C h a p t e r 3
With multiple design considerations,
developing edge AI hardware solutions
can often be a time-consuming and
arduous task. A designer can take several
different avenues to simplify the design
process and reduce time to market.
First, considering the broader ecosystem
is crucial for success when designers
are selecting components. Broadly,
ecosystem considerations encompass
the hardware components themselves
and their interoperability, the accessibility
of vendor support, and the availability
of development tools and software
frameworks. When selecting components
within a system, designers must ensure
that processors, memory, and other
peripherals work together cohesively to
achieve optimal performance.
For instance, certain AI accelerators
may require specific types of high-
bandwidth memory to function efficiently.
By choosing components from an
established ecosystem, designers
can reduce integration challenges by
leveraging prevalidated combinations
known to work well together. Often,
assurances of component interoperability
are established through strong
partnerships between component
SIMPLIFYING DEVELOPMENT:
THE ROLE OF PRETESTED
BUILDING BLOCKS
Choosing components that
deliver the best performance for
specific AI workloads requires
a deep understanding of the
hardware and software interplay.
This includes selecting the right
processors, memory, storage, and
AI accelerators."
Barry Chang
Director of Advantech Edge Server & AI Group,
Advantech
15
5 Experts on Addressing the Hidden Challenges of Embedding Edge AI into End Products
