3 ms·

"Optimal" in this context means it never repeats the work of beta reduction when it doesn't have to. Ie, evaluating `(\x -> x + x) (2 * 2)` only evaluates `2 *

"Optimal" in this context means it never repeats the work of beta reduction when it doesn't have to. Ie, evaluating `(\x -> x + x) (2 * 2)` only evaluates `2 * 2` once.

rowanG077 5y ago
Why is this special? Doesn't that mean GHC is beta optimal since afaik it stores thunks to computations.
- opnitro 5y ago
  GHC is not beta optimal, due to some complications around what happens when a closures are created. (This is `HOW.md` claims)
astrange 5y ago
That's not optimal on real machines; it's often faster to recalculate x*y than to cache it. In general this "optimal" strategy seems to assume infinite memory that's all accessible at the same speed.
- opnitro 5y ago
  "Beta Optimial" != Fastest Execution strategy for all kinds of code. Just defining the term, not arguing about it's engineering application.
  - astrange 5y ago
    The project certainly says it has "drastically improved efficiency" and "uncharted levels of performance". I don't think "massively parallel" is all that good for performance either, because battery life is part of that.
    - opnitro 5y ago
      Ok well _I_ was just defining the term. I didn't write the project. You will note they provide benchmarks with data showing the efficiency gain. What's left (as a reader) is evaluate the quality of those benchmarks.
- HelloNurse 5y ago
  The compiler could have heuristics and profiling data to replace optimal but "small" reductions with cheap recomputation with even less locking where it seems like a good idea; it's an additional level of improvement rather than a competing choice. As the Python documentation says, "practicality beats purity", particularly when the sacrificed purity is only the pride of using an universal solution. In a similar vein, if typical strategies for unstable sorting of arrays in place use quicksort splitting for long spans and insertion sort for short spans it doesn' mean that either algorithm is "better".

"Optimal" in this context means it never repeats the work of beta reduction when it doesn't have to. Ie, evaluating `(\x -> x + x) (2 * 2)` only evaluates `2 * 2` once.

rowanG077 5y ago

Why is this special? Doesn't that mean GHC is beta optimal since afaik it stores thunks to computations.

opnitro 5y ago
GHC is not beta optimal, due to some complications around what happens when a closures are created. (This is `HOW.md` claims)

astrange 5y ago

That's not optimal on real machines; it's often faster to recalculate x*y than to cache it. In general this "optimal" strategy seems to assume infinite memory that's all accessible at the same speed.

opnitro 5y ago
"Beta Optimial" != Fastest Execution strategy for all kinds of code. Just defining the term, not arguing about it's engineering application.
- astrange 5y ago
  The project certainly says it has "drastically improved efficiency" and "uncharted levels of performance". I don't think "massively parallel" is all that good for performance either, because battery life is part of that.
  - opnitro 5y ago
    Ok well _I_ was just defining the term. I didn't write the project. You will note they provide benchmarks with data showing the efficiency gain. What's left (as a reader) is evaluate the quality of those benchmarks.
HelloNurse 5y ago
The compiler could have heuristics and profiling data to replace optimal but "small" reductions with cheap recomputation with even less locking where it seems like a good idea; it's an additional level of improvement rather than a competing choice. As the Python documentation says, "practicality beats purity", particularly when the sacrificed purity is only the pride of using an universal solution. In a similar vein, if typical strategies for unstable sorting of arrays in place use quicksort splitting for long spans and insertion sort for short spans it doesn' mean that either algorithm is "better".