Skip to content
Discussion options

You must be logged in to vote

CubeCL kernels are JIT-compiled, not AOT-compiled. It does have a persistent compilation cache, along with an autotuning cache. But it's not AOT: kernels are still generated when first encountered and then reused on later runs.

You can, however, pre-warm those caches and ship them with your application. For known workloads and hardware, this should have similar practical benefits while retaining JIT as a fallback.

And yes, CubeCL can absolutely be used for non-AI workloads. It is a general-purpose compute language and runtime. Burn is its main consumer and drives much of its development, so many features are motivated by ML workloads, but CubeCL itself is not limited to this domain.

Replies: 1 comment 1 reply

Comment options

You must be logged in to vote
1 reply
@CytITDchen
Comment options

Answer selected by CytITDchen
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Category
Q&A
Labels
None yet
2 participants