Excerpt from article: “Mentor Highlights HLS Customer Use in Automotive Applications”
This is where HLS shines. You can develop code in C/C++ and experiment with architectures at least an order of magnitude more efficiently than you can at RTL since these are algorithmic problems most easily represented in that format (or in MATLAB or the common ML frameworks, to which the Siemens EDA HLS solutions can connect). You can also run verification of those giant datasets at this level, multiple orders of magnitude faster than RTL-based verification. (I believe this should even be faster than emulation since C-modeling is close to virtual prototyping which runs at near-real time performance.) And in response to late changes, you can incorporate those changes at the C-level and re-verify and re-synthesize pretty much hands-free, limiting impact on your schedule.
Siemens EDA recently released a white-paper (see below) on outcomes for three of their customers using their Catapult flow for designs in the automotive imaging pipeline. Bosch, a well-known mobility Tier1, are finding it valuable to enhance their own differentiation by building their own IPs and ICs for image recognition. This was the example where a design team had to produce three designs in a year. Using the Siemens EDA flow they were able to pull this off and deliver a 30% power reduction because they were could easily experiment with and refine the architecture for power. They also commented that it will be much easier to migrate the C-based model to new designs and evolving standards than it would have been with an RTL model.
Read the entire article on SemiWiki originally published on July 30th, 2019.