After months of freezing temperatures in Pittsburgh, a 78 degree wind hit me as I stepped out of the office yesterday. While I’m sure it will be cold again by the time this blog gets published, yesterday made me think about how things are changing.
In the 2017 annual HLS survey, we confirmed that wireless is the fastest growing market segment for high-level synthesis (HLS). That wasn’t much of a surprise, because for reasons I outlined previously, wireless and HLS go together like peanut butter and jelly.
| https://youtu.be/s8MDNFaGfT4 | Random side note: April 2, 2018 will be Peanut Butter and Jelly Day in the United States. Other locales may celebrate other childhood sandwiches on different days. |
It was surprising to me that a significant number of our users were leveraging Stratus HLS for machine learning applications. Back in the early days, I used to know every user of our high-level synthesis tool (or “behavioral synthesis” tool before that!). Then, later, at least I knew each group. But now, as things have progressed, that’s no longer the case… nor is it even possible.
Nonetheless, I set forth on the quest to find out… what machine learning applications are our users building? Fast forward several months and much laughing in my face, I realize two things.
- There are more machine learning and artificial intelligence applications being developed with Stratus HLS than I expected, even after the survey results.
- There is no way I’m going to find out any details of the applications. These are the cutting edge of the cutting edge, and the actual applications are a closely guarded secret.
But along the way, I learned something arguably more important… why so many machine learning applications are designed with HLS.
The common thread seems to be the intersection of three things.
- There is no pre-existing IP to reuse or modify.
- There are multiple algorithms / architectures under consideration.
- To evaluate the algorithms and architectures, designers need to rapidly explore implementations of each
I find it interesting that the challenges for machine learning designs are similar, but not identical, as those for cutting edge wireless designs. In wireless designs, being able to modify the high-level design as the spec changes is a huge benefit of HLS. When designing machine learning applications, modifying the high-level design to explore architectures and algorithms is fundamental to the design process.
In this niche, HLS enables a fundamental change to the way hardware is designed. Perhaps this is the harbinger of changes to come in hardware design.
In the mean time, if you would like to reflect on a different wind of change, put on your headphones and click on Scorpions’ “Wind of Change” music video. After all, you deserve four minutes and 43 seconds to recharge via power ballad. If you truly cannot find those few minutes to relax this week, then at least go see Black Panther this weekend. If you like the superhero genre, you’ll love the movie. Our resident movie critic gave it 9 stars… and if you know teenagers at all, you know almost nothing in life is worth 9 stars! | www.youtube.com/watch |