Stream: helpdesk (published)

Topic: Lazy array operations

view this post on Zulip Jesper Stemann Andersen (Dec 15 2024 at 10:58):

I'm working on MLX.jl to provide access to the MLX array framework (in particular for machine learning on Apple platforms).

In MLX almost all (array) operations are lazy (to make it possible to optimize a computational graph), i.e. operations are not executed until eval is called, e.g.:

>> import mlx.core as mx
>> a = mx.array([1, 2, 3, 4])
>> b = mx.array([1.0, 2.0, 3.0, 4.0])
>> c = a + b    # c not yet evaluated
>> mx.eval(c)  # evaluates c
>> c = a + b
>> print(c)     # Also evaluates c

(sorry for the "P-language" example :smile:)

How to best represent lazy arrays and operations on lazy arrays in Julia?
I have so far found Lazy.jl, LazyArrays.jl, and Thunks.jl (:top_hat: tip to Dagger.jl) - and there is also Thunks in ChainRulesCore, but not sure which approach would be best... suggestions?

Last updated: Dec 28 2024 at 04:38 UTC