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arikrahman 17 hours ago [-]
Any relation to the smash hit SHMUP of the same name?
viktorsovietov 17 hours ago [-]
No
cma256 16 hours ago [-]
> Rayforce is a library you link, not a server you deploy. The C API is small enough to wrap from any language with an FFI.
I'm familiar with large-scale, commercial, client-server use cases for columnar analytics and graph traversal but what is the use case for an embedded server like this?
392 9 hours ago [-]
Perhaps the fact that 99+% of today's workloads could be running on the client if it were as easy as shipping Rayforce and the data directly to the client.
Besides that, pure C that you can embed into your app is much easier to deploy for some (and likely 100x more performant) than stuff that comes via Helm chart [cries in JVM 'big'-data solutions]
hetoku 16 hours ago [-]
[dead]
noelwelsh 17 hours ago [-]
I thought "morsel-driven" was AI slop, but it turns out to be in common usage in the HPC world. So I learned something from this post!
tosh 17 hours ago [-]
afaiu morsel-driven means the workload gets turned into 'smallish' chunks (morsels)
instead of having to pre-allocate upfront (e.g. 4 nodes get 1/4 each) it is more granular and dynamic
a worker that's "done" can request another morsel
pragmatic approach because nodes might not all be equally fast (cache, cpu frequency, throttling, …) and also some morsel workloads take longer than others depending on the values they contain and what kind of work needs to get done
so this approach tends to balance out nicely
I'm sure someone else can explain it better / correct me (please do!)
noelwelsh 16 hours ago [-]
When I read up, it sounded like the same idea as work-stealing to me. Not surprising that different fields come up with the same idea under different terminology.
adsharma 10 hours ago [-]
DuckDB and LadybugDB use the same terminology to describe internals.
I'm familiar with large-scale, commercial, client-server use cases for columnar analytics and graph traversal but what is the use case for an embedded server like this?
Besides that, pure C that you can embed into your app is much easier to deploy for some (and likely 100x more performant) than stuff that comes via Helm chart [cries in JVM 'big'-data solutions]
instead of having to pre-allocate upfront (e.g. 4 nodes get 1/4 each) it is more granular and dynamic
a worker that's "done" can request another morsel
pragmatic approach because nodes might not all be equally fast (cache, cpu frequency, throttling, …) and also some morsel workloads take longer than others depending on the values they contain and what kind of work needs to get done
so this approach tends to balance out nicely
I'm sure someone else can explain it better / correct me (please do!)