Re:Demystifying Differentiable Programming (2018)
by ignoramous on Monday February 17, 2020 @03:29AM
(#22346328)
> Do offline analysis of the statistics from the previous run, speculate on different settings and replay them
Reminds me of Dynimize https://news.ycombinator.com/item?id=17025627
Re:Demystifying Differentiable Programming (2018)
by hinkley on Monday February 17, 2020 @02:57PM
(#22350203)
Databases have perhaps done this the longest. I think this notion first came up for me when I was thinking about complex operations on large data structures in application memory, and the way that hand-coded tuning parameters rot over time, or are counterproductive for your largest customers.
I think a few compilers sprouted the ability to take perf logs from previous runs into account when compiling, maybe ten years back now, but nothing is there for off-line optimization in situ. And again my choice of input data will never be perfect for all of my users. I can tune for my biggest customer or be populist.
With more and more cores coming, I expect to see this sort of thing happen once we accept that we can’t really use all of them.