vision, a "once-in-a-generation" technology, is a enormous and lucrative opportunity
for the semiconductor ecosystem, but compute and system-design issues post
challenges in the short term.
was the assessment of Jeff Bier, engineer and founder of the Embedded Vision
Alliance, who spoke to Cadence employees during a recent visit.
vision is...one of these once-in-a-generation technologies," Bier (pictured, right) said in
a presentation covering embedded vision technologies and their challenges and
opportunities. "The closest parallel I can draw is wireless. Wireless is a
huge industry that touches almost every aspect of technology."
technology is poised to improve safety, boost efficiency and productivity, and
simplify usability, he added.
Bier, it's clear that embedded vision's time is now because processing
technology has crossed an important threshold. He held up as an example Texas
Instruments' C6000 single-core DSP, designed for high-performance, streaming,
media-intensive applications but also optimized for cost and energy efficiency.
device has recently crossed the point at which it can perform 10 billion
multiply-accumulates a second. That's key, according to Bier, because that
performance level is a typical compute requirement for a vision application.
(threshold-crossing) is really, in my mind, the key reason...vision is
transforming from something you'd find (just) in factories with
half-million-dollar systems doing manufacturing and quality control to
something that's going to be in your living room, in your car, in
the store ... it's going to be everywhere."
markets, Bier argued, will quickly expand from established areas such as factory
automation, mil/aero, and video-game consoles to building automation, robots,
education, healthcare, field service, and other areas.
first some technology hurdles need to be reckoned with, Bier said, noting
"these are very hard problems algorithmically."
fundamental reason vision is hard is the inputs are infinitely varying,"
described at an abstracted level a typical "feed-forward" system in
which a challenge inversion occurs: At the initial stages right after image capture, the
embedded-vision system tends to focus on extremely high data rate execution as
the system processes every pixel and every color component of every pixel. So
there's a huge amount of data being processed very quickly but using relatively
simple algorithms to perform tasks such as correcting image distortion caused
by imperfect lenses, Bier said.
at the front end, the system is handling perhaps 8-10 math operations per data
item but tens or hundreds of millions of data items per second. That "huge" amount of
computing quickly pushes the processor up to billions of operations per second,
inversion occurs as you move down that feed-forward pipeline. Farther down, the
data rates fall "radically, down to thousands of data items per
second" but the algorithm complexity soars, from "tens of lines of
code to hundreds of thousands of lines of code," Bier said.
Because the algorithms are written at that point to help the system understand
interesting and tricky features of the landscape. For example, is what the sensor
is seeing a traffic lane or a seam in the road pavement?
the data rates go down as we get toward the end of the pipeline, but the
algorithm complexity goes way, way up. As you go toward the end of the line, you've got heuristics and machine learning and millions of lines of code
operating at very low data rates."
the embedded vision work load is very heterogenous, with different kinds of
algorithms often operating on different data types. That requires a heterogenous
processor to implemement it, Bier said.
is, he added, a sort-of land grab in fact for how to process these systems.
processor + CPU
noted that the heterogenous approach is driven in part by CPU limitations:
CPUs, while easy to use, often run out of performance and memory bandwidth in
these streaming-intensive applications.
added that companies such as Tensilica, which Cadence acquired in the spring,
are stepping in finely tuned DSP cores to take advantage of the growing market.
Bier, embedded vision is clearly the Wild West, with opportunity
for many. Standards are unsettled (and may never be); the ecosystem is just
forming (which his Embedded Vision Alliance is helping facilitate), and the
demand for vision solutions has tremendous potential.
a huge opportunity for companies in the semiconductor industry," Bier
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