Update banner for the lastest blog post

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Keavon Chambers 2022-06-06 16:09:42 -07:00
parent 8923b68e30
commit 0f93cc1e17

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@ -3,7 +3,7 @@ title = "Distributed computing in the Graphene runtime"
date = 2022-05-12
[extra]
banner = "https://static.graphite.rs/content/blog/2022-05-12-distributed-computing-in-the-graphene-runtime.png"
banner = "https://static.graphite.rs/content/blog/2022-05-12-distributed-computing-in-the-graphene-runtime__2.png"
author = "Keavon Chambers"
reddit = "https://www.reddit.com/r/graphite/comments/unw45k/blog_post_distributed_computing_in_the_graphene/"
twitter = "https://twitter.com/GraphiteEditor/status/1524664083554791424"
@ -43,6 +43,8 @@ For security and portability, user-authored nodes are compiled into WebAssembly
In the product architecture, Graphene is a distributed runtime environment for quickly processing data in the node graph by utilizing a pool of CPU and GPU compute resources available on local and networked machines. Jobs are run where latency, speed, and bandwidth availability will be most likely to provide a responsive user experience.
![Graphene in a local and cloud environment](https://static.graphite.rs/content/blog/2022-05-12-distributed-computing-in-the-graphene-runtime/local-and-cloud.png)
## Scheduler
If users are running offline, their CPU threads and GPU (or multiple GPUs) are assigned jobs by the local Graphene scheduler. If running online, some jobs are performed locally while others are run in the cloud, an on-prem compute cluster, or just a spare computer on the same network. The schedulers generally prioritize keeping quicker, latency-sensitive jobs local to the client machine or LAN while allowing slower, compute-intensive jobs to usually run on the cloud.