3 ms·
I mean that's obvious nonsense. Even in ML, which I work in, optimizing a data pipeline or model code to be 3x faster means you can run 3 experiments a day ins
by VHRanger 3y ago
I mean that's obvious nonsense.
Even in ML, which I work in, optimizing a data pipeline or model code to be 3x faster means you can run 3 experiments a day instead of 1.
There's a huge chilling effect from slow code in research iteration. But par for the course as academic code tends to be absolute trash.
- hedora 3y agoIdeally, a performance-related systems dissertation would achieve at least 10x vs. state of the art, but showing that is going to inevitably involve stacking many 10-20% optimizations just to get to par. Of course, there is plenty of low quality academic work that only compares to some existing system that has incomprehensibly bad performance, then shows a 10% improvement. That sort of research work should definitely be avoided.
- VHRanger 3y agoMy point isn't when you should be optimizing to the point that the optimization is publishable. My point is that you should be writing fast optimized code by default in ML research because you tend to throw large volumes of data at that code multiple times a day, and slow code reduces the number of experiments you can run. This isn't what I see however, lots of research code is horribly slow.