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SemiEngineering: Why TinyML is Such a Big Deal

Excerpt from article: “Why TinyML is Such a Big Deal

“If you just compile everything onto the controller, even at the bare metal level, it will be more energy-efficient,” said Anoop Saha, market development manager at Siemens EDA.

“Because of Moore’s Law, every couple of years we have more powerful chips,” observed Saha. “So if you just wait it out, we’ll be able to run an algorithm on tiny devices.”

But fragmentation has its downsides. “The problem with TinyML is that the market is so fragmented that it cannot be economically viable to build a single IoT-specific chip,” Saha pointed out. According to him, that may mean composing systems out of smaller sub-system chips for things like the radio or security.

When it comes to ML, he notes, “The better choice is to build an accelerator, which will be cheaper, and the chances of success are higher and better as well.”

Read the entire article on SemiEngineering originally published on September 2nd, 2021.
anoop.saha@siemens.com Saha

Anoop Saha manages strategic growth initiatives for Siemens EDA digital design portfolio - including Catapult High-Level Synthesis and PowerPro. He also manages outbound and inbound marketing as well as demand generation. Anoop has 20 years experience in the EDA industry in various roles - from development to marketing, sales and strategy. He is currently working on system level power modeling, custom hardware accelerators and machine learning in EDA. Anoop earned his bachelor degree in Computer Science and Engineering from IIT Kanpur, India and is currently pursuing his Executive MBA from The Wharton School.

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This article first appeared on the Siemens Digital Industries Software blog at https://blogs.stage.sw.siemens.com/hlsdesign-verification/2021/09/03/tinyml-is-aimed-at-implementing-machine-learning-on-severely-resource-constrained-systems-its-both-a-concept-and-an-organization-and-it-has-acquired-significant-momentum-over-the-l/