailored to various edge
AI use cases and memory configurations
• Work closely with SoM technical teams
who offer hands-on support and
expertise to help customers select the
right memory technologies and optimize
their designs for specific AI workloads
C h a p t e r 3 | S i m p l i f y i n g D e v e l o p m e n t : T h e R o l e o f P r e t e s t e d B u i l d i n g B l o c k s
By using pretested, verified
and validated building blocks,
developers can significantly
reduce development time, enhance
reliability, simplify integration,
achieve cost efficiency, focus on
core competencies, and ensure
scalability and flexibility."
Peter Müller
VP Product Center Modules, Kontron
18
5 Experts on Addressing the Hidden Challenges of Embedding Edge AI into End Products
