suntipa

4 ms·

1. 1.▲
   by suntipa 3y ago

   The machinery is large-scale ML and discrete optimization over large/complex data structures, designed for a specific vertical industry. These algorithms run for hours and lazy eval was an engineering disaster. Our team had experienced
2. 2.▲
   by suntipa 3y ago

   The heavy numerical work is in julia, python, R, and a little custom c++ where necessary. Team productivity has gone way up.
3. 3.▲
   by suntipa 3y ago

   Bang and StrictData are fine locally but things get enormously worse when that data flows into deeply-layered libraries that I don't own. Then, I need to understand and modify the evaluation behavior of a deeply-layered external softwa
4. 4.▲
   by suntipa 3y ago

   Lazy eval opens the floodgates for complex space leaks. Suppose you have a complicated algorithm that runs until it reaches mathematical convergence. In a lazy language like Haskell, those cycles of iteration/recursion can accumulate t
5. 5.▲
   by suntipa 3y ago

   Lazy evaluation also implies that Haskell programs can crash based on their input . That doesn't imply big input, simply that the input caused a space leak the author hadn't considered. Try selling that to your boss who runs a mi