Machine Learning Drives High-Level Synthesis Boom

June 6th, 2019 – By Kevin Fogarty

When a  company puts together a software/hardware design team, it’s not a bad idea to make sure where the final responsibility lies.

Asking the right questions
“In China I had a long conversation with the hardware engineer about what we were trying to do, and it eventually became clear he was not the one calling the shots,” said Kurt Shuler, vice president of marketing at Arteris IP. “It was the software architect calling the shots, so we all got together and that let us move forward once I realized the chip was defined by the algorithm, not the other way around.

”But the software architect doesn’t always have a good feel for the hardware. “The other problem we had was that, often, a software architect won’t be that good at abstracting down to the transistor level, and the hardware architect may not be good at abstracting up to the software, so you have to kind of walk them through that,” said Shuler.

Insisting on tight integration and optimization of software with hardware also may be a good way to coordinate development, but it doesn’t always reflect realistic performance requirements. Shuler noted that one way to help customers think about the problem is, rather than asking the hardware architect what would happen if the chip didn’t live up to expectations, to ask what the impact on the device would be if they were to remove the chip and replace it with an off-the-shelf inference chip that would have been completely generic to the application.

For more information, please download the Arteris FlexNoC Interconnect IP datasheet.

To read the entire article on the SemiEngineering page, please click here: https://semiengineering.com/machine-learning-drives-high-level-synthesis-boom